El grup fa recerca interdisciplinària en àrees com la matemàtica aplicada, la teoria de sistemes i l'enginyeria del control. La recerca progressa en dues direccions interrelacionades: una teòrica, aportant coneixements a l'estat de l'art; i una aplicada, desenvolupant eines d'utilitat en sistemes del món real, particularment en sistemes mecànics, de l'enginyeria civil i, recentment, de l'àmbit biomèdic.
This paper deals with a recent design of event-driven observer-based smart sensors for output feedback control of linear systems. We re-design the triggering mechanism proposed in a previously reported system with the implementation of self-sampling data smart sensors; as a result, we improve its performance. Our approach is theoretically supported by using Lyapunov theory and numerically evidenced by controlling the inverted pendulum on the cart mechanism.
This paper presents a recent self-sampled-data control algorithm applied to nonlinear systems with actuator failures. Our approach uses the linear model of a given nonlinear system, and based on a granted actuator fault observer method, an asynchronous sampled-data fault compensator controller is then formulated. The proposed sampling rule is realized by using an event-detector monitoring signal invention. On this way, the sampled rate is self governed and asynchronous by nature. Hence, our contribution is twofold. Fist, a new auto-generated non-uniform sampled-data mechanism is stated. Second, we grant an event-triggered control law with actuator failure observation and compensation. Our findings are completely supported by employing Lyapunov’s theory. Finally, according to our numerical experiments applied to an undamped torsional pendulum, our design is able to detect a failure in the actuator device and it can stabilize the undamped torsional pendulum system presenting better performance in comparison to its open-loop deployment.
In this paper a hybrid passivity based and fuzzy type-2 controller for chaotic and hyper-chaotic systems is presented. The proposed control strategy is an appropriate choice to be implemented for the stabilization of chaotic and hyper-chaotic systems due to the energy considerations of the passivity based controller and the flexibility and capability of the fuzzy type-2 controller to deal with uncertainties. As it is known, chaotic systems are those kinds of systems in which one of their Lyapunov exponents is real positive, and hyper-chaotic systems are those kinds of systems in which more than one Lyapunov exponents are real positive. In this article one chaotic Lorentz attractor and one four dimensions hyper-chaotic system are considered to be stabilized with the proposed control strategy. It is proved that both systems are stabilized by the passivity based and fuzzy type-2 controller, in which a control law is designed according to the energy considerations selecting an appropriate storage function to meet the passivity conditions. The fuzzy type-2 controller part is designed in order to behave as a state feedback controller, exploiting the flexibility and the capability to deal with uncertainties. This work begins with the stability analysis of the chaotic Lorentz attractor and a four dimensions hyper-chaotic system. The rest of the paper deals with the design of the proposed control strategy for both systems in order to design an appropriate controller that meets the design requirements. Finally, numerical simulations are done to corroborate the obtained theoretical results.
Reset controllers are commonly used to smooth the transient response of systems. We use this technique to improve a standard baseline pitch controller for offshore wind turbines (WTs). The introduction of this strategy enhances the overall performance of the WT. In particular, the fore-aft and side-to-side accelerations of the WT tower are significantly reduced, whilst a steadier power output is obtained, in comparison to the standard baseline pitch controller. Furthermore, our designed pitch control’s main advantage, with respect to the baseline, is its ease of implementation and reduced complexity as it does not require a gain-scheduling technique, nor pitch position measurement (thus, it is insensitive to pitch sensor faults). The proposed approach has been simulated on the NREL 5-MW prototype offshore turbine model, mounted on a jacket support. The simulations are carried out using the aero-hydro-servo-elastic simulator FAST, and key observations are thoroughly discussed.
Structural health monitoring (SHM) is a very important area in a wide spectrum of fields and engineering applications. With an SHM system, it is possible to reduce the number of non-necessary inspection tasks, the associated risk and the maintenance cost in a wide range of structures during their lifetime. One of the problems in the detection and classification of damage are the constant changes in the operational and environmental conditions. Small changes of these conditions can be considered by the SHM system as damage even though the structure is healthy. Several applications for monitoring of structures have been developed and reported in the literature, and some of them include temperature compensation techniques. In real applications, however, digital processing technologies have proven their value by: (i) offering a very interesting way to acquire information from the structures under test; (ii) applying methodologies to provide a robust analysis; and (iii) performing a damage identification with a practical useful accuracy. This work shows the implementation of an SHM system based on the use of piezoelectric (PZT) sensors for inspecting a structure subjected to temperature changes. The methodology includes the use of multivariate analysis, sensor data fusion and machine learning approaches. The methodology is tested and evaluated with aluminum and composite structures that are subjected to temperature variations. Results show that damage can be detected and classified in all of the cases in spite of the temperature changes
The design of vibration control systems for the seismic protection of closely adjacent buildings is a complex and challenging problem. In this paper, we consider distributed multi-actuation schemes that combine interbuilding linking elements and interstory actuation devices. Using an advanced static output-feedback H 8 approach, active and passive vibration control systems are designed for a multi-story two-building structure equipped with a selected set of linked and unlinked actuation schemes. To validate the effectiveness of the obtained controllers, the corresponding frequency responses are investigated and a proper set of numerical simulations is conducted using the full scale North–South El Centro 1940 seismic record as ground acceleration disturbance. The observed results indicate that using combined interstory-interbuilding multi-actuation schemes is an effective means of mitigating the vibrational response of the individual buildings and, simultaneously, reducing the risk of interbuilding pounding. These results also point out that passive control systems with high-performance characteristics can be designed using damping elements.
The main objective of this paper is to design a dynamic reference trajectory based on hysteresis to avoid saturation in controlled wind turbines. Basically, the torque controller and pitch controller set-points are hysteretically manipulated to avoid saturation and drive the system with smooth dynamic changes. Simulation results obtained from a 5MW wind turbine benchmark model show that our proposed strategy has a clear added value with respect to the baseline controller (a well-known and accepted industrial wind turbine controller). Moreover, the proposed strategy has been tested in healthy conditions but also in the presence of a realistic fault where the baseline controller caused saturation to nally conduct to instability.
radouane, A.; Giri, F.; Ikhouane, F.; Ahmed-Ali, T.; Chaoui, F.; Brouri, A. International journal of adaptive control and signal processing Vol. 31, num. 3, p. 332-359 DOI: 10.1002/acs.2700 Data de publicació: 2017-03-01 Article en revista
Existing works on Wiener system identification have essentially been focused on the case where the output nonlinearity is memoryless. When memory nonlinearities have been considered, the focus has been restricted to backlash like nonlinearities. In this paper, we are considering Wiener systems where the output nonlinearity is a general hysteresis operator captured by the well-known Bouc-Wen model. The Wiener system identification problem is addressed by making use of a steady-state property, obtained in periodic regime, referred to as hysteretic loop assumption'. The complexity of this problem comes from the system nonlinearity as well as its unknown parameters that enter in a non-affine way in the model. It is shown that the linear part of the system is accurately identified using a frequency method. Then, the nonlinear hysteretic subsystem is identified, on the basis of a parameterized representation, using a prediction-error approach.
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed.
Fàbrega, C.; Parcerisa, D.; Rossell, Josep M.; Gurenko, A.; Franke, C. Journal of analytical atomic spectrometry num. 4, p. 731-748 DOI: 10.1039/C6JA00397D Data de publicació: 2017-02-10 Article en revista
Instrumental mass fractionation (IMF) of isotopic SIMS analyses (Cameca 1280HR, CRPG Nancy) was predicted by response surface methodology (RSM) for 18O/16O determinations of plagioclase, K-feldspar and quartz. The three predictive response surface models combined instrumental and compositional inputs. The instrumental parameters were: (i) X and Y position, (ii) LT1DefX and LT1DefY electrostatic deflectors, (iii) chamber pressure and, (iv) primary-ion beam intensity. The compositional inputs included: (i) anorthite content (An%) for the plagioclase model and, (ii) orthoclase (Or%) and barium (BaO%) contents for the K-feldspar model. The three models reached high predictive powers. The coefficients R2 and prediction-R2 were, respectively, 90.47% and 86.74% for plagioclase, 87.56% and 83.17% for K-feldspar and 94.29% and 91.59% for quartz. The results show that RSM can be confidently applied to IMF prediction in stable isotope SIMS analyses by the use of instrumental and compositional variables.
Among all the elements that are integrated into a structural health monitoring (SHM) system, methods or strategies for damage detection and classification are nowadays playing a key role in enhancing the operational reliability of critical structures in several industrial sectors. The main contribution of this paper is the application of a new methodology to detect and classify structural changes. The methodology is based on: 1) an artificial immune system (AIS) and the notion of affinity is used for the sake of damage detection; 2) a fuzzy c-means algorithm is used for damage classification. One of the advantages of the proposed methodology is the fact that to develop and validate the strategy, a model is not needed. Additionally, and in contrast to standard Lamb waves-based methods, there is no need to directly analyse the complex time-domain traces containing overlapping, multimodal and frequency dispersive wave propagation that distorts the signals and difficult the analysis. The proposed methodology is applied to data coming from two sections of an aircraft skin panel. The results indicate that the proposed methodology is able to accurately detect damage as well as classify those damages.
This paper deals with a characterization of nonlinear systems of the form x¿ (t) = f (x¿(t), u(t/¿)) when the parameter ¿ ¿ 8. In particular, we are interested in the uniform convergence of the sequence of functions x¿ (¿t). Necessary conditions and sufficient ones are derived for this uni- form convergence to happen.
Calm, R.; Masià, R.; Olivé, C.; Pares, N.; Pozo, F.; Ripoll, J.; Sancho-Vinuesa, T. Journal of technology and science education Vol. 7, num. 2, p. 221-230 DOI: 10.3926/jotse.253 Data de publicació: 2017 Article en revista
Calculus courses often present a large number of difficulties to undergraduate students of scientific studies, especially in engineering degrees. These difficulties are sometimes related to teaching and assessment strategies. In this paper, a teaching innovation experience is presented within the framework of the Universitat Oberta de Catalunya. This teaching experience is focused on a continuous assessment through a systematic use of the so-called WIRIS quizzes. Academic outcomes are very positive from both quantitative and qualitative viewpoints.
Villamizar, R.; Mujica, L.E.; Ruiz, M.; Camacho-Navarro, J.; Moreno, G. Journal of physics: conference series Vol. 842, num. 1, p. 1-9 DOI: 10.1088/1742-6596/842/1/012017 Data de publicació: 2017 Article en revista
In previous works, damage detection of metallic specimens exposed to temperature changes has been achieved by using a statistical baseline model based on Principal Component Analysis (PCA), piezodiagnostics principle and taking into account temperature effect by augmenting the baseline model or by using several baseline models according to the current temperature. In this paper a new approach is presented, where damage detection is based in a new index that combine Q and T2 statistical indices with current temperature measurements. Experimental tests were achieved in a carbon-steel pipe of 1m length and 1.5 inches diameter, instrumented with piezodevices acting as actuators or sensors. A PCA baseline model was obtained to a temperature of 21º and then T2 and Q statistical indices were obtained for a 24h temperature profile. Also, mass adding at different points of pipe between sensor and actuator was used as damage. By using the combined index the temperature contribution can be separated and a better differentiation of damages respect to undamaged cases can be graphically obtained.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Moreno, G.; Quiroga , J. Journal of physics: conference series Vol. 842, num. 1, p. 1-9 DOI: 10.1088/1742-6596/842/1/012018 Data de publicació: 2017 Article en revista
Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage
assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross -correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test
structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in
the structural response when damages occur. Two types of damage cases are studied: crack and
leak for each structure, respectively. Experimental results show that the methodology is
promising in the continuous monitoring of real structures.
Quiroga , J.; Mujica, L.E.; Villamizar, R.; Ruiz, M.; Camacho-Navarro, J. Journal of physics: conference series Vol. 842, num. 1, p. 1-10 DOI: 10.1088/1742-6596/842/1/012069 Data de publicació: 2017 Article en revista
This paper presents an approach to calculate dispersion curves for homogeneous and isotropic plates subject to stress, via Semi-Analytical Finite Element and the Effective Elastic Constants, since stresses in the waveguide modify the phase and group velocities of the lamb waves. In the proposed methodology an isotropic specimen subjected to anisotropic loading is
emulated by proposing an equivalent stress-free anisotropic specimen. This approximation
facilitates determining the dispersion curves by using the well-studied numerical solution for the
stress-free cases. The lamb wave in anisotropic materials can be studied by means of the Effective Elastic Constants, which reduces the complexity of the numerical implementation. Finally, numerical data available in literature were used to validate the proposed methodology, where it could be demonstrated its effectiveness as approximated method.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Moreno, G. Journal of physics: conference series Vol. 842, num. 1, p. 1-11 DOI: 10.1088/1742-6596/842/1/012019 Data de publicació: 2017 Article en revista
The algorithms commonly used for damage condition monitoring present several drawbacks related to
unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures . Data from an active system based on piezoelectric sensors are stored and characterized through the T2 and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.
An innovative Stewart platform (hexapod)-based testing rig is designed, constructed, and used herein to experimentally characterize a seismic isolation device named roll-in-cage (RNC) isolator. The testing rig is a result of integrating a mechanical extension, or upgrade, to the hexapod. This allows for performing up to 15 standard mechanical tests using cylinder, block, prism, beam, plate, or bar specimens, besides reduced-scale prototypes of seismic isolation bearings. Several one-tenth reduced-scale prototypes of the RNC isolator are experimentally examined in this paper using this testing rig. Cyclic horizontal displacement tests are performed considering different test parameters including shear displacement amplitude, axial load, and loading frequency. The RNC isolator's force-displacement relationships, shear stiffness, and damping properties are investigated. Vertical cyclic displacements are also applied to examine the RNC isolator's capability to withstand vertical axial tension. Furthermore, tests at the ultimate level consisting of an increasing-amplitude shear loading, beyond the bearing's design displacement limit, are also carried out to investigate the bearing's behavior after activating its inherent self-stopping, or buffer, mechanism. The obtained experimental outputs are then related to analytical and thorough FEM simulation outputs. This relation is intended to validate those previously developed mathematical and numerical models of the RNC isolator based on the real experimental measurements in this paper. A comparative study of the results is then performed, and the main observations are highlighted. Copyright (C) 2015 John Wiley & Sons, Ltd.
This work addresses the problem of online fault detection of an advanced wind turbine benchmark under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type. The fault detection scheme starts by computing the baseline principal component analysis (PCA) model from the healthy wind turbine. Subsequently, when the structure is inspected or supervised, new measurements are obtained and projected into the baseline PCA model. When both sets of data are compared, a statistical hypothesis testing is used to make a decision on whether or not the wind turbine presents some fault. The effectiveness of the proposed fault-detection scheme is illustrated by numerical simulations on a well-known large wind turbine in the presence of wind turbulence and realistic fault scenarios.
The paper presents results for the second moment stability of continuous-time Markov jump systems with quadratic terms, aiming for engineering applications. Quadratic terms stem from physical constraints in applications, as in electronic circuits based on resistor (R), inductor (L), and capacitor (C). In the paper, an RLC circuit supplied a load driven by jumps produced by a Markov chain—the RLC circuit used sensors that measured the quadratic of electrical currents and voltages. Our result was then used to design a stabilizing controller for the RLC circuit with measurements based on that quadratic terms. The experimental data confirm the usefulness of our approach.
This paper presents an application of Iterative Learning Control (ILC) theory to secure communication system design by using chaotic signals, where the logistic-map is employed as a source of chaos. Meanwhile, the ILC scheme is employed as a tool to encrypt and decrypt a message. A set of numerical experiments is realized to evidence the performance of our system, including the noisy case on the channels of communication of the proposed scheme.
We give an exhaustive characterization of singular weak solutions for some singular ordinary differential equations. Our motivation stems from the fact that in the context of hydrodynamics several prominent equations are reducible to an equation of this form upon passing to a moving frame. We construct peaked and cusped waves, fronts with finite-time decay and compact solitary waves. We prove that one cannot obtain peaked and compactly supported traveling waves for the same equation. In particular, a peaked traveling wave cannot have compact
support and vice versa. To exemplify the approach we apply our results to the Camassa-Holm equation and the equation for surface waves of moderate amplitude, and show how the different types of singular solutions
can be obtained varying the energy level of the corresponding planar Hamiltonian systems.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Pérez, O. Key engineering materials Vol. 713, p. 107-110 DOI: 10.4028/www.scientific.net/KEM.713.107 Data de publicació: 2016-09-30 Article en revista
Pipe leaks detection has a great economic, environmental and safety impact. Although several methods have been developed to solve the leak detection problem, some drawbacks such as continuous monitoring and robustness should be addressed yet. Thus, this paper presents the main results of using a leaks detection and classification methodology, which takes advantage of piezodiagnostics principle. It consists of: i) transmitting/sensing guided waves along the pipe surface by means of piezoelectric device ii) representing statistically the cross-correlated piezoelectric measurements by using Principal Component Analysis iii) identifying leaks by using error indexes computed from a statistical baseline model and iv) verifying the performance of the methodology by using a Self Organizing Map as visualization tool and considering different leak scenario. In this sense, the methodology was experimentally evaluated in a carbon-steel pipe loop under different leaks scenarios, with several sizes and locations. In addition, the sensitivity of the methodology to temperature, humidity and pressure variations was experimentally validated. Therefore, the effectiveness of the methodology to detect and classify pipe leaks, under varying environmental and operational conditions, was demonstrated. As a result, the combination of piezodiagnostics approach, cross-correlation analysis, principal component analysis, and Self Organizing Maps, become as promising solution in the field of structural health monitoring and specifically to achieve robust solution for pipe leak detection.
Quiroga , J.; Quiroga, J.; Mujica, L.E.; Villamizar, R.; Ruiz, M. Key engineering materials Vol. 713, p. 288-292 DOI: 10.4028/www.scientific.net/KEM.713.288 Data de publicació: 2016-09-30 Article en revista
In this paper, a guided wave temperature robust PCA-based stress monitoring
methodology is proposed. It is based on the analysis of the longitudinal guided wave propagating
along the path under stress. Slight changes in the wave are detected by means of PCA via statistical
T2 and Q indices. Experimental and numerical simulations of the guided wave propagating in
material under different temperatures have shown significant variations in the amplitude and the
velocity of the wave. This condition can jeopardize the discrimination of the different stress
scenarios detected by the PCA indices. Thus, it is proposed a methodology based on an extended
knowledge base, composed by a PCA statistical model for different discrete temperatures to
produce a robust classification of stress states under variable environmental conditions.
Experimental results have shown a good agreement between the predicted scenarios and the real
Quiroga, J.; Quiroga , J.; Mujica, L.E.; Villamizar, R.; Ruiz, M. Key engineering materials Vol. 713, p. 329-333 DOI: 10.4028/www.scientific.net/KEM.713.329 Data de publicació: 2016-09-30 Article en revista
In this investigation, a flow rate estimation guided wave based scheme in pipes is
proposed. The effect of the fluid over the propagation of longitudinal waves has been
experimentally studied by using several laminar flows of water transported by a steel pipe. Results
have shown a decrease of the guided wave pattern repeatability and the signal energy as the flow
rate increase as a result of the energy leakage from the pipe to the fluid. A Matlab® script is used to
excite the PZT actuator via picoscope 2208 of Picotech®, the captured signal is acquired also by the
picoscope and the data is processed in Matlab. The test bench utilized is composed by a 1” sch 40
A-106 pipe, a needle valve and a centrifugal pump provides the flow energy. A couple of PZTs are
used in a picth-catch configuration to produce and capture the longitudinal waves along the cross
section of the pipe.
The paper presents conditions to assure stochastic stability for a nonlinear model. The proposed model is used to represent the input-output dynamics of the angle of aperture of the throttle valve (input) and the manifold absolute pressure (output) in an automotive spark-ignition engine. The automotive model is second moment stable, as stated by the theoretical result—data collected from real-time experiments supports this finding.
Vargas, A.; Sampio, L.; Acho, L.; Zhang, L.; do Val, J. IEEE transactions on control systems technology Vol. 24, num. 5, p. 1820-1827 DOI: 10.1109/TCST.2015.2508959 Data de publicació: 2016-09-01 Article en revista
The note presents an algorithm for the average
cost control problem of continuous-time Markov jump linear
systems. The controller assumes a linear state-feedback form
and the corresponding control gain does not depend on the
Markov chain. In this scenario, the control problem is that of
minimizing the long-run average cost. As an attempt to solve the
problem, we derive a global convergent algorithm that generates
a gain satisfying necessary optimality conditions. Our algorithm
has practical implications, as illustrated by the experiments that
were carried out to control an electronic dc–dc buck converter.
The buck converter supplied a load that suffered abrupt changes
driven by a homogeneous Markov chain. Besides, the source of
the buck converter also suffered abrupt Markov-driven changes.
The experimental results support the usefulness of our algorithm.
We present three alternative methodologies to find continua of periodic points with a prescribed period for rational maps having rational first integrals. The first two have been already used by other authors and apply when the maps are birational and the generic level sets of the corresponding first integrals have either genus 0 or 1. As far as we know, the third one is new and it works for rational maps without imposing topological properties to the invariant level sets. It is based on a computational point of view, and relies on the use of resultants in a suitable setting. We apply them to several examples, including the 2-periodic Lyness composition maps and some of the celebrated McMillan–Gumovski–Mira maps
Aguilar, J.V.; Langarita, P.; Rodellar, J.; Linares, L.; Horväth, K. Water resources management Vol. 30, num. 11, p. 3829-3843 DOI: 10.1007/s11269-016-1387-6 Data de publicació: 2016-09-01 Article en revista
Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an irrigation canal located in Spain. First, a discrete time linear model of the process is described and its parameters are experimentally identified. The model is well validated within the usual canal operating range and is used to formulate a predictive control law with an incremental formulation. Finally, experimental and simulation results are presented in which predictive control has shown better performance than a well-tuned proportional, integral and derivative controller to automatically manage demanded water discharges.
Background: Automated peripheral blood
(PB) image analyzers usually underestimate
the total number of blast cells, mixing
them up with reactive or normal
lymphocytes. Therefore, they are not able
to discriminate between myeloid or lymphoid
blast cell lineages. The objective of
the proposed work is to achieve automatic
discrimination of reactive lymphoid cells
(RLC), lymphoid and myeloid blast cells
and to obtain their morphologic patterns
through feature analysis. Methods: In the
training stage, a set of 696 blood cell
images was selected in 32 patients (myeloid
acute leukemia, lymphoid precursor
neoplasms and viral or other infections).
For classification, we used support vector
machines, testing different combinations
of feature categories and feature selection
techniques. Further, a validation was
implemented using the selected features
over 220 images from 15 new patients
(five corresponding to each category).
Results: Best discrimination accuracy in
the training was obtained with feature
selection from the whole feature set
(90.1%). We selected 60 features, showing
significant differences (P < 0.001) in the
mean values of the different cell groups.
Nucleus-cytoplasm ratio was the most
important feature for the cell classification,
and color-texture features from the cytoplasm
were also important. In the validation
stage, the overall classification accuracy
and the true-positive rates for RLC, myeloid
and lymphoid blast cells were 80%,
85%, 82% and 74%, respectively. Conclusion:
The methodology appears to be able
to recognize reactive lymphocytes well,
especially between reactive lymphocytes
In this paper, we address the problem of real-time fault detection in wind turbines. Starting from a data-driven fault detection method, the contribution of this paper is twofold. First, a sensor selection algorithm is proposed with the goal to reduce the computational effort of the fault detection method. Second, an analysis is performed to reduce the data acquisition time needed by the fault detection method, that is, with the goal of reducing the fault detection time. The proposed methods are tested in a benchmark wind turbine where different actuator and sensor failures are simulated. The results demonstrate the performance and effectiveness of the proposed algorithms that dramatically reduce the number of sensors and the fault detection time.
Given the equation motion of a moving charged particle in a controlled electromagnetic field, this paper proves that its velocity-trajectory motion converges to an specified velocity-surface in the 3-D Euclidean dimensional space. This is basically realized by just manipulating the electric field of an electromagnetic field. Lyapunov theory is invoked to test our statement; besides, a numerical example is provided to support our theoretical contribution. Finally, we consider that the exposition of this paper could be of interest to undergraduate students.
This paper presents an application of unscented Kalman filters ( UKFs) to an automotive electronic throttle device. The motivation of this study is on estimating the position of the throttle device when measurements of the position are inaccessible, e. g., due to failures in the sensor of position. In this case, an external wattmeter is connected in the circuitry to measure the power consumed by the throttle, and this information feeds UKFs to produce the estimation for the position. Experimental data support the findings of this paper. Almost all of the brand-new vehicles based on spark-ignition combustion engines have an electronic throttle valve to control the power produced by the engine. The electronic throttle has a unique sensor for measuring the position of the throttle valve, and this feature can represent a serious problem when the sensor of position fails. As an attempt to prevent the effects of a failure from such a sensor, we present an algorithm ( UKF) combined with the use of an additional sensor, i. e., a wattmeter. The wattmeter is detached from the throttle's structure but is arranged to measure the electric power consumed by the throttle. Measurements of the power consumption then feed the UKF. This filter then produces an estimation of the position of the throttle valve. Experimental data illustrate the practical benefits of our approach.
The paper presents an application of unscented
Kalman filters to an automotive electronic throttle device. The
motivation of this study is on estimating the position of the
throttle device when measurements of position are inaccessible,
e.g., due to failures in the sensor of position. In this case, an
external wattmeter is connected in the circuitry to measure the
power consumed by the throttle, and this information feeds
unscented Kalman filters to produce the estimation for the
position. Experimental data support the findings of this paper.
The objective was to advance in the automatic, image-based, characterization and recognition of a heterogeneous set of lymphoid cells from peripheral blood, including normal, reactive, and five groups of abnormal lymphocytes: hairy cells, mantle cells, follicular lymphoma, chronic lymphocytic leukemia, and prolymphocytes. Methods: A number of 4389 images from 105 patients were selected by pathologists, based on morphologic visual appearance, from patients whose diagnosis was confirmed by all the remaining complementary tests. Besides geometry, new color and texture features were extracted using six alternative color spaces to obtain rich information to characterize the cell groups. The recognition system was designed using support vector machines trained with the whole image set. Results: In the experimental tests, individual sets of images from 21 new patients were analyzed by the trained recognition system and compared with the true diagnosis. An overall recognition accuracy of 97.67% was achieved when the cell screening was performed into three groups: normal lymphocytes, abnormal lymphoid cells, and reactive lymphocytes. The accuracy of the whole experimental study was 91.23% when considering the further discrimination of the abnormal lymphoid cells into the specific five groups. Conclusion: The excellent automatic screening of the three groups of normal, reactive, and abnormal lymphocytes is useful as it discriminates between malignancy and not malignancy. The discrimination of the five groups of abnormal lymphoid cells is encouraging toward the idea that the system could be an automated image-based screening method to identify blood involvement by a variety of B lymphomas.
Pujol-Vazquez, G.; Vidal, Y.; Acho, L.; Vargas, A. International journal of numerical modeling. Electronic networks devices and fields Vol. 29, num. 2, p. 192-204 DOI: 10.1002/jnm.2063 Data de publicació: 2016-03 Article en revista
This paper presents an improved model for an automotive electronic throttle inspired on the behavior observed in real-time experiments. Due to a number of issues, particularly the return-spring, the performance
of the throttle valve depends on whether it is opening or closing. This asymmetric behavior was taken into account to design a mathematical model of the throttle body and to derive a nonlinear asymmetric PI controller. The experimental demonstration suggests that considering an asymmetric term dramatically improves the performance of the controller
This is the peer reviewed version of the following article: Pujol, G., Vidal, Y., Acho, L. and Vargas, A. N. (2015), Asymmetric modelling and control of an electronic throttle. Int. J. Numer. Model, which has been published in final form at http://dx.doi.org/10.1002/jnm.2063. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
This paper presents an improved model for an automotive electronic throttle inspired on the behavior observed in real-time experiments. Due to a number of issues, particularly the return-spring, the performance of the throttle valve depends on whether it is opening or closing. This asymmetric behavior was taken into account to design a mathematical model of the throttle body and to derive a nonlinear asymmetric
PI controller. The experimental demonstration suggests that considering an asymmetric term dramatically improves the performance of the controller
Palacios-Quiñonero, F.; Rubió-Massegú, J.; Rossell, Josep M.; Karimi, H.R. IET control theory and applications Vol. 10, num. 4, p. 407-416 DOI: 10.1049/iet-cta.2015.0737 Data de publicació: 2016-02 Article en revista
The synthesis of optimal controllers for vibrational protection of large-scale structures with multiple actuation devices and partial state information is a challenging problem. In this study, the authors present a design strategy that allows computing this kind of controllers by using standard linear matrix inequality optimisation tools. To illustrate the main elements of the new approach, a five-story structure equipped with two interstory actuation devices and subjected to a seismic disturbance is considered. For this control setup, three different controllers are designed: an ideal state-feedback H 8 controller with full access to the complete state information and two static output-feedback H 8 controllers with restricted neighbouring state information. To assess the performance of the proposed controllers, the corresponding frequency responses are investigated and a proper set of numerical simulations are conducted, using the full scale North-South El Centro 1940 seismic record as ground acceleration input. The obtained results indicate that, despite the severe information constraints, the proposed static output-feedback controllers attain a level of seismic protection that is very similar to that achieved by the ideal state-feedback controller with complete state information.
This article introduces a new methodology for the detection of structural changes using a statistical data-driven modeling approach by means of a distributed piezoelectric active sensor network at different actuation phases. The three main features that characterize the proposed methodology are (a) the nature of the data used in the test since vectors of principal component analysis projections are used instead of the entire measured response of the structure or the coefficients of an AutoRegressive model, (b) the number of data used since the test is based on two random samples instead of some characteristic indicators, and (c) the samples come from a multidimensional variable and therefore a test for the plausibility of a value for a normal population mean vector is performed. The framework of multivariate statistical inference is used with the objective of the classification of structures in healthy or damaged. The novel scheme for damage detection presented in this article —based on multivariate inference over the principal component analysis projections of the raw data—is applied, validated, and tested on a small aluminum plate. The results show that the presented methodology is able to accurately detect damages, that is, for each actuation phase, a unique and reliable damage detection indicator is obtained no matter the number of sensors and/or actuators. It is worth noting that a major contribution of this article is that there exists an entire range of significance levels where the multivariate statistical inference is able to offer a correct decision although all of the univariate tests make a wrong decision.
Tibaduiza, D.A.; Mujica, L.E.; Rodellar, J.; Güemes Gordo, Jesús Alfredo Journal of intelligent material systems and structures Vol. 27, num. 2, p. 233-248 DOI: 10.1177/1045389X14566520 Data de publicació: 2016-01-01 Article en revista
One of the most important tasks in structural health monitoring corresponds to damage detection. In this task, the existence of damage should be determined. In the literature, several potentially useful techniques for damage detection can be found, and their applicability to a particular situation depends on the size of the critical damages that are admissible in the structure. Almost all of these techniques follow the same general procedure: the structure is excited using actuators, and the dynamical response is sensed at different locations throughout the structure. Any damage will change this vibrational response. The state of the structure is diagnosed by means of the processing of these data. Several studies have shown that the detection of changes in a structure depends on the distance from the damage to the actuator as well as the configuration of the sensor network. In this article, the authors considered the advantage of using an active piezoelectric system, where the lead zirconate titanate transducers are used as actuator and sensors in different actuation phases. In each actuation phase of the diagnosis procedure, one lead zirconate titanate transducer is used as actuator (a known electrical signal is applied), and the others are used as sensors (collecting the wave propagated through the structure at different points). An initial baseline model for undamaged structure is built applying principal component analysis to the data collected by several experiments and after the current structure (damaged or not) is subjected to the same experiments, and the collected data are projected into the principal component analysis models. Two of these projections and four damage indices (T-2-statistic, Q-statistic, combined index, and I-2 index) by each actuation phase are used to determine the presence of damages and to distinguish between them. These indices are calculated based on the analysis of the residual data matrix to represent the variability of the data projected within the residual subspace and the new space of the principal components. To validate the approach, data from two aeronautical structuresan aircraft skin panel and an aircraft turbine blade-are used.
One of the most important tasks in structural health monitoring corresponds to damage detection. In this task, the existence
of damage should be determined. In the literature, several potentially useful techniques for damage detection can
be found, and their applicability to a particular situation depends on the size of the critical damages that are admissible in
the structure. Almost all of these techniques follow the same general procedure: the structure is excited using actuators,
and the dynamical response is sensed at different locations throughout the structure. Any damage will change this vibrational
response. The state of the structure is diagnosed by means of the processing of these data. Several studies have
shown that the detection of changes in a structure depends on the distance from the damage to the actuator as well as
the configuration of the sensor network. In this article, the authors considered the advantage of using an active piezoelectric
system, where the lead zirconate titanate transducers are used as actuator and sensors in different actuation
phases. In each actuation phase of the diagnosis procedure, one lead zirconate titanate transducer is used as actuator (a
known electrical signal is applied), and the others are used as sensors (collecting the wave propagated through the structure
at different points). An initial baseline model for undamaged structure is built applying principal component analysis
to the data collected by several experiments and after the current structure (damaged or not) is subjected to the same
experiments, and the collected data are projected into the principal component analysis models. Two of these projections
and four damage indices (T2-statistic, Q-statistic, combined index, and I2 index) by each actuation phase are used to
determine the presence of damages and to distinguish between them. These indices are calculated based on the analysis
of the residual data matrix to represent the variability of the data projected within the residual subspace and the new
space of the principal components. To validate the approach, data from two aeronautical structures—an aircraft skin
panel and an aircraft turbine blade—are used.
Wind turbines (WTs) are basically controlled by varying the generator load torque (with the so-called torque control) and the blade pitch angles (with the so-called pitch control) based on measurement of the generator shaft speed. These two controllers unitedly work to satisfy the control objectives, and it is crucial that they are tolerant to possible faults in the WT system. Passive fault-tolerant control comprises the design of robust controllers against disturbances and uncertainties. This enables the controller to counteract the effect of a fault without requiring reconfiguration or fault detection. In this regard, the main contribution of this paper is to propose new control techniques that not only provide fault tolerance capabilities to the WT system but also improve the overall performance of the system in both fault-free and faulty conditions. Coupling nonlinear aero-hydro-servo-elastic simulations of an offshore WT with jacket platform is carried out for several pitch actuator faults. The jacket platform motions and structural loads caused by fault events with the proposed controllers are compared with loads encountered during normal operation and with respect to a well-known baseline controller in the literature. The proposed controllers are based in the super-twisting algorithm by using feedback of the generator shaft speed as well as the fore-aft and side-to-side acceleration signals of the WT tower.
This paper addresses the problem of online fault detection of an advanced wind turbine benchmark under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type: fixed value, gain factor, offset and changed dynamics. The fault detection scheme starts by computing the baseline principal component analysis (PCA) model from the healthy or undamaged wind turbine. Subsequently, when the structure is inspected or supervised, new measurements are obtained are projected into the baseline PCA model. When both sets of data—the baseline and the data from the current wind turbine—are compared, a statistical hypothesis testing is used to make a decision on whether or not the wind turbine presents some damage, fault or misbehavior. The effectiveness of the proposed fault-detection scheme is illustrated by numerical simulations on a well-known large offshore wind turbine in the presence of wind turbulence and realistic fault scenarios. The obtained results demonstrate that the proposed strategy provides and early fault identification, thereby giving the operators sufficient time to make more informed decisions regarding the maintenance of their machines.
Seismic isolation systems are essentially designed to preserve structural safety, prevent occupants injury and properties damage. An active saturated LMI-based control design is proposed to attenuate seismic disturbances in base-isolated structures under saturation actuators. Using a mathematical model of an eight-storied building structure, an active control algorithm is designed. Performance evaluation of the controller is carried out in a simplified model version of a benchmark building system, which is recognized as a state-of-the-art model for numerical experiments of structures under seismic perturbations. Experimental results show that the proposed algorithm is robust with respect to model and seismic perturbations. Finally, the performance indices show that the proposed controller behaves satisfactorily and with a reasonable control effort.
Tibaduiza, D.A.; Anaya, M.; Forero, E.; Castro, R.; Pozo, F. IOP Conference Series: Materials Science and Engineering Vol. 138, p. 1-8 DOI: 10.1088/1757-899X/138/1/012016 Data de publicació: 2016 Article en revista
This paper introduces a recent seismic isolation system, named Roll-in-Cage (RNC) isolator, for efficient protection of bridges against destructive earthquakes. The RNC isolator is a rolling-based isolation system with several integrated features in a single unit providing all the necessary functions of vertical rigid support, horizontal flexibility, full stability, hysteretic energy dissipation, and resistance to minor vibration loads. Besides, it is distinguished by a self-stopping (buffer) mechanism to limit the peak bearing displacement under abrupt severe excitations, a linear gravity-based self-recentering mechanism to prevent permanent dislocations after excitations, and a notable resistance to axial tension. A three-span box-girder prestressed concrete bridge is investigated under a set of different destructive real and synthetic earthquakes including near-fault, long-period, and pulse-like ground motions. As a performance measure, the responses of isolated and nonisolated cases are compared. In addition, the RNC isolator's behavior is then compared with those of other isolation systems including HDB, FPS, and LRB. The results confirmed that the RNC isolator has a superior behavior in achieving a balance between the peak displacements and accelerations of the isolated deck, relative other isolation systems, besides being the most (relatively) efficient isolator in the great majority of studies performed.
The Bouc–Wen hysteresis model is widely employed to mathematically represent the dynamical behavior of several physical devices, materials and systems such as magnetorheological dampers, lanthanide zirconium or aluminum oxides, mechanical structures or biomedical systems. However, these mathematical models must account for different properties such as the bounded-input bounded-output stability, asymptotic motion, thermodynamic admissibility or passivity in order to be physically consistent with the systems they represent. The passivity of a system is related to energy dissipation. More precisely, a system is passive if it does not generate energy but only dissipates it. The objective of this paper is to prove that two different double-loop Bouc–Wen models are passive under a particular set of model parameters.
We prove that any planar birational integrable map, which preserves a fibration given by genus 0 curves has a Lie symmetry and some associated invariant measures. The obtained results allow to study in a systematic way the global dynamics of these maps. Using this approach, the dynamics of several maps is described. In particular we are able to give, for particular examples, the explicit expression of the rotation number function, and the set of periods
of the considered maps.
We consider the problem of characterizing, for certain natural
number m, the local C^m-non-integrability near
elliptic fixed points of smooth planar measure preserving maps. Our
criterion relates this non-integrability with the existence of some
Lie Symmetries associated to the maps, together with the study of
the finiteness of its periodic points. One of the steps in the proof
uses the regularity of the period function on the whole period
annulus for non-degenerate centers, question that we believe that is
interesting by itself. The obtained criterion can be applied to
prove the local non-integrability of the Cohen map and of several
rational maps coming from second order difference equations.
This paper aims at forcing the isolated asymmetric structures to behave as symmetric structures with, theoretically, no absolute torsional responses. In addition, it attempts to provide efficient protection to such structures against severe near-fault ground motions considering limited seismic gaps with no seismic pounding. To achieve these goals, the recently proposed multi-feature roll-in-cage (RNC) isolator is used. An improved full-feature sap2000 model (Computers and Structures, Inc., Walnut Creek, CA, USA) is first developed for the RNC isolator then validated using analytical and experimental results. Next, an RNC isolation method that could eliminate the eccentricities between both structural centers of mass and rigidity is employed to theoretically remove structural torsion. It is based on using different isolator sets with unequal elastic stiffness to allow for shifting the center of rigidity at the isolation level, having dominant lateral behavior in case of isolated structures, to coincide with the structural center of mass above that level. After that, the ability of the RNC isolator to provide efficient seismic isolation considering relatively limited seismic gaps is investigated under unidirectional and bidirectional near-fault earthquakes. This could be attained through the independent source of high hysteretic damping and pre-yield elastic stiffness of the RNC isolator, in addition to its integrated self-stopping or buffer mechanism. The obtained results demonstrate the capability of the RNC isolator to, theoretically, eliminate torsional responses of isolated asymmetric structures besides providing relatively efficient seismic isolation, with no seismic pounding, considering insufficient or limited seismic gaps under severe near-fault unidirectional and simultaneous bidirectional ground motions.