This paper addresses the problem of fault detection and isolation of wind turbines using a mixed Bayesian/Set-membership approach. Modeling errors are assumed to be unknown but bounded, following the set-membership approach. On the other hand, measurement noise is also assumed to be bounded, but following a statistical distribution inside the bounds. To avoid false alarms, the fault detection problem is formulated in a set-membership context. Regarding fault isolation, a new fault isolation scheme that is inspired on the Bayesian fault isolation framework is developed. Faults are isolated by matching the fault detection test results, enhanced by a complementary consistency index that measures the certainty of not being in a fault situation, with the structural information about the faults stored in the theoretical fault signature matrix. The main difference with respect to the classical Bayesian approach is that only models of fault-free behavior are used. Finally, the proposed FDI method is assessed against the wind turbine FDI benchmark proposed in the literature, where a set of realistic fault scenarios in wind turbines are proposed.
This paper presents a fault tolerant control (FTC) strategy for unstable linear systems subject to actuator saturation and fault isolation delay. The solution relies on virtual actuators, an active fault-hiding method that reconfigures the faulty plant instead of the controller. The main contribution of the paper consists in the design of the virtual actuators with guarantees that, if at the fault isolation time the closed-loop system state is inside a region defined by a value of the Lyapunov function, the state trajectory will converge to zero despite the appearance of faults within a predefined set. In addition, the design of the nominal controller is performed so as to maximize the tolerated delay between the fault occurence and its isolation. Finally, the theoretical results are demonstrated and illustrated using an example.
Sànchez-Marrè, M.; Rodríguez-Roda, I.; Poch, M.; Cortes, U.; Lafuente Sancho, Francisco Javier Annual reviews in control Vol. 19, p. 147-152 DOI: 10.1016/0066-4138(94)90057-4 Data de publicació: 1994-12-01 Article en revista
One of the key problems in real-time control Artificial Intelligent systems design is the development of an architecture able to manage efficiently the different elements of the process. In the management of Waste Water Treatment Plants (WWTP), with a great interrelation between the different units, there is a problem in order to identify and solve the different specific situations. A Supervisory System recognizes predefined problems and uses a determined strategy in order to keep the process controlled. The main goal of the paper is to present a knowledge-based distributed architecture for real time supervision and control of WWTP that overcomes some of these troubles. It is discussed the development of the application and the methodology employed in it. The prototype's architecture being developed DAI-DEPUR is detailed together with some obtained results.