Hernandez, C.; Muñoz, J.; Esparza, O.; Mata, J.; Alins, J. International journal of innovative computing information and control Vol. 8, num. 11, p. 7925-7942 Data de publicació: 2012-11-01 Article en revista
Costa-Castelló, R.; Olm, Josep M.; Vargas, H.; Ramos, G. A. International journal of innovative computing information and control Vol. 8, num. 8, p. 5591-5606 Data de publicació: 2012-08 Article en revista
This article presents an educational approach to resonant control and repet-
itive control, which are Internal Model Principle-based control techniques speci cally de-
signed for the tracking/rejection of periodic signals. The analytical formulation is com-
pleted by a set of simulations and physical experiments on a mechatronic educational
plant integrated in a virtual/remote laboratory. The laboratory features are oriented to
realize the limited performance of classic PID control to reject non-constant disturbances
and, at the same time, to show the effectiveness of the Internal Model Principle for the
rejection of periodic disturbances by means of resonators and repetitive control. Assess-
ment based on students' perception reveals it as a useful distance learning tool. The
laboratory is integrated in Automatl@bs, a Spanish interuniversity network of web-based
laboratories devoted to distance learning of control engineering.
In this paper, we contribute to the further development of delay-range-dependent state-feedback aspect of robust control for vibration reduction in a building structure with limited wireless communication capacity subjected to measurement quantization, signal transmission delay and data packet dropout, which appear typically in a network environment. The feedback loop is subjected to a time-varying bounded delay within the sensors and the structure. By using an appropriate Lyapunov-Krasovskii functional and some free weighting matrices, new sufficient conditions in terms of some
linear matrix inequalities are established for the existence of desired controllers such that the resulting closed-loop system is asymptotically stable and kept within a prescribed level of H1 performance bound. Finally, simulation results are given to illustrate the usefulness of the proposed control methodology.
A new adaptive nonlinear state predictor (ANSP) is presented for a class of
unknown nonlinear systems with input time-delay. A dynamical identification with neu-
ral network (NN) is constructed to obtain NN weights and their derivatives. The future
NN weights are deduced for the nonlinear state predictor design without iterative calcu-
lations. The time-delay and unknown nonlinearity are compensated by a feedback control
using the predicted states. Rigorous stability analysis for the identification, predictor and
feedback control are provided by means of Lyapunov criterion. Simulations and practical
experiments of a temperature control system are included to verify the effectiveness of
the proposed scheme.