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Multivariable Systems (multivariable + system)
Selected AbstractsExplicit constructions of global stabilization and nonlinear H, control laws for a class of nonminimum phase nonlinear multivariable systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 12 2008Weiyao Lan Abstract This paper investigates a global stabilization problem and a nonlinear H, control problem for a class of nonminimum phase nonlinear multivariable systems. To avoid the complicated recursive design procedure, an asymptotic time-scale and eigenstructure assignment method is adopted to construct the control laws for the stabilization problem and the nonlinear H, control problem. A sufficient solvability condition is established onthe unstable zero dynamics of the system for global stabilization problem and nonlinear H, control problem, respectively. Moreover, based on the sufficient solvability condition, an upper bound of the achievable L2 -gain is estimated for the nonlinear H, control problem. Copyright © 2007 John Wiley & Sons, Ltd. [source] Perturbation signal design for neural network based identification of multivariable nonlinear systemsTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 1 2002Pankaj S. Kulkarni Abstract The paper focuses on issues in experimental design for identification of nonlinear multivariable systems. Perturbation signal design is analyzed for a hybrid model structure consisting of linear and neural network structures. Input signals, designed to minimize the effects of nonlinearities during the linear model identification for the multivariable case, have been proposed and its properties have been theoretically established. The superiority of the proposed perturbation signal and the hybrid model has been demonstrated through extensive cross validations. The utility of the obtained models for control has also been proved through a case study involving MPC of a nonlinear multivariable neutralization plant. On traite dans cet article de la problématique des plans expérimentaux pour la détermination des systèmes multivariés non linéaires. La conception des signaux de perturbation est analysée pour un modèle de structure hybride composée de structures à réseaux linéaires et neuronaux. Des signaux d'entrée, con,us pour minimiser les effets des non-linéarités lors de la détermination du modèle linéaire pour le cas multivarié, sont proposés et leurs propriétés sont établies de manière théorique. La supériorité du signal de perturbation et du modèle hybride proposés est démontrée par des validations croisées poussées. L'utilité des modèles obtenus pour le contr,le est également prouvée par une étude de cas faisant intervenir le MPC d'une installation de neutralisation multivariée non linéaires. [source] A Design Of Multiloop Predictive Self-Tuning Pid ControllersASIAN JOURNAL OF CONTROL, Issue 4 2002Masaru Katayama ABSTRACT In this paper, a new design scheme of multiloop predictive self-tuning PID controllers is proposed for multivariable systems. The proposed scheme firstly uses a static pre-compensator as an approximately decoupling device, in order to roughly reduced the interaction terms of the controlled object. The static matrix pre-compensator is adjusted by an on-line estimator. Furthermore, by regarding the approximately decoupled system as a series of single-input single-output subsystems, a single-input single-output PID controller is designed for each subsystem. The PID parameters are calculated on-line based on the relationship between the PID control and the generalized predictive control laws. The proposed scheme is numerically evaluated on a simulation example. [source] | ||||||||||