Representation and control of time delay system: Multimodel approach

The multimodel approach is recently developed in order to resolve complexity of many industrial processes. Nevertheless, this approach is often confronted to several difficulties, such as, the determination of the useful models' base. A new approach for determination of a models' base for the representation of non stationary time delay systems is presented in this paper. This mul-timodel representation is validated by a generalized minimum variance multimodel control scheme.

[1]  H. Kurz,et al.  Digital parameter-adaptive control of processes with unknown dead time , 1981, Autom..

[2]  Tao Zhang,et al.  An adaptive generalized predictive control of time-varying delay system , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[3]  E. Boukas.  Discrete-time systems with time-varying time delay: Stability and stabilizability , 2006 .

[4]  Ahmad B. Rad,et al.  Simultaneous online identification of rational dynamics and time delay: a correlation-based approach , 2003, IEEE Trans. Control. Syst. Technol..

[5]  P. Gawthrop,et al.  Identification of time delays using a polynomial identification method , 1985 .

[6]  Wei Xing Zheng,et al.  Identification problems in distributed parameter neuron models , 1990 .

[7]  Wei Xing Zheng,et al.  Identification of stochastic time lag systems in the presence of colored noise , 1990, Autom..

[8]  Tao Zhang,et al.  A Bilateral Control of Teleoperators Based on Time Delay Identification , 2008, 2008 IEEE Conference on Robotics, Automation and Mechatronics.

[9]  Sreten B. Stojanovic,et al.  A Lyapunov-Krasovskii methodology for asymptotic stability of discrete time delay systems , 2007 .

[10]  G. Carter,et al.  The generalized correlation method for estimation of time delay , 1976 .

[11]  Jean-Pierre Richard,et al.  Time-delay systems: an overview of some recent advances and open problems , 2003, Autom..

[12]  G. Dumont,et al.  New method for delay estimation , 1990, 29th IEEE Conference on Decision and Control.

[13]  Stephen L. Chiu,et al.  Fuzzy Model Identification Based on Cluster Estimation , 1994, J. Intell. Fuzzy Syst..