Adaptive neural internal model control for complex process with delay

This paper adopts the adaptive neural internal model control strategy to design a control system for complex and uncertain process with delay. Because of the shortage of the classic internal model control system the performance of the control system will slip back if there exist large errors between the real plant and the model, an adaptive mechanism based on single neuron which can tune the parameters of the internal model and that of controller in the control system on line is designed. The multimodel approach is exploited to represent the direct model by a model basis made up of five linear models, and to construct a controller trained by the corresponding reverse models. The simulation results shows that the adaptive internal model control system designed in this paper has good performance of overcoming deviations of model parameters.

[1]  Han-Xiong Li,et al.  An approximate internal model-based neural control for unknown nonlinear discrete processes , 2006, IEEE Transactions on Neural Networks.

[2]  Moonyong Lee,et al.  Robust PID tuning for Smith predictor in the presence of model uncertainty , 1999 .

[3]  Léon Personnaz,et al.  Nonlinear internal model control using neural networks: application to processes with delay and design issues , 2000, IEEE Trans. Neural Networks Learn. Syst..

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

[5]  V. Kharitonov.  Asympotic stability of an equilibrium position of a family of systems of linear differntial equations , 1978 .

[6]  M. Benrejeb,et al.  Multimodel multicontrol decision making in system automation , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[7]  S. Niculescu.  Delay Effects on Stability: A Robust Control Approach , 2001 .

[8]  G. Zames.  On the input-output stability of time-varying nonlinear feedback systems--Part II: Conditions involving circles in the frequency plane and sector nonlinearities , 1966 .

[9]  G. P. Rangaiah,et al.  Internal model control with feedback compensation for uncertain non-linear systems , 2001 .

[10]  Darci Odloak,et al.  LMI-Based Multi-model Predictive Control of an Industrial C3/C4 Splitter , 2003, Journal of Control, Automation and Electrical Systems.

[11]  Aniruddha Datta,et al.  Adaptive internal model control: Design and stability analysis , 1996, Autom..

[12]  G. Zames.  On the input-output stability of time-varying nonlinear feedback systems Part one: Conditions derived using concepts of loop gain, conicity, and positivity , 1966 .

[13]  Doug Cooper,et al.  A practical multiple model adaptive strategy for single-loop MPC , 2003 .

[14]  Riccardo Scattolini,et al.  Easy tuning of smith predictor in presence of delay uncertainty , 1993, Autom..

[15]  Jean Jacques Loiseau,et al.  Applications of Time Delay Systems , 1984 .

[16]  Min-Sen Chiu,et al.  A multiple-model approach to decentralized internal model control design , 2001 .