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Multirate Input Control for Fuzzy Systems Based on Disk-Pole Placement | IEEE Conference Publication | IEEE Xplore

Multirate Input Control for Fuzzy Systems Based on Disk-Pole Placement


Abstract:

A new multirate fuzzy control technique for continuous-time nonlinear systems is presented in this paper. First, the lifted Takagi-Sugeno(T-S) fuzzy model of the plant is...Show More

Abstract:

A new multirate fuzzy control technique for continuous-time nonlinear systems is presented in this paper. First, the lifted Takagi-Sugeno(T-S) fuzzy model of the plant is constructed subject to linear matrix inequalities (LMIs). Then, a multirate input controller for the multiple T-S linear models, based on the design of the local feedback controllers using optimal diskpole (D-pole) placement, is proposed. A sufficient condition for the existence of such a controller is expressed in terms of algebraic Riccati equation. Finally, the stability of the closed-loop control system is derived in the sense of Lyapunov. Simulation results show the effectiveness of the proposed method.
Date of Conference: 18-20 June 2008
Date Added to IEEE Xplore: 22 August 2008
CD:978-0-7695-3161-8
Conference Location: Dalian, China

1. Introduction

Nowadays, practical and modern control systems usually use digital computers as discrete-time controllers to control continuous-time systems. Such a control system involves both continuous-time and discrete-time signals and is called a sampled-data system [1]. Recently, some researches have been reported on digital control for nonlinear systems based on T-S fuzzy model [2], [3]. In [4], a digital controller stabilizing the discretized model of T-S fuzzy systems was proposed. But their results are only approximate formulations since the sampling of continuous time signals implies loss of some information. One can get better discretized models if one can make A/D and D/A conversions faster. However, this results in higher cost in implementation. An alternative approach is multirate input control scheme which updates the control inputs faster than the output measurements. In the past decades, there have been fruitful researches on multirate systems [5]–[7]. But their results basically work only for a class of linear systems. Thus, it is highly demanded to develop multirate control for nonlinear systems. So far, few efforts have been concentrated on utilizing multirate control technique in fuzzy systems except for [8], [9].

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References

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