Decentralized Networked Control System Design Using Takagi-Sugeno (TS) Fuzzy Approach

This paper proposes a new method for control of continuous large-scale systems where the measures and control functions are distributed on calculating members which can be shared with other applications and connected to digital network communications.At first, the nonlinear large-scale system is described by a Takagi-Sugeno(TS) fuzzy model. After that, by using a fuzzy LyapunovKrasovskii functional, sufficient conditions of asymptotic stability of the behavior of the decentralized networked control system(DNCS),are developed in terms of linear matrix inequalities(LMIs). Finally, to illustrate the proposed approach, a numerical example and simulation results are presented.     

State feedback control of continuous-time T-S fuzzy systems via switched fuzzy controllers

This paper studies the problem of state feedback control of continuous-time T-S fuzzy systems. Switched fuzzy controllers are exploited in the control design, which are switched based on the values of membership functions, and the control scheme is an extension of the parallel distributed compensation (PDC) scheme. Sufficient conditions for designing switched state feedback controllers are obtained with meeting an H_∞ norm bound requirement and quadratic D stability constraints. It is shown that the new control design method provides less conservative results than the corresponding ones via the parallel distributed compensation (PDC) scheme. A numerical example is given to illustrate the effectiveness of the proposed method.     

具有时变输入时滞的不确定T-S模糊系统的鲁棒稳定性

本文主要针对不确定的输入变时滞 T-S 模糊系统设计模糊控制器使系统鲁棒稳定. 首先基于 Lyapunov-Krasovskii 泛函方法, 通过引入更多的松弛变量矩阵, 以 LMI 形式给出使此模糊系统稳定的充分条件. 在设计模糊控制器时并不要求满足时变输入时滞的导数小于1的限制条件. 最后给出数值仿真例证本文提出的结果的有效性且保守性更小.     

Controller design for electric power steering system using T-S fuzzy model approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.     

A systematic approach to improve multiple Lyapunov function stability and stabilization conditions for fuzzy systems

This paper presents a systematic approach for decreasing conservativeness in stability analysis and control design for Takagi-Sugeno (TS) systems. This approach is based on the idea of multiple Lyapunov functions together with simple techniques for introducing slack matrices. Unlike some previous approaches based on multiple Lyapunov functions, both the stability and the stabilization conditions are written as linear matrix inequality (LMI) problems. The proposed approach reduces the number of inequalities and guarantees extra degrees of freedom to the LMI problems. Numeric examples illustrate the effectiveness of this method.     

基于T-S模糊神经网络的齿槽效应补偿方法研究*

针对齿槽效应带来的齿槽误差问题,提出在传感器探头内布设齿槽位置检测线圈,建立传感器齿槽特性模型和基于T-S模糊神经网络的齿槽补偿系统模型,依据齿槽位置信号对传感器进行齿槽误差补偿。利用附加动量的BP学习方法对网络进行学习和测试。仿真结果表明补偿模型的输出不再随齿槽位置波动,最大误差为依0.2mm,该种方法可以有效地消除齿槽效应并提高传感器的检测精度,满足高速磁浮车悬浮控制系统要求。     

A survey on industrial applications of fuzzy control

Fuzzy control has long been applied to industry with several important theoretical results and successful results. Originally introduced as model-free control design approach, model-based fuzzy control has gained widespread significance in the past decade. This paper presents a survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000.