A model reference adaptive fuzzy control for MIMO Takagi-Sugeno fuzzy model

Nonlinear model reference adaptive control using Takagi-Sugeno fuzzy systems

This paper develops a new direct model reference fuzzy adaptive control of SISO continuous-time nonlinear systems. The model following conditions are assured by using an adaptive Takagi-Sugeno (TS) fuzzy system as nonlinear state feedback controller. Both full state information and observer-based control schemes are investigated. It is shown, that the proposed control algorithm guarantees the s...

Stable Indirect Adaptive Fuzzy Control Based on Takagi-sugeno Model

This paper presents an indirect adaptive fuzzy control scheme for nonlinear uncertain stable plants with unmeasurable states. A discrete-time T-S fuzzy model is employed as a dynamic model of an unknown plant. Based on this model, a feedback linearization controller is designed and applied to both the model and the plant. Parameters of the model are updated on-line to allow for partially unknow...

LMI-based tracking control for Takagi-Sugeno fuzzy model

This paper deals with the problem of tracking control for Takagi-Sugeno fuzzy model. An LMI (Linear Matrix Inequality) formulation is suggested to make possible the convergence of the state vector of the continuous-time system to a desired one using a new approach, called MultiQuadratic Fuzzy Lyapunov (MQFL). A fourth order unstable nonlinear system is studied to illustrate the efficiency of th...

Fuzzy model-based predictive control using Takagi-Sugeno models

Nonlinear model-based predictive control (MBPC) in multi-input multi-output (MIMO) process control is attractive for industry. However, two main problems need to be considered: (i) obtaining a good nonlinear model of the process, and (ii) applying the model for control purposes. In this paper, recent work focusing on the use of Takagi±Sugeno fuzzy models in combination with MBPC is described. F...

Takagi-Sugeno Fuzzy Modeling for Process Control