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Journal ArticleDOI

An approach to fuzzy control of nonlinear systems: stability and design issues

TLDR
The authors represent a nonlinear plant with a Takagi-Sugeno fuzzy model with a model-based fuzzy controller design utilizing the concept of the so-called "parallel distributed compensation" and presents a design methodology for stabilization of a class of nonlinear systems.
Abstract
Presents a design methodology for stabilization of a class of nonlinear systems. First, the authors represent a nonlinear plant with a Takagi-Sugeno fuzzy model. Then a model-based fuzzy controller design utilizing the concept of the so-called "parallel distributed compensation" is employed. The main idea of the controller design is to derive each control rule so as to compensate each rule of a fuzzy system. The design procedure is conceptually simple and natural. Moreover, the stability analysis and control design problems can be reduced to linear matrix inequality (LMI) problems. Therefore, they can be solved efficiently in practice by convex programming techniques for LMIs. The design methodology is illustrated by application to the problem of balancing and swing-up of an inverted pendulum on a cart.

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Book

Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach

Kazuo Tanaka, +1 more
TL;DR: Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.
Journal ArticleDOI

Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs

TL;DR: New relaxed stability conditions and LMI- (linear matrix inequality) based designs for both continuous and discrete fuzzy control systems are applied to design problems of fuzzy regulators and fuzzy observers.
Journal ArticleDOI

A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Journal ArticleDOI

Least-squares policy iteration

TL;DR: The new algorithm, least-squares policy iteration (LSPI), learns the state-action value function which allows for action selection without a model and for incremental policy improvement within a policy-iteration framework.
Journal ArticleDOI

Comments on "Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H/sup /spl infin// control theory, and linear matrix inequalities"

TL;DR: New stability conditions for a generalized class of uncertain systems are derived from robust control techniques such as quadratic stabilization, H/sup /spl infin// control theory, and linear matrix inequalities.
References
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Journal ArticleDOI

Fuzzy identification of systems and its applications to modeling and control

TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Journal ArticleDOI

Stability analysis and design of fuzzy control systems

TL;DR: The fuzzy block diagrams and the stability analysis are applied to the design problems of a model-based fuzzy controller and a new design technique of a fuzzy controller is proposed.
Journal ArticleDOI

A robust stabilization problem of fuzzy control systems and its application to backing up control of a truck-trailer

TL;DR: A fuzzy controller is designed which guarantees stability of the control system under a condition and the simulation results show that the designed fuzzy controller smoothly achieves backing up control of the truck-trailer from all initial positions.
Proceedings ArticleDOI

Parallel distributed compensation of nonlinear systems by Takagi-Sugeno fuzzy model

TL;DR: A model-based fuzzy controller design utilizing the concept of so-called "parallel distributed compensation" is employed and the method is illustrated by application to the problem of balancing an inverted pendulum on a cart.
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