Seog-Hwan Yoo

A balanced model reduction for t-s fuzzy systems with uncertain time varying parameters

This paper deals with a balanced model reduction for a class of Takagi-Sugeno(T-S) fuzzy systems with uncertain time varying parameters. We define a generalized controllability Gramian and a generalized observability Gramian for quadratically stable T-S fuzzy systems with uncertainties. We introduce a balanced state space realization using the generalized controllability and observability Gramians and obtain a reduced model by truncating not only states but also time varying uncertain parameters from the balanced state space realization. We also present an upper bound of the approximation error. The generalized controllability and observability Gramians can be computed from solutions of linear matrix inequalities(LMIs).

A balanced model reduction for t-s fuzzy systems with integral quadratic constraints

This paper deals with a balanced model reduction for a class of nonlinear systems with integral quadratic constraints(IQCs) using a T-S(Takagi-Sugeno) fuzzy approach. We define a generalized controllability Gramian and a generalized observability Gramian for a stable T-S fuzzy systems with IQCs. We obtain a balanced state space realization using the generalized controllability and observability Gramians and obtain a reduced model by truncating not only states but also IQCs from the balanced state space realization. We also present an upper bound of the approximation error. The generalized controllability Gramian and observability Gramian can be computed from solutions of linear matrix inequalities.

Design of Control System for Hydraulic Cylinders of a Sluice Gate Using Fuzzy PI Algorithm

A main technology of opening and closing a sluice gate is accurate synchronous and position control for the two cylinders when they are moving with the sluice gate together over 10[m]. Since the supply flow and supply pressure of cylinders are not constant and a nonlinear friction force of the piston in cylinders exists, a difference will be made between the displacement of two cylinders. This difference causes the sluice gate to deform and abrade, and even it may be out of order. In order to solve this problem we design two kinds of fuzzy PI controllers. The former is for a position control of two cylinders, the latter is for their synchronous control. We show some simulation results compare the performance of fuzzy PI controller to the conventional PID controller.

A Fault Detection system Design for Uncertain Nonlinear Systems

This paper deals with a fault detection system design for nonlinear systems with uncertain time varying parameters modelled as a T-S fuzzy system. A coprime factorization for T-S fuzzy systems is defined and a residual generator is designed using a left coprime factor. A fault detection criteria derived from the residual generator is also suggested. In order to demonstrate the efficacy of the suggested method, the fault defection method is applied to an inverted pendulum system and computer simulations are performed.

A fault detection system design for uncertain t-s fuzzy systems

This paper deals with a fault detection system design for uncertain nonlinear systems modeled as T-S fuzzy systems with the integral quadratic constraints. In order to generate a residual signal, we used a left coprime factorization of the T-S fuzzy system. Using a multi-objective filter, the fault occurrence can be detected effectively. A simulation study with nuclear steam generator level control system shows that the suggested method can be applied to detect the fault in actual applications.

A Fractional Model Reduction for T-S Fuzzy Systems with State Delay

This paper deals with a fractional model reduction for T-S fuzzy systems with time varying delayed states. A contractive coprime factorization of time delayed T-S fuzzy systems is defined and obtained by solving linear matrix inequalities. Using generalized controllability and observability gramians of the contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is performed.

A Fault Detection System Design for Uncertain Fuzzy Systems

This paper deals with a fault detection system design for uncertain nonlinear systems modelled as T-S fuzzy systems with the integral quadratic constraints. In order to generate a residual signal, we used a left coprime factorization of the T-S fuzzy system. From the filtered signal of the residual generator, the fault occurence can be detected effectively. A simulation study with nuclear steam generator level control system shows that the suggested method can be applied to detect the fault in actual applications.

A Fault Detection System Design for Nuclear Steam Generator Level Control System

This paper deals with a fault detection system design for nuclear steam generator water level control system. We expressed the nonlinear properties of the steam generator level system as a T-S fuzzy system with time varying uncertain parameters. We design a residual generator using a left coprime factorization of the T-S fuzzy model and a fault detection filter in order to improve the fault detection performance. We demonstrate the efficiency of the suggested design method via many computer simulations.

A Balanced Model Reduction for Uncertain Nonlinear Systems

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

Robust Mixed H 2 /H ∞ Filter Design for Uncertain Fuzzy Systems

This paper deals with a robust mixed filter design problem for a nonlinear dynamic system modeled as a T-S fuzzy system. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. A sufficient condition for solvability is given in terms of linear matrix inequality problem which can be efficiently solved using a convex optimization technique. In order to demonstrate the Proposed method, a numerical design example is provided.