Ken Yeh

Modeling, H∞ Control and Stability Analysis for Structural Systems Using Takagi-Sugeno Fuzzy Model

This article proposes a design method for producing H ∞ control performance for structural systems using the Tagagi-Sugeno (T-S) fuzzy model. A structural system with a tuned mass damper is modeled using a T-S type fuzzy model. Using the parallel distributed compensation (PDC) scheme, we design a nonlinear fuzzy controller for the tuned mass damper system. A sufficient stability condition for the control system is derived in terms of Lyapunov theory and this control problem is reformulated into solving the linear matrix inequalities (LMI) problem. Finally, the tuned mass damper is designed based on the first modal frequency of the control system and a fuzzy controller to stabilize the structural system is then found using the Matlab LMI toolbox. A simulation example is given to show the feasibility of the proposed fuzzy controller design method.

A NOVEL DELAY-DEPENDENT CRITERION FOR TIME-DELAY T-S FUZZY SYSTEMS USING FUZZY LYAPUNOV METHOD

This study presents an H∞ controller design for time-delay T-S fuzzy systems based on the fuzzy Lyapunov method, which is defined in terms of fuzzy blending quadratic Lyapunov functions. The delay-...

Stability analysis for nonlinear systems subjected to external force

This paper considers a fuzzy Lyapunov method for stability analysis of nonlinear systems subjected to external forces. The nonlinear systems under external forces can be represented by Tagagi-Sugeno (T-S) fuzzy model. In order to design a nonlinear fuzzy controller to stabilize this nonlinear system, the parallel distributed compensation (PDC). scheme is used to construct a global fuzzy logic controller. We then propose the robustness design to ensure the modeling error is bounded and some stability conditions are derived based on the controlled systems. Based on the stability criterion, the nonlinear systems with external forces are guaranteed to be stable. This control problem can be reformulated into linear matrix inequalities (LMI) problem.

Stability Analysis for Floating Structures Using T-S Fuzzy Control

This study constructs a mathematical model of an ocean environment in which wave-induced flow fields cause structural surge motion. The solutions corresponding to the mathematical model are derived analytically. In this study, a fuzzy control technique is developed to mitigate structural vibration. The Takagi-Sugeno (T-S) fuzzy model is employed to approximate the oceanic structure and a parallel distributed compensation (PDC) scheme is utilized in the controller design procedure to reduce structural response.

Stability Analysis of Time-Delay Fuzzy Systems Using Fuzzy Lyapunov Method

This study presents an H-infinite controller design for time-delay Takagi-Sugeno (T-S) fuzzy systems based on the fuzzy Lyapunov method, which is defined in terms of fuzzy blending quadratic Lyapunov functions. The delay-dependent robust stability criterion is derived in terms of the fuzzy Lyapunov method to guarantee the stability of time-delay T-S fuzzy systems subjected to disturbances. Based on the delay-dependent condition and parallel distributed compensation (PDC) scheme, the controller design problem is transformed into solving linear matrix inequalities (LMI).

Application to GA-Based Fuzzy Control for Nonlinear Systems with Uncertainty

In this study, we strive to combine the advantages of fuzzy theory, genetic algorithms (GA), H-infinite tracking control schemes, smooth control and adaptive laws to design an adaptive fuzzy sliding model controller for the rapid and efficient stabilization of complex and nonlinear systems. First, we utilize a reference model and a fuzzy model (both involvingrules) to describe and well-approximate an uncertain, nonlinear plant. The FLC rules and the consequent parameter are decided on via GA. A boundary-layer function is introduced into these updated laws to cover modeling errors and to guarantee that the state errors converge into a specified error bound. After this, a H-infinite tracking problem is characterized. We solve an eigenvalue problem (EVP), and derive a modified adaptive neural network controller (MANNC) to simultaneously stabilize and control the system and achieve H-infinite control performance.

Stability Analysis of Fuzzy Control for Nonlinear Systems

In this study, we propose a method of stability analysis for a GA-Based reference ANNC capable of handling these types of problems for a nonlinear system. The initial values of the consequent parameter vector are decided via a genetic algorithm (GA) after which a modified adaptive law is derived based on Lyapunov stability theory to control the nonlinear system for tracking a user-defined reference model. The requirement of Kalman-Yacubovich lemma is fulfilling. A boundary-layer function is introduced into these updating laws to cover parameter and modeling errors, and to guarantee that the state errors converge into a specified error bound. After this, an adaptive neural network controller (ANNC) is derived to simultaneously stabilize and control the system.

Applying the Linear Matrix Inequality for Hybrid Fuzzy/H-infinity Control of Active Structural Damping

This paper proposes a design method of Hinfin control performance for structural systems using Takagi-Sugeno (T-S) fuzzy model. The structural system with tuned mass damper is modeled by T-S type fuzzy model. By using parallel distributed compensation (PDC) scheme, we design a nonlinear fuzzy controller for the tuned mass damper system. According to the control system, a sufficient stability condition is derived in terms of Lyapunov theory and this control problem is reformulated into solving linear matrix inequalities (LMI) problem.