Chun-Hsiung Fang

Bio: Chun-Hsiung Fang is an academic researcher from National Kaohsiung University of Applied Sciences. The author has contributed to research in topics: Robust control & Fuzzy control system. The author has an hindex of 14, co-authored 73 publications receiving 1463 citations. Previous affiliations of Chun-Hsiung Fang include National Sun Yat-sen University.

Fuzzy tracking control design

Abstract: The tracking control problem of T-S fuzzy systems is solved in the paper. A new method is proposed to improve the existing result. All the designed conditions are expressed in the form of LMIs. Thus they are numerically realizable. From the simulation example, it can be seen that the proposed approach achieves a better tracking performance.

Robust H ∞ fuzzy control for nonlinear discrete-time systems by nonquadratic Lyapunov function approach

Abstract: In this paper, a new relaxed condition is proposed to deal with H ∞ control for nonlinear discrete-time systems that are represented by T-S fuzzy model. The main results are derived based on the nonquadratic Lyapunov function and the non-PDC controller. The new relaxed conditions are expressed in terms of linear matrix inequalities, which can be efficiently solved by software. Finally, illustrative examples are given to show the performance of our approach.

A new approach to stabilization of T-S fuzzy systems

Abstract: A more relaxed stabilization condition for continuous time T-S fuzzy systems is proposed by using the multiple Lyapunov function and the non-PDC controller. All stability conditions are represented in terms of linear matrix inequalities (LMIs). The proposed approach is simpler and more realizable in dealing the time derivatives of membership functions in comparison with existing results.

An improvement on observer-based H ∞ control of fuzzy systems

Abstract: The paper solves the observer-based H ∞ control problems of T-S fuzzy systems. Two conditions that guarantee the existence of H ∞ controller based on fuzzy observers are developed. The conditions are more relaxed than the existing one and ensure the designed fuzzy controller achieving a better H ∞ control performance. A numerical example is given to demonstrate the validity and applicability of the proposed approach in the control of a nonlinear system.

Image Processing

Abstract: MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

Robust stability and stabilization for singular systems with state delay and parameter uncertainty

Abstract: Considers the problems of robust stability and stabilization for uncertain continuous singular systems with state delay. The parametric uncertainty is assumed to be norm bounded. The purpose of the robust stability problem is to give conditions such that the uncertain singular system is regular, impulse free, and stable for all admissible uncertainties, while the purpose of the robust stabilization is to design a state feedback control law such that the resulting closed-loop system is robustly stable. These problems are solved via the notions of generalized quadratic stability and generalized quadratic stabilization, respectively. Necessary and sufficient conditions for generalized quadratic stability and generalized quadratic stabilization are derived. A strict linear matrix inequality (LMI) design approach is developed. An explicit expression for the desired robust state feedback control law is also given. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Stability Analysis of Interval Type-2 Fuzzy-Model-Based Control Systems

Abstract: This paper presents the stability analysis of interval type-2 fuzzy-model-based (FMB) control systems. To investigate the system stability, an interval type-2 Takagi-Sugeno (T-S) fuzzy model, which can be regarded as a collection of a number of type-1 T-S fuzzy models, is proposed to represent the nonlinear plant subject to parameter uncertainties. With the lower and upper membership functions, the parameter uncertainties can be effectively captured. Based on the interval type-2 T-S fuzzy model, an interval type-2 fuzzy controller is proposed to close the feedback loop. To facilitate the stability analysis, the information of the footprint of uncertainty is used to develop some membership function conditions, which allow the introduction of slack matrices to handle the parameter uncertainties in the stability analysis. Stability conditions in terms of linear matrix inequalities are derived using a Lyapunov-based approach. Simulation examples are given to illustrate the effectiveness of the proposed interval type-2 FMB control approach.

Fuzzy-Model-Based Reliable Static Output Feedback $\mathscr{H}_{\infty }$ Control of Nonlinear Hyperbolic PDE Systems

Abstract: This paper investigates the problem of output feedback robust $\mathscr{H}_{\infty }$ control for a class of nonlinear spatially distributed systems described by first-order hyperbolic partial differential equations (PDEs) with Markovian jumping actuator faults. The nonlinear hyperbolic PDE systems are first expressed by Takagi–Sugeno fuzzy models with parameter uncertainties, and then, the objective is to design a reliable distributed fuzzy static output feedback controller guaranteeing the stochastic exponential stability of the resulting closed-loop system with certain $\mathscr{H}_{\infty }$ disturbance attenuation performance. Based on a Markovian Lyapunov functional combined with some matrix inequality convexification techniques, two approaches are developed for reliable fuzzy static output feedback controller design of the underlying fuzzy PDE systems. It is shown that the controller gains can be obtained by solving a set of finite linear matrix inequalities based on the finite-difference method in space. Finally, two examples are presented to demonstrate the effectiveness of the proposed methods.