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 topic(s): Robust control & Fuzzy control system. The author has an hindex of 14, co-authored 73 publication(s) receiving 1463 citation(s). Previous affiliations of Chun-Hsiung Fang include National Sun Yat-sen University.

A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems

Abstract: This paper proposes a new quadratic stabilization condition for Takagi-Sugeno (T-S) fuzzy control systems. The condition is represented in the form of linear matrix inequalities (LMIs) and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature. A rigorous theoretic proof is given to show that the proposed condition can include previous results as special cases. In comparison with conventional conditions, the proposed condition is not only suitable for designing fuzzy state feedback controllers but also convenient for fuzzy static output feedback controller design. The latter design work is quite hard for T-S fuzzy control systems. Based on the LMI-based conditions derived, one can easily synthesize controllers for stabilizing T-S fuzzy control systems. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. Finally, the validity and applicability of the proposed approach are successfully demonstrated in the control of a continuous-time nonlinear system.

A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems

Abstract: This paper proposes a new quadratic stabilization condition for T-S fuzzy control systems. The condition is represented in the form of linear matrix inequalities (LMIs) and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature. A rigorous theoretic proof is given to show that the proposed condition can include previous results as special cases. In comparison with conventional conditions, the proposed condition is not only suitable for designing fuzzy state feedback controllers but also convenient for fuzzy static output feedback controller design. The latter design work is quite hard for T-S fuzzy control systems. Based on the LMI-based conditions derived, one can easily synthesize controllers for stabilizing T-S fuzzy control systems. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable.

Robust H∞ fuzzy static output feedback control of T-S fuzzy systems with parametric uncertainties

Abstract: This paper addresses robust H"~ fuzzy static output feedback control problem for T-S fuzzy systems with time-varying norm-bounded uncertainties. Sufficient conditions for synthesis of a fuzzy static output feedback controller for T-S fuzzy systems are derived in terms of a set of linear matrix inequalities (LMIs). In comparison with the existing literatures, the proposed approach not only simplifies the design procedure but also achieves a better H"~ performance. Three drawbacks existing in the previous papers such as coordinate transformation, same output matrices and BMI problem have been eliminated. The effectiveness of the proposed design method is demonstrated by an example for the control of a truck-trailer system.

Analysis of stability robustness for generalized state-space systems with structured perturbations

Abstract: A new approach is proposed to analyze the stability robustness of generalized state-space systems with structured perturbations. The presented method is computationally simple to use and can easily be calculated by computer. As far as we are aware, this paper seems to be the first one to solve the robust stability problems for generalized state-space systems with structured uncertainties. The robust stability problem of generalized state-space systems is more complicated than that of regular state-space systems because it needs consideration of not only stability robustness but also system regularity and impulse elimination. The latter two ones need not be considered in regular state-space systems.

Robust control analysis and design for discrete-time singular systems

Abstract: In this paper, we propose a simple approach to analyse stability robustness of discrete-time singular systems under structured perturbations. The developed robustness criteria are then applied to solve robust regional pole-assignment problems of singular systems. A robust control design algorithm, via state feedback, is also given. The robust stability problem of singular systems is more complicated than that of regular systems. Not only stability robustness but system regularity and impulse elimination should be considered simultaneously. Since the results of robust control and analysis for singular systems is not available in the literature as much as other fields, the paper may be viewed as a complementary result in this field. Although only discrete-time case is discussed, several results can be directly applied to continuous-time systems as well.

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.

Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya's theorem

Abstract: Stability and performance requirements in fuzzy control of Takagi-Sugeno systems are usually stated as fuzzy summations, i.e., sums of terms, related to Lyapunov functions, which are weighted by membership functions or products of them. This paper presents an application to fuzzy control of Polya's theorems on positive forms on the standard simplex. The result provides a set of progressively less conservative sufficient conditions for proving positivity of fuzzy summations; such conditions are less and less conservative as a complexity parameter, n, increases. Particular cases of such conditions are those in [C.-H. Fang, Y.-S. Liu, S.-W. Kau, L. Hong, C.-H. Lee, A new LMI-based approach to relaxed quadratic stabilization of T-S fuzzy control systems, IEEE Trans. Fuzzy Systems 14 (2006) 286-397; X. Liu, Q. Zhang, New approaches to H"~ controller designs based on fuzzy observers for T-S fuzzy systems via LMI, Automatica 39 (9) (2003) 1571-1582], with n=2 and 3, respectively. The proposed conditions are asymptotically exact, i.e., necessary and sufficient when n tends to infinity or, equivalently, when a tolerance parameter tends to zero.

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.

Robust stability and stabilization of discrete singular systems: an equivalent characterization

Abstract: This note deals with the problems of robust stability and stabilization for uncertain discrete-time singular systems. The parameter uncertainties are assumed to be time-invariant and norm-bounded appearing in both the state and input matrices. A new necessary and sufficient condition for a discrete-time singular system to be regular, causal and stable is proposed in terms of a strict linear matrix inequality (LMI). Based on this, the concepts of generalized quadratic stability and generalized quadratic stabilization for uncertain discrete-time singular systems are introduced. Necessary and sufficient conditions for generalized quadratic stability and generalized quadratic stabilization are obtained in terms of a strict LMI and a set of matrix inequalities, respectively. With these conditions, the problems of robust stability and robust stabilization are solved. An explicit expression of a desired state feedback controller is also given, which involves no matrix decomposition. Finally, an illustrative example is provided to demonstrate the applicability of the proposed approach.