scispace - formally typeset
Search or ask a question
Author

Chun-Hsiung Fang

Other affiliations: National Sun Yat-sen University
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.


Papers
More filters
Proceedings ArticleDOI
02 Jul 2007
TL;DR: A new LMI approach to establish a more relaxed sufficient condition for quadratic stabilization of T-S fuzzy systems and two conditions that guarantee the existence of the H∞ controller based on fuzzy observers are developed.
Abstract: This paper proposes a new LMI approach to establish a more relaxed sufficient condition for quadratic stabilization of T-S fuzzy systems. The proposed conditions not only improve the conservativeness but also include previous results as special cases. Extending the proposed idea to deal with the observer-based H ∞ control problem, two conditions that guarantee the existence of the H ∞ controller based on fuzzy observers are also developed. The conditions are more relaxed than the existing one and ensure the designed fuzzy H ∞ controller achieving a better performance. The validity and applicability of the proposed approach are successfully demonstrated in the control of a continuous-time nonlinear system.

2 citations

Proceedings ArticleDOI
01 Jul 1997
TL;DR: In this paper, the robust stability of generalized state-space systems with uncertainty in the form of one-parameter family of matrices is investigated by using the linear fractional transformation (LFT) techniques, exact bounds of the perturbation parameter can be obtained for both continuous and discrete time cases easily.
Abstract: Robust stability of generalized state-space systems with uncertainty in the form of one-parameter family of matrices is investigated in this paper. By using the linear fractional transformation (LFT) techniques, exact bounds of the perturbation parameter can be obtained for both continuous and discrete-time cases easily.

2 citations

Proceedings ArticleDOI
15 Feb 2009
TL;DR: A multimodality image registration framework (MIRF) is proposed for radiotherapy plans to be registered automatically with longitudinal follow-up images, and volume visualization is proved to display changes in serial medical images.
Abstract: The introduction of adaptive image-guided radiotherapy (IGRT) in the radiotherapy environment has contributed to the rapid accumulation of medical image data, often making it difficult to consolidate information on a single patient. For oncology patients, the lack of data integration can negatively impact on patient care. We propose a multimodality image registration framework (MIRF) for radiotherapy plans to be registered automatically with longitudinal follow-up images. Volume visualization is proved to display changes in serial medical images, and transformed dose distribution and mesh models of radiotherapy targets can be superimposed on these successive images.

2 citations

Journal ArticleDOI
TL;DR: In this article, a simple approach is proposed to ensure that all poles of an uncertain system are clustered in a prescribed ring, and explicit bounds on linear time-invariant structured perturbations are obtained.
Abstract: A simple approach is proposed to ensure that all poles of an uncertain system are clustered in a prescribed ring. The explicit bounds on linear time-invariant structured perturbations are obtained. Under these allowable highly structured perturbations, both stability robustness and certain performance robustness will thus be ensured. In the literature, as far as we are aware, little effort has been devoted to investigating pole-clustering robustness in such regions.

2 citations


Cited by
More filters
Proceedings Article
01 Jan 1994
TL;DR: 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.
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.

2,134 citations

Journal ArticleDOI
TL;DR: A strict linear matrix inequality (LMI) design approach is developed that solves the problems of robust stability and stabilization for uncertain continuous singular systems with state delay via the notions of generalized quadratic stability and generalizedquadratic stabilization.
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.

759 citations

Journal ArticleDOI
TL;DR: The result provides a set of progressively less conservative sufficient conditions for proving positivity of fuzzy summations of Polya's theorems on positive forms on the standard simplex.

582 citations

Journal ArticleDOI
01 Jun 2008
TL;DR: To investigate the system stability, an interval type-2 Takagi-Sugeno (T-S) fuzzy model is proposed to represent the nonlinear plant subject to parameter uncertainties, which allows the introduction of slack matrices to handle the parameter uncertainties in the stability analysis.
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.

382 citations

Journal ArticleDOI
TL;DR: Two approaches are developed for reliable fuzzy static output feedback controller design of the underlying fuzzy PDE systems and 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.
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.

336 citations