Wen-Jer Chang

National Taiwan Ocean University, Keelung, Taiwan, Taiwan

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Publications (91)52.82 Total impact

  • Wen-Jer Chang, Che-Pin Kuo, Cheung-Chieh Ku
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    ABSTRACT: This paper provides the criterion for discussing stability analysis and synthesis of a class of complex nonlinear systems represented by Takagi–Sugeno fuzzy models with multiplicative noise. In the consequent part of the T–S fuzzy models, the Itô’s stochastic differential equations are introduced to represent the linear subsystems with multiplicative noise. Under the concept of imperfect premise matching, a novel fuzzy controller is designed without limitation of sharing the same membership function of fuzzy models. In other words, the imperfect premise matching technique provides a more general approach in designing fuzzy controllers. The advantage of the proposed fuzzy controller design method is that it can be enhanced more flexibility and robustness than well-known parallel distributed compensation based fuzzy control approach. At last, two numerical examples are given to illustrate the usefulness and effectiveness of proposed fuzzy controller design method.
    Neurocomputing 04/2015; 154. DOI:10.1016/j.neucom.2014.11.065 · 2.01 Impact Factor
  • Wen-Jer Chang, Ying-Jie Shih
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    ABSTRACT: In this paper, a H∞ performance constrained fuzzy control approach is investigated for a class of nonlinear stochastic systems subject to actuator saturation. The nonlinear stochastic systems considered in this paper are represented by Takagi-Sugeno fuzzy models with multiplicative noises. According to H∞ performance constraint and actuator saturation, it is shown that the stabilization of multiplicative noised Takagi-Sugeno fuzzy models can be formulated as a convex optimization problem subject to linear matrix inequalities. The proposed fuzzy control method is accomplished based on the Lyapunov stability theory. Simulation study on a continuous-time nonlinear stochastic ship steering system is given to show the performances of the proposed H∞ performance constrained fuzzy control methodology.
    Neurocomputing 01/2015; 148:512-520. DOI:10.1016/j.neucom.2014.07.012 · 2.01 Impact Factor
  • Wen-Jer Chang, Bo-Jyun Huang
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    ABSTRACT: The multi-constrained robust fuzzy control problem is investigated in this paper for perturbed continuous-time nonlinear stochastic systems. The nonlinear system considered in this paper is represented by a Takagi–Sugeno fuzzy model with perturbations and state multiplicative noises. The multiple performance constraints considered in this paper include stability, passivity and individual state variance constraints. The Lyapunov stability theory is employed to derive sufficient conditions to achieve the above performance constraints. By solving these sufficient conditions, the contribution of this paper is to develop a parallel distributed compensation based robust fuzzy control approach to satisfy multiple performance constraints for perturbed nonlinear systems with multiplicative noises. At last, a numerical example for the control of perturbed inverted pendulum system is provided to illustrate the applicability and effectiveness of the proposed multi-constrained robust fuzzy control method.
    ISA Transactions 09/2014; DOI:10.1016/j.isatra.2014.08.016 · 2.26 Impact Factor
  • Wen-Jer Chang, Bo-Jyun Huang, Po-Hsun Chen
    Mathematical Problems in Engineering 01/2014; 2014:1-12. DOI:10.1155/2014/598618 · 1.08 Impact Factor
  • Wen-Jer Chang, Bo-Jyun Huang, Zong-Guo Fu
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    ABSTRACT: An individual state variance constrained fuzzy controller design methodology is developed in this paper to achieve state variance constraint and passivity constraint for discrete nonlinear multiplicative noised stochastic systems. The discrete nonlinear multiplicative noised stochastic system considered in this paper is represented by the discrete-time Takagi-Sugeno fuzzy model. The proposed fuzzy controller is constructed by the concept of parallel distributed compensation. The sufficient conditions are derived based on the Lyapunov theory. Employing the matrix transformation technique, these sufficient conditions can be expressed in terms of linear matrix inequalities. Finally, the feasibility and validity of the proposed method are illustrated with a numerical simulation example.
    2013 International Conference on Fuzzy Theory and Its Applications (iFUZZY); 12/2013
  • Wen-Jer Chang, Bo-Jyun Huang, Po-Hsun Chen
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    ABSTRACT: This paper studies the passive and individual variance constrained fuzzy control problem for discrete-time stochastic Takagi-Sugeno fuzzy systems. The performances considered in this paper include passivity constraint and individual state variance constraint. The proposed fuzzy control is accomplished by using the concept of parallel distributed compensation. Based on the Lyapunov stability theory, the sufficient conditions are derived to achieve the above multiple performance constraints. In order to illustrate the applicability and validity of the proposed fuzzy control method, a numerical control simulation for a discrete-time Takagi-Sugeno fuzzy system with multiplicative noise is provided.
    2013 CACS International Automatic Control Conference (CACS); 12/2013
  • Wen-Jer Chang, Fung-Lin Hsu, Bo-Jyun Huang
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    ABSTRACT: This paper proposes a passive fuzzy controller design methodology for stabilization of nonlinear system with external disturbance based on multiplicative noised Takagi-Sugeno fuzzy model and parallel distributed compensation control design. Applying the Itô's formula and the sense of mean square, the sufficient conditions are developed to analyze the stability and to design the controller for stochastic nonlinear systems. The sufficient conditions derived in this paper belong to the linear matrix inequality forms which can be solved efficiently by convex optimal programming algorithm. Besides, the passivity theory is applied to discuss the effect of external disturbance on system. Finally, a ball and beam system is provided in the example to demonstrate the applications of the proposed fuzzy controller design technique.
    2013 International Conference on Fuzzy Theory and Its Applications (iFUZZY); 12/2013
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    ABSTRACT: This article presents an estimated state feedback fuzzy controller design method for uncertain passive discrete-time nonlinear stochastic systems with multiplicative noises. The nonlinear stochastic systems considered in this article are represented by Takagi–Sugeno (T–S) fuzzy models. For describing stochastic behaviors, stochastic differential equations are used to structure the stochastic T–S fuzzy model for representing nonlinear stochastic systems. Besides, the uncertainties of the controlled system are considered for dealing with molding errors and varying parameters. The concept of parallel distributed compensation is employed in this article to construct the estimated state feedback fuzzy controllers. Applying the Lyapunov and passivity theories, the sufficient stability conditions are derived in terms of linear matrix inequality. Finally, a numerical example is provided to show the effectiveness and applicability of the proposed fuzzy controller design approach.
    Journal- Chinese Institute of Engineers 09/2013; 36(6). DOI:10.1080/02533839.2012.740584 · 0.21 Impact Factor
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    ABSTRACT: This paper investigates a fuzzy controller design method for discrete-time nonlinear stochastic time-delay systems which are presented by the Takagi-Sugeno (T-S) fuzzy model with multiplicative noises. Utilizing the proposed design method, the fuzzy controller can be carried out via not only state feedback scheme but also output feedback scheme. Both of them are accomplished by the concept of imperfect premise matching (IPM). For discussing the stabilization problem, the Lyapunov-Krasovskii function and passivity theory are applied to derive the sufficient conditions. Moreover, the discrete Jensen inequality is employed to decrease the conservatism of the proposed method. Finally, a numerical example for the control of a nonlinear time-delay pendulum system is provided to show the effectiveness and usefulness of the proposed design method.
    International Journal of Control Automation and Systems 06/2013; 11(3). DOI:10.1007/s12555-012-0087-0 · 1.07 Impact Factor
  • Wen-Jer Chang, Bo-Jyun Huang
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    ABSTRACT: The variance and passivity constrained fuzzy control problem for the nonlinear ship steering systems with state multiplicative noises is investigated. The continuous-time Takagi-Sugeno fuzzy model is used to represent the nonlinear ship steering systems with state multiplicative noises. In order to simultaneously achieve variance, passivity, and stability performances, some sufficient conditions are derived based on the Lyapunov theory. Employing the matrix transformation technique, these sufficient conditions can be expressed in terms of linear matrix inequalities. By solving the corresponding linear matrix inequality conditions, a parallel distributed compensation based fuzzy controller can be obtained to guarantee the stability of the closed-loop nonlinear ship steering systems subject to variance and passivity performance constraints. Finally, a numerical simulation example is provided to illustrate the usefulness and applicability of the proposed multiple performance constrained fuzzy control method.
    Mathematical Problems in Engineering 03/2013; 2013. DOI:10.1155/2013/687317 · 1.08 Impact Factor
  • Wen-Jer Chang, Cheung-Chieh Ku, Hao-Jie Liang
    Mathematical Problems in Engineering 01/2013; 2013:1-9. DOI:10.1155/2013/732939 · 1.08 Impact Factor
  • Wen-Jer Chang, Yao-Chung Chang
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    ABSTRACT: This paper studies the line-integral fuzzy Lyapunov function based fuzzy controller design for continuous-time Takagi-Sugeno fuzzy systems with multiplicative noises. For stability analysis and synthesis, the sufficient conditions are derived via line-integral fuzzy Lyapunov functions. These conditions belong to the linear matrix inequality forms which can be solved by the convex optimal programming algorithm. In addition, the passivity theory is utilized to deal with the effect of external disturbance in the system. Finally, a numerical example is supplied to show the usefulness and effectiveness of the proposed design method.
    Control and Automation (ICCA), 2013 10th IEEE International Conference on; 01/2013
  • Wen-Jer Chang, Cheung-Chieh Ku, Zong-Guo Fu
    Mathematical Problems in Engineering 01/2013; 2013:1-12. DOI:10.1155/2013/159279 · 1.08 Impact Factor
  • Wen-Jer Chang, Bo-Jyun Huang
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    ABSTRACT: A passive fuzzy controller design methodology is developed in this paper to achieve state variance constraint for continuous-time Takagi-Sugeno (T-S) fuzzy models. The proposed fuzzy controller is constructed by the concept of Parallel Distributed Compensation (PDC). Based on the Lyapunov theory, the sufficient conditions are derived to guarantee the stability of the closed-loop system. Besides, the passivity and variance constraints are also considered in the derivations of these sufficient conditions. These sufficient conditions belong to the Linear Matrix Inequality (LMI) forms, which can be solved by the convex optimal programming algorithm. Finally, the feasibility and validity of the proposed method are illustrated with a numerical simulation example.
    Power Electronics and Drive Systems (PEDS), 2013 IEEE 10th International Conference on; 01/2013
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    ABSTRACT: This paper presents a relaxed scheme of fuzzy controller design for continuous-time nonlinear stochastic systems that are constructed by the Takagi–Sugeno (T–S) fuzzy models with multiplicative noises. Through Nonquadratic Lyapunov Functions (NQLF) and Non-Parallel Distributed Compensation (Non-PDC) control law, the less conservative Linear Matrix Inequality (LMI) stabilization conditions on solving fuzzy controllers are derived. Furthermore, in order to study the effects of stochastic behaviors on dynamic systems in real environments, the multiplicative noise term is introduced in the consequent part of fuzzy systems. For decreasing the conservatism of the conventional PDC-based fuzzy control, the NQLF stability synthesis approach is developed in this paper to obtain relaxed stability conditions for T–S fuzzy models with multiplicative noises. Finally, some simulation examples are provided to demonstrate the validity and applicability of the proposed fuzzy controller design approach.
    Journal of the Franklin Institute 10/2012; 349(8):2664–2686. DOI:10.1016/j.jfranklin.2012.06.004 · 2.26 Impact Factor
  • Wen-Jer Chang, Liang-Zhi Liu, Cheung-Chieh Ku
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    ABSTRACT: This paper investigates the fuzzy control problem of a class of nonlinear continuous-time stochastic systems with achieving the passivity performance. A model-based observer feedback fuzzy control utilizing the concept of so-called parallel distributed compensation (PDC) is employed to stabilize the class of nonlinear stochastic systems that are represented by the Takagi-Sugeno (T-S) fuzzy models. Based on the Lyapunov criteria, the Linear Matrix Inequality (LMI) technique is used to synthesize the observer feedback fuzzy controller design such that the closed-loop system satisfies stability and passivity constraints, simultaneously. Finally, a numerical example is given to demonstrate the applicability and effectiveness of the proposed design method. KeywordsObserver feedback fuzzy control–parallel distributed compensation–passivity property–Takagi-Sugeno fuzzy model
    International Journal of Control Automation and Systems 06/2011; 9(3):550-557. DOI:10.1007/s12555-011-0315-z · 1.07 Impact Factor
  • Wen-Jer Chang, Yu-Teh Meng, Kuo-Hui Tsai
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    ABSTRACT: In this article, Takagi–Sugeno (T–S) fuzzy control theory is proposed as a key tool to design an effective active queue management (AQM) router for the transmission control protocol (TCP) networks. The probability control of packet marking in the TCP networks is characterised by an input constrained control problem in this article. By modelling the TCP network into a time-delay affine T–S fuzzy model, an input constrained fuzzy control methodology is developed in this article to serve the AQM router design. The proposed fuzzy control approach, which is developed based on the parallel distributed compensation technique, can provide smaller probability of dropping packets than previous AQM design schemes. Lastly, a numerical simulation is provided to illustrate the usefulness and effectiveness of the proposed design approach.
    International Journal of Systems Science 04/2011; 2011(pp. 1–17). DOI:10.1080/00207721.2011.572197 · 1.58 Impact Factor
  • Wen-Jer Chang, Wei-Han Huang, Cheung-Chieh Ku
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    ABSTRACT: The purpose of this paper is to study the stability analysis and controller synthesis principles of Discrete Perturbed Time-Delay Affine (DPTDA) Takagi-Sugeno (T-S) fuzzy models. In general, the T-S fuzzy model is a weighted sum of some linear subsystems via fuzzy membership functions. This paper considers fuzzy rules include both linear nominal parts and uncertain parameters in the time-delay affine T-S fuzzy model. For DPTDA T-S fuzzy models, the T-S fuzzy control scheme is used to confront the H∞ performance constraints. Some sufficient conditions are derived on robust H∞ disturbance attenuation in which both robust stability and a prescribed performance are required to be achieved. In order to find suitable fuzzy controllers, the Iterative Linear Matrix Inequality (ILMI) algorithm is employed to solve these sufficient conditions. At last, a numerical simulation for the nonlinear truck-trailer system is given to show the applications of the present design approach. KeywordsIterative linear matrix inequality–perturbed time-delay systems–S-procedure–Takagi-Sugeno fuzzy model
    International Journal of Control Automation and Systems 02/2011; 9(1):86-97. DOI:10.1007/s12555-011-0111-9 · 1.07 Impact Factor
  • Wen-Jer Chang, Che-Pin Kuo, Cheung-Chieh Ku
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    ABSTRACT: This paper presents the fuzzy controller design using Imperfect Premise Matching (IPM) for inverted pendulum robot system. With the movable supportive base, the inverted pendulum robot system can be applied to simulate human stance. Moreover, the Takagi-Sugeno (T-S) fuzzy model is employed to describe the complex nonlinearities of the system. And, the multiplicative noise term is introduced in the consequent part of fuzzy system to present the stochastic behavior of system. In order to extend the application of this paper, the IPM technique provides a generalization approach in designing proposed fuzzy controller. Based on the IPM, the fuzzy controller design can be enhanced more flexibility and robustness than one applies Parallel Distributed Compensation (PDC) approach. Finally, simulation results are given to demonstrate the usefulness and applicability of the proposed fuzzy controller design approach.
  • Wen-Jer Chang, Che-Pin Kuo, Po-Hsun Chen
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    ABSTRACT: This paper presents the stabilization conditions for designing fuzzy controller of two-link arm robot via Linear Parameter Varying (LPV) Takagi-Sugeno (T-S) fuzzy models. With the movable supportive base, the stochastic behavior of concerned system is considered in this paper for investigating the real environment. As mentioned above, combining the LPV system with T-S fuzzy model can approximate better the nonlinear two-link arm robot. Besides, the multiplicative noise term is introduced in the consequent part of fuzzy model to represent the stochastic behaviors. Based on the Lyapunov stability theory, the stability conditions are derived into Linear Matrix Inequality (LMI) problems that can be solved by using the convex optimal algorithm. Finally, simulation results are given to demonstrate the usefulness and applicability of the proposed fuzzy controller design approach.

Publication Stats

333 Citations
52.82 Total Impact Points

Institutions

  • 1999–2015
    • National Taiwan Ocean University
      • Department of Marine Engineering
      Keelung, Taiwan, Taiwan
  • 2004
    • Air Force Institute of Technology
      Air Force Academy, Colorado, United States
  • 2003–2004
    • National Central University
      • Department of Electrical Engineering
      Taoyuan City, Taiwan, Taiwan