教師著作

Permanent URI for this collectionhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31266

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    A performance approach to fuzzy control design for nonlinear systems
    (Elsevier, 1994-06-24) Yeh, Zong-Mu
    This paper presents a systematic methodology to the design of a decentralized fuzzy logic controller for large-scale nonlinear systems. A new method which is based on a performance index of sliding mode control is used to derive fuzzy rules and an adaptive algorithm is used to reduce the chattering phenomenon. The simulation results of a two-inverted pendulum system and a two-link manipulator demonstrate that the attractive features of the proposed approach include a smaller residual error and robustness against nonlinear interactions.
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    A Decentralized fuzzy logic controller Design
    (Institute of Electrical and Electronics Engineers (IEEE), 1994-06-26) Yeh, Zong-Mu
    Presents a systematic methodology to the design of a decentralized fuzzy logic controller for large-scale nonlinear systems. A new method which is based on a performance index of sliding mode control is used to derive fuzzy rules and an adaptive algorithm is used to eliminate the chattering phenomenon. The simulation results of a two-inverted pendulum system and a two-link manipulator demonstrate that the attractive features of the proposed approach include a smaller residual error and robustness against nonlinear interactions.
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    An Adaptive Neural Net controller Design
    (Institute of Electrical and Electronics Engineers (IEEE), 1994-06-27) Yeh, Zong-Mu
    This paper presents a stability method which is based on the stability condition of sliding mode control to derive the learning law for neural net controllers (NNC) to ensure the convergence of the training algorithm and the stability of the closed-loop system. The proposed method is an online approach of a multilayered neural network which does not require any information about the system dynamics, and the lengthy training of the controller can be eliminated by using the proposed approach. The simulation results of a nonlinear system and a two-link manipulator demonstrate that the attractive features of the proposed approach include a smaller residual error and robustness against nonlinear interactions of an interconnected system or external disturbances.
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    On-Learning Neurocontrol of Nonlinear Systems
    (1994-12-01) Yeh, Zong-Mu
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    A Self-Organized Neural Fuzzy Logic controller
    (1994-12-01) Yeh, Zong-Mu; Tarng, Y.S.; Nian, C.Y.
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    A Decentralized Learning controller for Nonlinear Systems
    (Institute of Electrical and Electronics Engineers (IEEE), 1994-12-05) Yeh, Zong-Mu; Hsu, How-Gao; Lien, Ching-Chieh
    This paper presents a decentralized learning controller for large-scale nonlinear systems. A new learning method which is based on a performance index of sliding mode control is used to derive an iterative learning algorithm to obtain control actions. The effectiveness and the performance of the proposed approach are illustrated by the simulation results of a two-inverted pendulum system and a two-link manipulator. The attractive features also include a smaller residual error and robustness against nonlinear interactions.
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    A self-organizing decentralized fuzzy neural net controller
    (Institute of Electrical and Electronics Engineers (IEEE), 1995-03-20) Yeh, Zong-Mu; Chen, Hung-Pin
    This paper presents a self-organizing decentralized learning controller using fuzzy control and neurocontrol for large-scale nonlinear systems. A new online unsupervised learning method which is based on a performance index of sliding mode control is used to train the fuzzy neural net controller to obtain control actions. To overcome the interactions between the subsystems, a learning algorithm is adopted to modify the control input to improve the system performance. The effectiveness and the performance of the proposed approach are illustrated by the simulation results of a two-inverted pendulum system and a two-link manipulator. The attractive features also include a smaller residual error and robustness against nonlinear interactions.
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    Design of Adaptive Neural Net controller
    (Institute of Electrical and Electronics Engineers (IEEE), 1995-05-22) Yeh, Zong-Mu
    This paper presents an adaptive neural net controller for controlling given plants which are unknown. In the neural net structure, a two-layered network is used to emulate the unknown plant dynamics, and another two-layer neural network, which is the inverse of the estimator, is used to generate the control action on-line. A modified Widrow-Hoff delta rule is adopted as a learning algorithm to minimize the error between the real plant response and the output of the estimator. An effective learning method which is based on sliding motions is provided to tune the control action to improve the system performance and convergence. The major advantage of the proposed approach is that the lengthy training of the controller might be eliminated. The effectiveness of the proposed approach is illustrated through simulations of controlling a unstable plant and normalized motor model with noise disturbances.
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    A self-organizing neural fuzzy logic controller for turning operations
    (Elsevier, 1995-10-01) Yeh, Zong-Mu; Tarng, Y. S.; Nian, C. Y.
    This paper proposes a neural fuzzy logic controller to achieve self-organizing control for turning operations. A new learning method which is based on a performance index of sliding mode control is used for control rule modifications and some supervision rules are also given to secure rule modifications. One of the major advantages of the proposed model is that it can start from an empty control rule base. Simulation and experimental results of the control of a constant turning force under varying cutting conditions are given to illustrate the effectiveness of the proposed method.
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    運用蓋拉金積分法解非均質物體之彈性力場
    (逢甲大學, 1995-11-01) 李永明; 屠名正; 孫玉柱
    在以往研究非均質物體彈性力場的文獻中，基體大多是無限大的，本文則使用蓋拉金積分法，求解三維有限區域基體，含一個或多個球體、橢圓體雜物之非均質物體之彈性力場。本文所解問題之邊界條件為固定值之應變場，而冗長的數學運算則由數值程式配合 Mathematica 軟體來執行。本文也研究不同相介質的機械性質比，夾雜物之體積分率及長寬比等，對彈性力場整體與局部之影響。 經過詳細的分析，下列兩種效應非常顯著（ 1 ）在不同介質界面附近的彈性力場， 會因夾雜物存在而受到干擾，（ 2 ）在不同介質界面間，會有應力集中的現象。
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    Adaptive Fuzzy Logic controller
    (1995-12-07) Yeh, Zong-Mu
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    A study of backlash on the motion accuracy of CNC lathes
    (Elsevier, 1996-05-01) Kao, J.Y.; Yeh, Zong-Mu; Tarng, Y.S.; Lin, Y.S.
    In this paper, an analytical solution is reported to explain the experimentally observed backlash behaviors on the motion accuracy of CNC lathes. It is found that backlash occurs when the feed direction is reversed. Due to the imperfect transient response of the driving mechanism, not only the static backlash error but also the dynamic backlash error is generated on the contouring profile. A simple control strategy is then developed to reduce the static and dynamic backlash errors. Computational simulations and experimental results are presented to illustrate the proposed method.
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    Cross-Coupled Fuzzy Logic Control for Biaxial Servomechanisms
    (Institute of Electrical and Electronics Engineers (IEEE), 1996-09-08) Yeh, Zong-Mu; Tarng, Y.S.; Lin, Y.S.
    This paper presents a design and implementation case study that focuses on contour of a biaxial CNC machine tools. However, it is difficult to obtain an accurate nonlinear mathematical model of cross-coupled multi-axis machine tools. In this paper we investigate an alternative to conventional approaches where we employ cross-coupled fuzzy logic controllers for improving contouring accuracy of multi-axis CNC machine tools. A new fuzzy rule-generated method which is based on a performance index of the contour error obtained from an online estimation algorithm is proposed. Experimental results have shown that the desired contouring accuracy can be achieved, and the proposed approach outperforms over uncoupled approaches. In conventional control, increasing contour feedrate for productivity may result in larger contour errors. However, the experimental results have shown that the performance of the proposed approach is still quite good with the increasing contour feedrate.
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    Genetic synthesis of fuzzy logic controller in turning
    (Elsevier, 1996-11-11) Tarng, Y. S.; Yeh, Zong-Mu
    The paper presents an optimal fuzzy logic controller design using efficient robust optimization techniques called genetic algorithms. It is shown that genetic algorithms can automatically search input and output scaling factors, membership functions, and fuzzy rules of the fuzzy logic controllers based on a fitness function. As a result, fuzzy logic controllers with optimal control performance can be systematically constructed instead of using a time-consuming trial and error approach. An adaptive force control system in turning operations is then used to illustrate the proposed method. It is shown that the developed fuzzy logic controller can achieve an automatic adjustment of feed rate to optimize the production rate with a constant cutting force in turning operations.
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    A Bi-tree Multi-stage Inference Fuzzy Control System
    (Institute of Electrical and Electronics Engineers (IEEE), 1996-12-11) Yeh, Zong-Mu; Chen, Hung-Pin
    This paper presents a methodology for the design of a binary tree multi-stage inference fuzzy controller in which the consequence in an inference stage is passed to the next stage as fact, and so forth. A new general method which is based on a performance index of the control system is used to generate fuzzy rule bases for bi-tree multi-stage inference. This proposed method can be used to reduce the complexity of fuzzy rule sets. The new method has been applied to control a truck-and-two-trailer system. The simulation studies showed that the proposed method is feasible.
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    Adaptive Multivariable Fuzzy Logic controller
    (Elsevier, 1997-02-16) Yeh, Zong-Mu
    This paper presents a systematic methodology to the design of a multivariable fuzzy logic controller (MFLC) for large-scale nonlinear systems. A new general method which is based on a performance index of sliding motion is used to generate a fuzzy control rule base. Reducible input variables obtained from sliding motion are adopted as input variable of the fuzzy controller and the output scale factors of the MFLC are tuned by the switching variable. Thus, the determination of the input/output scale factors becomes easier and the system performance is significantly improved. The simulation results of a Puma 560 system and a two-inverted pendulum system demonstrate that the attractive features of this proposed approach include a smaller residual error and robustness against nonlinear interactions.
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