Browsing by Author "Lin, PZ"

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On-line genetic fuzzy-neural sliding mode controller design
(2005)
Lin, PZ
;
Wang, WY
;
Lee, TT
;
Chen, GM
;
電控工程研究所
In this paper, a novel online B-spline membership function (BMF) fuzzy-neural sliding mode controller trained by an adaptive bound reduced-form genetic algorithm (ABRGA) is developed to guarantee robust stability and tracking performance for robot manipulators with uncertainties and external disturbances. The general sliding manifold is used to construct the sliding surface and reduce the chattering of the control signal, which can be nonlinear or time varying. For the purpose of identification, the proposed BMF fuzzy-neural network trained by the ABRGA approximates the regressor of the manipulator. An adaptive bound algorithm is used to aid and speed up the searching speed of the RGA. Simulation results show that the proposed on-line ABRGA-based BMF fuzzy-neural sliding mode controller is effective and yields superior tracking performance for robot manipulators.
Type-2 fuzzy controller design using a sliding-mode approach for application to DC-DC converters
(2005-11-01)
Lin, PZ
;
Lin, CM
;
Hsu, CF
;
Lee, TT
;
電機資訊學士班
Fuzzy controllers and fuzzy sliding-mode controllers have found extensive use in a variety of applications. Generally, type-1 fuzzy sets are used for the membership functions of these controllers. However, in real-time applications, uncertainty associated with the available information always occurs. A type-2 fuzzy controller and a type-2 fuzzy sliding-mode controller are proposed that are able to solve the problem that the words used in the inference rules can mean different things to different people. Since the membership functions use type-2 fuzzy sets then, the proposed control schemes can handle the rule uncertainties when the operation is extremely uncertain and/or the membership grades cannot be exactly determined. The proposed control systems are applied to control a buck DC-DC converter. A comparison between a PI controller, a type-2 fuzzy controller and a type-2 fuzzy sliding-mode controller is made. The experimental results show that the type-2 fuzzy sliding-mode controller achieves the best control performance.
Type-2 fuzzy logic controller design for buck DC-DC converters
(2005)
Lin, PZ
;
Hsu, CF
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Type-1 fuzzy logic controllers (T1FLCs) have been successfully developed and used in various applications. The experience and knowledge of human experts are needed to decide both the membership functions and the fuzzy rules. However, in the real-time applications, uncertainty associated with the available information always happens. This paper proposes a type-2 fuzzy logic control (T2FLC), which involves the fuzzifier, rule base, fuzzy inference engine, and output processor with type reduction and defuzzifier. Because the antecedent and/or consequent membership functions of the T2FLC are type-2 fuzzy sets, the T2FLC can handle rule uncertainties when the operation is extremely uncertain and/or the engineers cannot exactly determine the membership grades. Furthermore, the proposed T2FLC is applied to a buck DC-DC converter control. Experimental results show that the proposed T2FLC is robust against input voltage and load resistance variations for the converter control.