Sliding-mode-controlled slider-crank mechanism with fuzzy neuralnetwork
Faa-Jeng Lin
Rong-Jong Wai
Dept. of Electr. Eng., Chung Yuan Christian Univ., Chung Li;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Feb 2001
Volume: 48,
Issue: 1
On page(s): 60-70
ISSN: 0278-0046
References Cited: 20
CODEN: ITIED6
INSPEC Accession Number: 6860880
Digital Object Identifier: 10.1109/41.904553
Current Version Published: 2002-08-07
Abstract
The dynamic response of a sliding-mode-controlled slider-crank
mechanism, which is driven by a permanent-magnet (PM) synchronous servo
motor, is studied in this paper. First, a position controller is
developed based on the principles of sliding-mode control. Moreover, to
relax the requirement of the bound of uncertainties in the design of a
sliding-mode controller, a fuzzy neural network (FNN) sliding-mode
controller is investigated, in which a FNN is adopted to adjust the
control gain in a switching control law on line to satisfy the sliding
mode condition. In addition, to guarantee the convergence of tracking
error, analytical methods based on a discrete-type Lyapunov function are
proposed to determine the varied learning rates of the FNN. Numerical
and experimental results show that the dynamic behaviors of the proposed
controller-motor-mechanism system are robust with regard to parametric
variations and external disturbances. Furthermore, compared with the
sliding-mode controller, smaller control effort results and the
chattering phenomenon is much reduced by the proposed FNN sliding-mode
controller
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