Intelligent modeling and control for nonlinear systems with rate-dependent hysteresis |
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Authors: | JianQin Mao HaiShan Ding |
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Affiliation: | (1) School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China;(2) China Airborne Missile Academy, Luoyang, 471009, China |
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Abstract: | A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling
of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than
the existed approaches. Compared with the experiment result, the model built can well describe the hysteresis nonlinear of
the actuator for input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the
fuzzy tree model and inverse learning and special learning that are used in neural network broadly. In this approach, the
inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model is connected with the
plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line
manner. The direct inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator
by simulation. The simulation results show the correctness of the approach.
Supported by the National Natural Science Foundation of China (Grant No. 60534020), the National Basic Research Program of
China (Grant No. G2002cb312205-04), the Research Fund for the Doctoral Program of Higher Education (Grant No. 20070006060),
and the Key Subject Foundation of Beijing (Grant Nos. XK100060526, XK100060422) |
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Keywords: | nonlinear systems with rate-dependent hysteresis intelligent modeling and control fuzzy tree model T-S fuzzy model adaptive inverse control |
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