期刊
IEEE-ASME TRANSACTIONS ON MECHATRONICS
卷 21, 期 3, 页码 1561-1571出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMECH.2015.2506701
关键词
Active suspension system; adaptive rule; negative stiffness structure (NSS); sliding mode control
类别
资金
- Research Fund of the University of Ulsan
- National Research Foundation of Korea [22A20130011018] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Improvement of the isolation effectiveness of the isolation system using negative stiffness structure (NSS) named system with NSS by introducing an adaptive sliding mode control algorithm is presented in this paper. The control strategy is to employ a radial basis function neural network (RBFNN) model to approximate the equivalent control effort and a self-tuning proportional-integral-derivative (PID) algorithm is used to compensate approximate error. Moreover, a fuzzy logic inference mechanism is utilized for realizing an auxiliary control law to remove completely the chattering problem on the conventional sliding mode control. Then, the Lyapunov stability theorem is utilized to figure out the adaptive laws for updating the coefficients in the RBFNN model, PID compensator, and tuning the fuzzy parameters. Finally, four experimental cases of studies are performed to evaluate the proposed control method.
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