[1]FU Xingjian,YU Shixian.Flexible plant system control based on GBF-CMAC and sliding mode control[J].CAAI Transactions on Intelligent Systems,2018,13(5):791-798.[doi:10.11992/tis.201706066]
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Flexible plant system control based on GBF-CMAC and sliding mode control

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 5 Page number: 791-798 Column: 学术论文—智能系统 Public date: 2018-09-05
Title:
Flexible plant system control based on GBF-CMAC and sliding mode control
Author(s):
FU Xingjian;  YU Shixian
School of Automation, Beijing Information Science and Technology University, Beijing 100192, China
Keywords:
Gaussian basis function; CMAC; neural network; adaptive; sliding mode control; hierarchical structure; uncertain system; flexible linear system
CLC:
TP273
DOI:
10.11992/tis.201706066
Abstract:
In this paper, a tracking control method combining cerebellar model articulation controller with Gaussian basis function (GBF-CMAC) and sliding mode control (SMC) for uncertain systems is designed. An adaptive learning algorithm of GBF-CMAC is proposed, in which a signed distance and hierarchical structure are used to reduce the memory capacity needed by the neural network. The designed controller is applied for the tracking control of high-order flexible linear system with uncertainties and under-actuated structures, and it is compared with general SMC and integral sliding mode control (ISMC). The experimental results show that the designed controller has a better robustness and improves the chattering problem of SMC. Moreover, the chattering is controlled by adjusting the parameters of the neural network to achieve the optimal choice between chattering and tracking performance.
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