期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 61, 期 1, 页码 486-494出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2013.2240635
关键词
Adaptive control; friction compensation; motion control; neural networks (NNs); servo mechanisms
资金
- National Natural Science Foundation of China [61203066, 61273150, 60974046]
This paper proposes an adaptive control for a class of nonlinear mechanisms with guaranteed transient and steady-state performance. A performance function characterizing the convergence rate, maximum overshoot, and steady-state error is used for the output error transformation, such that stabilizing the transformed system is sufficient to achieve the tracking control of the original system with a priori prescribed performance. A continuously differentiable friction model is adopted to account for the friction nonlinearities, for which primary model parameters are online updated. A novel high-order neural network with only a scalar weight is developed to approximate unknown nonlinearities and to dramatically diminish the computational costs. Comparative experiments on a turntable servo system are included to verify the reliability and effectiveness.
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