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Adaptive learning algorithm for Cerebellar model articulation controller
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DOI：10.1016/S0957-4158(01)00031-9.png)
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Abstract
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Cerebellar model articulation controller (CMAC) was developed two decades ago, yet lacks an adequate learning algorithm. Examining the performance of a CMAC based controller showed that the control system become unstable after a long period of real time runs. A new adaptive learning algorithm is proposed. The resultant controller is applied for the trajectory tracking control of a piezoelectric actuated tool post. The performance of the proposed controller is compared with those of conventional controllers (PI controller and the conventional CMAC based controller). The experimental results showed that performance of the CMAC based controller using the proposed learning algorithm is stable and more effective than that of the conventional controllers. (C) 2002 Elsevier Science Ltd. All rights reserved.
Keywords:
cerebellar model articulation controller (CMAC)
stability
neural network
adaptive learning algorithm
piezoelectric actuated tool post
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