A learning algorithm of CMAC based on RLS
Qin T and Chen Z.H. and Zhang H.T.
Neural Processing Letters, Volume 19, Pages 49-61, 2004Abstract
Conventionally, least mean square rule which can be named CMAC-LMS is used to update the weights of CMAC. The convergence ability of CMAC-LMS is very sensitive to the learning rate. Applying recursive least squares (RLS) algorithm to update the weights of CMAC, we bring forward an algorithm named CMAC-RLS. And the convergence ability of this algorithm is proved and analyzed. Finally, the application of CMAC-RLS to control nonlinear plant is investigated. The simulation results show the good convergence performance of CMAC-RLS. The results also reveal that the proposed CMAC-PID controller can reject disturbance effectively, and control nonlinear time-varying plant adaptively.
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- @Article{,
- author = {Qin T and Chen Z.H. and Zhang H.T.},
- journal = {Neural Processing Letters},
- title = {A learning algorithm of CMAC based on RLS},
- year = {2004},
- pages = {49-61},
- volume = {19}
- }
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