Application of a general learning algorithm to the control of robotic manipulators
International Journal of Robotics Research
CMAC with general basis functions
Neural Networks
Learning Convergence of CMAC Algorithm
Neural Processing Letters
Learning convergence of CMAC technique
IEEE Transactions on Neural Networks
Continuous CMAC-QRLS and Its Systolic Array
Neural Processing Letters
Hi-index | 0.00 |
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.