Dynamic control of a parallel link manipulator using CMAC neural network

A multiple neural network structure called cascaded CMAC (Cerebella Model Arithmetic Computer) is proposed for solving the problem of dynamic control of a parallel-link manipulator. The cascaded CMAC networks can provide faster learning capability and the ability to capture both general trends and fine details of an unknown nonlinear mapping. Simulation results are given.<
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