A Mutation Co-evolution Clone Algorithm-Based Dynamic Recurrent Neural Network for Decoupling Control of Parallel Manipulator

Parallel manipulator is very complicate nonlinear, Strong coupling system. In this work, a decoupling controller was presented for parallel manipulator based on an improved dynamic recurrent neural network (IDRNN). IDRNN was trained by a mutation co-evolution clone algorithm. Finally, the control performance of the proposed control approach is illustrated through the comparison studies with robot tracking control approach.