Neural networked based synchronized control for multiple robotic manipulators

A novel neural networked based synchronized control approach is developed for multiple robotic manipulators systems (MRMS). An adaptive neural network scheme is used to compensate manipulators modeling uncertainty. The corresponding stability analysis is presented in light of Lyapunov method. Finally, an illustrative example is conducted to validate the proposed approach.