Optimal Tracking Control for Robotic Manipulator using Actor-Critic Network
Yong Hu, Lingguo Cui, Senchun Chai · 2021
This paper proposed an optimal control scheme based on the actor-critic neural network(NN) for the complex mechanical manipulator system with dynamic disturbance. The actor’s goal is to optimize control behavior, while the critic’s goal is to evaluate control performance. The optimal control update law in the scheme can guarantee the system error and the weight estimation error SGUUB, and its stability and convergence are proved based on the direct Lyapunov method. Finally, the connecting rods on two degrees of freedom are tested to verify the effectiveness of the proposed optimal control scheme.