单连杆柔性关节机械臂系统的优化反步跟踪控制OA

In this paper,an optimized backstepping tracking control method based on a reinforcement learning strategy is proposed for a single-link flexible-joint robotic arm system.Firstly,the actor-critic ar-chitecture is employed at each backstepping step to implement the reinforcement learning strategy,thereby obtaining the optimal virtual controller for each subsystem and ultimately deriving the system's optimal controller.Then,based on the defined Lyapunov function,it is demonstrated that all signals of the single-link flexible-joint robotic arm system are bounded,proving the stability of the designed control method.Finally,simulation experiments verify the effectiveness of the optimized backstepping tracking control based on reinforcement learning strategy in a single-link flexible-joint robotic arm system.