关键词: RBF神经网络, 轨迹跟踪, 滑模控制, 三自由度球型腕

Abstract: To overcome some shortcomings of existing wrists, such as complex structure, low integration, kinematic coupling and poor ability to resist uncertain disturbance, a 3-DOF decoupling spherical wrist with independent kinematic chain and adaptive sliding mode control is proposed. The decoupling structure of double hemispheres and double universal joints is employed to guarantee compactness and flexibility of the spherical wrist. To analyze the transitive relation of the wrist, the forward and inverse kinematics and dynamics are derived. The system control model and motion transitive relation between the working space and the joint space are established, the experimental platform of the 3-DOF decoupled spherical wrist is established. A nonlinear terminal sliding surface controller and RBF neural network are employed to increase convergent speed of the system. The Lyapunov function is used to prove the stability of the control system. Simulation and experiment demonstrate that the proposed control method is insensitive to uncertain disturbance, the chattering of sliding mode system is reduced, trajectory tracking control ability is good, and higher positional accuracy is realized.

Key words: 3-DOF spherical wrist, RBF neural network, sliding mode control, trajectory tracking