Force/Position Hybrid Control of Polishing Robot Based on LNN and RBF
Aiming at the problem of parameter uncertainty and stability control in the modeling of polishing robot system,a force/position hybrid control method based on LNN and RBF was proposed.By combining LNN and RBF neural network controllers,the accu-rate dynamic model parameters of the polishing robot were obtained by learning Lagrangian on the premise of ensuring the conservation of system energy.At the same time,a force/position hybrid controller was used to meet the end position and polishing force requirements of the polishing robot,and the RBF neural network controller was used as the position controller,which was combined with the PID force controller to control the manipulator in real time.On this basis,the 2DOF polishing robot was used as the research object to simulate the end trajectory tracking and polishing force tracking of the polishing robot.The results show that the proposed Lagrangian neural network can accurately obtain the dynamics model of the polishing robot,and the RBF force/position hybrid control method can achieve good tracking and polishing effects.
万方数据
维普
