基于故障观测器的机器人多关节手臂最优容错控制OA北大核心CSTPCD

Aimming at the issue of control accuracy affected by malfunctions such as jamming,saturation and damage that are prone to occur in robot multi-joint manipulator,an optimal fault-tolerant control law was proposed using the designed fault observ-er.Firstly,a fault model of the robot multi-joint manipulator was established based on the relationship between the spatial posi-tion of the end of the robot multi-joint manipulator and the rotation angle of each joint.Then,the tracking errors of the multi-joint manipulator rotation angle and contact force were defined,and the fault observer was designed.The model parameters were esti-mated by the introduced RBF neural network.Finally,performance index matrix of robot multi-joint manipulator with the tracking error of position/contact force and faults was established according to the idea of dynamic programming,and the fault-tolerant control law including Hamiltonian equation was designed.The RBF neural network was used to solve the optimal performance in-dex,so as to obtain the optimal fault-tolerant control law.The simulation results show that the designed optimal fault-tolerant con-trol law can overcome the influence of various faults,the maximum error of fault estimation is only 0.09 N·m,the maximum er-ror of position tracking is only 0.14 cm,and the maximum error of contact force control is only 0.18 N,which verifies the feasi-bility of the designed method.The measured results of the six degrees of freedom multi-joint manipulator show that the maximum error of positioning on 8 spatial coordinates is only 0.17 cm,and the maximum error of the contact force is only 0.22 N,which verifies that the designed optimal fault-tolerant control law has superior engineering practicability.