有约束的机械臂高精度轨迹跟踪增量模型预测控制OA

To address the control accuracy issues of robot manipulator end-effector positioning in task space with constraints on joint angles and angular velocities,an Incremental Model Predictive Control(IMPC)strategy is proposed based on traditional Model Predictive Control(MPC).Firstly,the complex nonlinear kinematic equations are approximated as a linear incremental system to simplify state prediction calculations.Secondly,a stage cost function is defined with the objective of minimizing trajectory tracking errors,and an optimal control problem(OCP)is formulated by integrating input and state constraints,thereby completing the design of the IMPC method.Finally,a simulation model of a 3-DOF robot manipulator is constructed,and comparative experiments with traditional MPC are conducted.The results demonstrate that the tracking accuracy of the IMPC method is significantly improved,with the maximum error in the X-direction reduced by 0.0068 m and in the Y-direction by 0.0075 m.The proposed method effectively handles input and state constraints,achieving high-precision trajectory tracking,and can serve as a reference for designing controllers for robot manipulators requiring high-precision operation under constrained conditions.