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针对一类存在随机输入状态扰动、输出扰动及系统初值与给定期望值不严格一致的离散非线性重复系统,提出了一种P型开闭环鲁棒迭代学习轨迹跟踪控制算法.基于λ范数理论证明了算法的严格鲁棒稳定性,并通过多目标函数性能指标优化P型开闭环迭代学习控制律的增益矩阵参数,保证了优化算法下系统输出期望轨迹跟踪误差的单调收敛性,达到提高学习算法收敛速度和跟踪精度的目的.最后应用于二维运动移动机器人的实例仿真,验证了本文算法的可行性和有效性.
For a class of discrete nonlinear repetitive systems with stochastic input state perturbations, output perturbations and initial values and given expectation values, a P-type closed-loop robust iterative learning trajectory tracking control algorithm is proposed. Based on λ norm The theory proves the robust robustness of the algorithm and optimizes the gain matrix parameters of P-type closed-loop iterative learning control law through the multi-objective function performance index to ensure the monotonic convergence of the tracking error of the expected output of the system under the optimized algorithm, Learning algorithm convergence speed and tracking accuracy.Finally, this method is applied to the case simulation of two-dimensional mobile robot to verify the feasibility and effectiveness of the proposed algorithm.