参考轨迹更新的点到点迭代学习控制算法优化及应用
Optimal algorithm and application for point to point iterative learning control via updating reference trajectory

针对受非重复扰动作用的离散线性系统的输出跟踪控制问题, 提出一种基于参考轨迹更新的点到点迭代 学习控制算法. 首先通过构建性能指标函数对控制器进行范数优化, 并给出相应的收敛性条件, 使得系统输出能够 跟踪上更新后参考轨迹处的期望点. 其次, 当系统输出端受到某批次非重复扰动的影响时, 进一步通过引入拉格朗 日乘子算法构造多目标性能指标函数, 以优化鲁棒迭代学习控制器, 达到提高收敛速度和跟踪精度的目的. 最后将 该算法应用于电机驱动的单机械臂控制系统中, 仿真结果验证了算法的合理性和有效性.
For the output tracking control problem of discrete linear system with non-repetitive disturbance, a point to point iterative learning control algorithm based on updating reference trajectory is proposed. Firstly, the iterative learning controller is optimized by constructing performance index with norm function, and the corresponding convergence conditions are given, then the system output can track with the desired points in updating reference trajectory. Furthermore, when the system output is affected by non-repetitive disturbance in some trials, a new multi-objective performance index function is constructed by Lagrange multiplier algorithm, and the robust iterative learning controller is optimized to improve the convergence speed and tracking accuracy. Finally, the simulation results of the motor driven single mechanical arm control system show the effectiveness and feasibility of the proposed algorithm.