Abstract: An iterative learning control algorithm was proposed for linear time-invariant systems based on optimal theory. On the basis of the quadratic performance criterion, a gradient descent search method was adopted to fit the iterative learning control law. Simulation results demonstrate that the proposed algorithm has rapid convergence speed. Moreover, the actual output of the systems can track the given trajectory rapidly under less iterated times.

Key words: Optimization algorithm, Iterative learning control, Quadratic performance criterion

摘要： 针对线性时不变系统提出了一种基于优化控制理论设计的迭代学习控制算法，该算法基于二次型优化性能指标，利用梯度下降搜索法来拟合迭代学习控制律，仿真结果表明，该算法具有较快的收敛速度，且系统实际输出能够在较小的迭代次数下快速跟踪给定轨迹。

关键词: 优化算法, 迭代学习控制, 二次型性能指标