A novel iterative learning control scheme based on Broyden‐class optimization method

Summary This study proposes a novel iterative learning control scheme for discrete‐time linear systems based on the Broyden‐class optimization method. To overcome the difficulty of lacking system information, a cost function is introduced for the performance index by constructing a positive‐definite matrix with little system information. An optimization‐based learning control algorithm is proposed using a Hessian matrix approximation and the generated input sequence is demonstrated to exhibit a superlinear convergence rate. The proposed scheme is extended to address the point‐to‐point tracking problem. Numerical simulations are provided to verify the effectiveness of the proposed approach.