Algebraic $H_infty$ Design of Higher-Order Iterative Learning Controllers

This paper presents an H_infin-based design technique for synthesis of higher-order iterative learning controllers (ILC) for plants subject to iteration-domain input/output disturbances and plant model uncertainty. Using a formulation of the higher-order ILC problem into a high-dimensional MIMO discrete-time system, it is shown how the addition of input/output disturbances and plant model uncertainty to the ILC problem can be cast into a standard H_infin framework. An algebraic approach to solving the problem in this framework is presented, resulting in a sub-optimal controller that can achieve both stability and robust performance. The key observation is that H_infin synthesis can be used for higher-order ILC design to achieve reliable performance in the presence of iteration-varying external disturbances and model uncertainty