Iteration domain H_∞-optimal iterative learning controller design

This paper presents an H_∞-based design technique for the synthesis of higher-order iterative learning controllers (ILCs) for plants subject to iteration-domain input/output disturbances and plant model uncertainty. Formulating the higher-order ILC problem into a high-dimensional multivariable discrete-time system framework, it is shown how the addition of input/output disturbances and plant model uncertainty to the ILC problem can be cast as an H_∞-norm minimization problem. The distinctive feature of this formulation is to consider the uncertainty as arising in the iteration domain rather than the time domain. 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_∞ synthesis can be used for higher-order ILC design to achieve a reliable performance in the presence of iteration-varying external disturbances and model uncertainty. Copyright © 2007 John Wiley & Sons, Ltd.