ℋ℞ based disturbance attenuation for iterative learning control

Abstract

Previous research has shown that repetitive processes, a class of 2D systems, can be used to design linear model based iterative learning control laws for convergence and transient performance, with supporting experimental benchmarking. In many applications attenuation of disturbances acting on the plant signals will also be required. The new results in this paper are control law design algorithms for this problem with disturbance attenuation measured by an ℋ∞ norm.