Iterative learning control for distributed parameter systems based on non-collocated sensors and actuators

In this paper, an open-loop PD-type iterative learning control ( ILC ) scheme is first proposed for two kinds of distributed parameter systems ( DPSs ) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained in the sense of the λ -norm. Finally, one numerical example for a distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.