Iterative Learning Identification for Discrete Parabolic Distributed Parameter Systems

This paper presents an iterative learning identification scheme for discrete parabolic distributed parameter systems with unknown curve surface parameters. The method achieves identification through iterative learning control concepts, a P-type learning identification controller is employed to estimate the spatial-temporal varying curve surface iteratively. Then, the sufficient convergence conditions for identification error in the sense of L-2 norm has been presented through rigorous analysis. In the end, numerical simulations are shown to illustrate the effectiveness of the proposed learning identification algorithm.