Iterative learning control (ILC) is a popular design methodology to achieve high performance trajectory tracking of systems operating in a repetitive manner. This paper further extends the applicability of ILC by showing that ILC can solve a more general problem of optimising some system performance for which trajectory tracking is just a special case. The problem is formulated in a general Hilbert space setting using system operators and a gradient based algorithm is proposed as a solution. The algorithm's convergence and robustness properties are analysed in detail and numerical simulations are provided to demonstrate the effectiveness of the proposed method.
['Bing Chu']
Iterative learning control for performance optimisation