A dual Iterative Learning Control loops for cascade systems

Iterative Learning Control (ILC) is a practical control methodology which can “learn” from the experience gained from past iterations. ILC has been widely used in many industrial repetitive processes and has shown its potential in achieving perfect tracking performance. This paper focuses on time-varying cascade systems with two sub-systems. An ILC algorithm is available for each sub-system to ensure the convergence. By connecting two ILC loops with a proper time-scale separation, the main result shows that the cascade system semi-globally practically uniformly converges to the desired trajectory. Simulation result supports the main result.