Iterative learning control laws with full dynamics

Iterative learning control can be applied to systems that execute the same finite duration task over and over again. The distinguishing feature is the use of information from previous executions to construct the input to the next one in the sequence, including time domain information that would be non-causal in standard control systems. Many algorithms or laws have been developed for an ever increasing range of applications. This paper develops a new law which is fully dynamic, not static, when implemented. Experimental verification results are also given.