Iterative learning control for linear time-variant continuous systems with iteration-varying initial conditions and iteration-varying reference trajectories

For non-strictly repetitive linear time-variant continuous systems, when both the iterative initial conditions and the reference trajectories are iteration-varying within a bound, we present a kind of iterative learning controller with a rectifying action to the non-strictly repetitive tracking. The proposed controller can make the output tracking error beyond the initial time interval driven to a residual set whose size depends on the estimation error of input matrix. Especially, when the input matrix is accurately known, the output tracking error beyond the initial time interval can be driven to zero.