Iterative Learning Control for Switched Systems with Sensor Saturation Constraints

To solve trajectory tracking problem of switched system with sensor saturation, an iterative learning control algorithm is proposed. The method uses actual measurement error to modify the variable on premise that rule does not change along iteration axis, but it randomly changes time axis. Moreover, by dealing saturation via diagonal matrix method, convergence strictly proved in sense λ-norm, and condition derived. can achieve complete desired finite interval under random rule, as iterations increase. simulation example verifies validity proposed algorithm.