Convergence property of relative degree-based iterative learning control in the sense of Lebesgue-p norm

A kind of relative degree-based r-th-order derivative-type iterative learning control strategy is studied for linear time-invariant systems with relative degree r. By taking advantage of the method of integration by parts and the generalized Young inequality of convolution integral, monotone convergence of the relative degree-based iterative learning control law is derived in the sense of Lebesgue-p norm. Numerical simulations are given to show the validity and effectiveness of the proposed strategy.