ILC for networked nonlinear systems with unknown control direction through random Lossy channel

The iterative learning control is constructed for the discrete-time networked nonlinear systems with random measurement losses and unknown control direction, which have not been studied simultaneously in literature. Differing from the conventional Bernoulli random variable model, the random packet loss is modeled by an arbitrary stochastic sequence with bounded length requirement, which is a new model of realistic packet losses. A novel regulating approach based on truncations is introduced to make the proposed algorithm find the correct control direction adaptively, and then guarantee the almost sure convergence property. Therefore, this paper has three major innovations compared with reported studies, namely, the stochastic sequence model of packet loss, the novel control direction regulation method, and the almost sure convergence property of the proposed algorithm. An illustrative example shows the effectiveness of the proposed approach.