Adaptive Iterative Learning Control for Complex Dynamical Networks

Abstract EN

A new adaptive iterative learning control scheme is proposed for complex dynamical networks with repetitive operation over a fixed time interval.

By designing difference type updating laws for unknown time-varying parameters and coupling strength, the state of each node in complex dynamical networks can track the reference signal.

By constructing a composite energy function, a sufficient condition of the convergence of tracking error sequence is achieved in the iteration domain.

Finally, a numerical example is given to show the effectiveness of the designed method.