Direct adaptive control for a class of MIMO nonlinear discrete-time systems

Abstract

This paper considers the problem of adaptive control for a class of multiple input multiple output(MIMO) nonlinear discretetime systems based on inputoutput model with unknown interconnections between subsystems. Based on the Taylor expand technology, an equivalent model in affinelike form is derived for the original nonaffine nonlinear system. Then a direct adaptive neural network(NN) controller is implemented based on the affinelike model. By finding an orthogonal matrix to tune the NN weights, the closedloop system is proven to be semiglobally uniformly ultimately bounded. The σmodification technique is used to remove the requirement of persistence excitation during the adaptation. The control performance of the closedloop system is guaranteed by suitably choosing the design parameters.