Model-free adaptive tensor product control for a class of nonlinear systems

This paper presents a new data driven control for a class of discrete-time multiple input and multiple output nonlinear systems which uses the principles of model-free adaptive control and the tensor product. The design of a linearization model using the notion of the tensor product overcomes reset problems in the calculation of the pseudo partial derivative and also improves control performance. The stability of the proposed method is guaranteed by theoretical analysis. Numerical simulation results and an experimental trial are presented to validate the effectiveness of the proposed approach.