Model reference adaptive control for multi-input multi-output nonlinear systems using neural networks

This paper presents a method of MRAC (model reference adaptive control) for multi-input multi-output (MIMO) nonlinear systems using NNs (neural networks). The control input is given by the sum of the output of the NN (neural network). The NN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual MRAC. The role of the NN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.