Multiple models direct adaptive controller for a stochastic non-minimum phase system

For a stochastic non-minimum phase multivariable system, a multiple models direct adaptive controller is presented. It is composed of multiple fixed models with two adaptive models. The fixed models are used to cover the region where the system parameters jump and improve the transient response, while another two adaptive models are used to guarantee the stability. Utilizing generalized minimum variance design method, it adopts the stochastic system estimation algorithm with optimal controller design method to identify the controller parameter directly. Finally, the global convergence is given. The simulation proves the effectives of the controller proposed.