Disturbance rejection using self-tuning ARMARKOV adaptive control with simultaneous identification

We perform numerical experiments involving the ARMARKOV adaptive control (AAC) algorithm with simultaneous identification. The performance of the algorithm is considered under a diverse set of conditions representing plant and disturbance uncertainty. A supervisory controller was devised to make higher level control decisions for simultaneous operation of control and identification. The numerical study shows that the AAC algorithm is able to reject unknown disturbances without any prior knowledge of the plant and is able to stabilize the plant under extreme destabilizing conditions. Experimental implementation of the algorithm validates the numerical results