Adaptive disturbance accommodating controller for uncertain stochastic systems

This paper presents a Kalman filter-based adaptive disturbance-accommodating stochastic control scheme for linear uncertain systems to minimize the adverse effects of both model uncertainties and external disturbances. A rigorous stochastic stability analysis reveals a lower bound requirement on system process noise covariance to ensure the stability of the controlled system when the nominal control action on the true plant is unstable. Finally, an adaptive law is synthesized for the selection of stabilizing system process noise covariance. Simulation results are presented where the proposed control scheme is implemented on a two degree-of-freedom helicopter.