A design of self-tuning pole-assignment controllers for stochastic systems with unknown deterministic disturbances

In this paper, a new self-tuning pole-assignment control scheme is proposed for stochastic systems with unknown deterministic disturbances, whose control law is first derived based on minimizing a quadratic cost function. Furthermore, user-specified polynomials are designed based on the pole-assignment scheme. By considering the minimization of the cost function, the variance of the control errors can be minimized. On the other hand, this scheme has internal models corresponding to deterministic disturbances, and the internal models are adjusted in an on-line manner. Inserting self-tuned internal models enables us to reduce the influence of unknown deterministic disturbances. The effectiveness of the newly proposed control scheme is evaluated on simulation examples.