Application of improved adaptive controllers to a plant with jumps in parameters

The application of modern adaptive control theory to an electrical engineering system is considered. An adaptive dual pole-placement controller and an adaptive dual linear quadratic Gaussian (LQG) controller are designed and applied to speed control of a thyristor-driven DC motor. The DC motor considered is a plant with parameters jumps. The suggested synthesis approach is based on bicriteria optimization of two cost functions. The adaptation algorithms include the detection of the parameter jumps and restarting of the adaptation. The LQG-controller is obtained using spectral factorization and pole positioning which corresponds to the optimum of the cost function of the LQG-controller. The designed controllers are applied to the speed control problem of a thyristor-driven DC-motor. The described applications demonstrate the superiorities of the designed controllers over the standard ones based on the certainty equivalence approach.