| Power system operation is characterized by the random variation of load conditions, continuous change in generation schedule and network interconnections. Also, power systems are subject to different exogenous disturbances. An adaptive optimal controller is highly desirable to enhance the performance and guarantee stability under such complicated conditions.; An adaptive optimal controller, which will improve a power system's overall stability in the face of system non-linearity and external disturbances, is described in this thesis. The transfer function of the plant is estimated in real time by the Recursive Least-Squares (RLS) algorithm, and converted into its state equation. The plant states are estimated by Kalman filter. Control output is calculated by solving the Riccati algebraic equation. The applied structure enables improvement in performance from a linear controller.; A TMS320C30 Digital Signal Processor (DSP) and an ABB PHSC2 Programmable Logic Controller (PLC) were employed to develop a prototype real time digital control environment and to implement the optimal adaptive power system stabilizer.; Experimental results, which demonstrate the benefits of adapting the stabilizer parameters as the system dynamics change, ate presented in this thesis. |
