| In a self-tuning adaptive control algorithm, parameters of a model of the plant to be controlled are identified on-line and the control action is calculated based on the identified parameters. In practice, duplicate controllers, one active and one standby, are often employed. In the case of a digital adaptive controller, because the standby unit is not tracking the system operating conditions, a sudden change over from the active unit to the standby unit can cause deterioration in control. Performance of a power system with duplicate adaptive power system stabilizer and the actions required for a smooth change over from one controller to the other are presented in this study.;Most of the present control techniques involve the optimization of one-step ahead performance index. However, the control signals have a dynamic impact on the future states of the system. Therefore, full-scale optimization is desirable. The drawback of such full-scale optimization is the computational burden attached to it. To over come this shortcoming, simplifications are proposed using the 'dynamic control limits'.;Proper system identification is one of the important factors that gives a good controller performance. This means that while the model parameter estimates are good, the controller output is good, whereas if the model parameter estimates are bad then almost surely the computed control will be bad. Proper selection of the identified system model order is also investigated. |
