AN AUTOMATIC VOLTAGE REGULATOR USING IDENTIFIED MODELS

This paper obtains the mathematical model of a single machine infinite bus power system using the idea of parameter identifications. Because the noise is considered in parameter identification process, the model reflects the real system more exactly. On the base of the identified model this paper also presents a discrete automatic voltage regulator by minimum variance control principles. In order to avoid the static error, we combine discrete minimum variance control with continuous integral control and get very satisfactory effects. This proposed control strategy is very easy to realize. The simulation results show that in every case the dynamic qualities of the proposed control strategy are incomparably superior to that of the conventional PI regulator, which means the proposed control strategy has great practical values.     

DECENTRALIZED LOAD FREQUENCY CONTROL OF HYDROTHERMAL POWER SYSTEM

The decentralized load frequency control (LFC) of hydrothermal power system is designed with overlapping information set. The conflicts among the generation regulation constraint (GRC) ,the process of reheat steam turbines,the governor dead-band effects,and the dynamic response of LFC have been coordinated.     

A SELF-TUNING CONTROL FOR A PARALLEL AC/DC POWER SYSTEM

Based on a non-linear system model, an adaptive control methodology is presented for a parallel AC/DC power system by means of on-line recursive parameter identifications. Taking the advantage of rapid power regulatiing ability of the DC power system and combining with the generalized minimum variance self-tuning control principles, the dynamic qualities of the controlled system has been greatly improved. Using SISO form makes the control system very simple to implement. Through the design, simulation and analysis of the self-tuning control system for a practical example, it shows that the self-tuning control strategy is very promising for AC/DC power systems.     

The Adaptive Robust Control Based On Synthetical Algorithm

An adaptive robust control based on synthetical algorithm was presented in this paper. The main character is to put the expert knowledge into parameter identification to realize the robust estimation, and combine the generalised minimum variance control with the pole assignment control for improving the robustness of the controller. Numerical simulation has proved that the control scheme suggested by authors quite prevailed over the general adaptive controller in control effects.