Neural PID adaptive generator excitation control for two-machine system

With the rapid development of microgrids, generator excitation control for multi-machine systems to improve the stability of power systems has become a key technical problem. This paper presents an excitation controller design for a typical two-machine system. According to the characteristics of strong nonlinearity, load disturbance and time-varying uncertainty, conventional PID control schemes cannot meet the high quality requirement of excitation control for two- machine systems. A Resource Allocation Network (RAN) based neural PID adaptive generator excitation control is proposed for two-machine systems. The parameters of the PID controller can be adjusted dynamically according to the RAN-enabled online model. The validity of the proposed control strategy is demonstrated by the simulation results.