Decentralized Steam-Valving Adaptive Neural Control of Multi-machine Power Systems

In this paper, an adaptive neural control scheme is proposed for multi-machine steam-valving power systems. The multi-machine steam-valving power systems consist of interconnected subsystems, with coupling in the form of unknown nonlinearities and parametric uncertainties. Using the adaptive neural control method by S. S. Ge and Cong Wang, A (2004), the coupling problem between subsystems can be solved without linearization treatment. Semi-global ultimate boundedness of all the signals in the closed-loop system are obtained. The outputs of the closed-loop system are proven to converge to a small neighborhood of the desired trajectories. Simulation results of two-machine power systems are presented as an example to show the effectiveness of the approach.