Title :
Decentralized Steam-Valving Adaptive Neural Control of Multi-machine Power Systems
Author :
Xiurong Zhong ; Cong Wang ; Yuelong Liu
Author_Institution :
Control & Optimization Center & Coll. of Autom., South China Univ. of Technol., Guangzhou, China
Abstract :
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.
Keywords :
adaptive control; closed loop systems; machine control; neurocontrollers; power system control; power system interconnection; backstepping technique; closed-loop system; coupling problem; interconnected subsystem; machine power system; multimachine power systems; steam-valving adaptive neural control; Adaptive control; Control systems; Power system control; Power system modeling; Power system simulation; Power system stability; Power system transients; Power systems; Programmable control; Turbines; Adaptive neural control; backstepping; multimachine power systems; steam-valving control;
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
DOI :
10.1109/CHICC.2006.280532
