Comparisons Of An Adaptive Neural Network Based Controller And An Optimized Conventional Power System Stabilizer
- 1 October 2007
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2007 IEEE International Conference on Control Applications
- No. 10851992,p. 922-927
Abstract
Power system stabilizers are widely used to damp out the low frequency oscillations in power systems. In power system control literature, there is a lack of stability analysis for proposed controller designs. This paper proposes a Neural Network (NN) based stabilizing controller design based on a sixth order single machine infinite bus power system model. The NN is used to compensate the complex nonlinear dynamics of power system. To speed up the learning process, an adaptive signal is introduced to the NN's weights updating rule. The NN can be directly used online without offline training process. Magnitude constraint of the activators is modeled as saturation nonlinearities and is included in the stability analysis. The proposed controller design is compared with Conventional Power System Stabilizers whose parameters are optimized by Particle Swarm Optimization. Simulation results demonstrate the effectiveness of the proposed controller design.Keywords
This publication has 18 references indexed in Scilit:
- Decentralized Nonlinear Adaptive Control for Multimachine Power Systems Via High-Gain Perturbation ObserverIEEE Transactions on Circuits and Systems I: Regular Papers, 2004
- Decentralized control design for large-scale systems with strong interconnections using neural networksIEEE Transactions on Automatic Control, 2003
- Particle swarm optimization for multimachine power system stabilizer design2001
- Nonlinear decentralized control of large-scale power systemsAutomatica, 2000
- Robust tuning of power system stabilizers in multimachine power systemsIEEE Transactions on Power Systems, 2000
- Toward a globally robust decentralized control for large-scale power systemsIEEE Transactions on Control Systems Technology, 1997
- Development of an advanced power system stabilizer using a strict linearization approachIEEE Transactions on Power Systems, 1996
- Stochastic choice of basis functions in adaptive function approximation and the functional-link netIEEE Transactions on Neural Networks, 1995
- Adaptive nonlinear excitation control of power systems with unknown interconnectionsIEEE Transactions on Control Systems Technology, 1994
- Universal approximation bounds for superpositions of a sigmoidal functionIEEE Transactions on Information Theory, 1993