Online Levenberg-Marquardt algorithm for neural network based estimation and control of power systems - Arif,J; Chaudhuri,NR; Ray,S; Chaudhuri,B (IEEE, 2009)
Levenberg-Marquardt (LM) algorithm, a powerfuloff-line batch training method for neural networks, is adaptedhere for online estimation of power system dynamic behavior.A special form of neural network compatible with the feedbacklinearization framework is used to enable non-linear self-tuningcontrol. Use of LM is shown to yield better closed-loop performancecompared to conventional recursive least square (RLS) approach.For successive disturbance use of LM in conjunction withnon-linear neural network structure yields faster convergencecompared to RLS. A case study on a test system demonstratesthe effectiveness of the online LM method for both linear andnonlinear estimation over RLS estimation (linear).