Decoupling Control of Single Neuron for Cascaded STATCOM

Cascaded STATCOM is a complex nonlinear system with strong coupling relationship. The most effective way of accurate control of cascaded STATCOM is to decoupling control. Due to ordinary decoupling control method hard to achieve good control performance of cascaded STATCOM, a control strategy based on the output control of cascaded STATCOM of single neuron is proposed to decouple active and reactive power completely in this paper by taking the advantage of neuron which has good learning ability and its learning ability does not rely on model features. Delta learning rules, decoupling mechanism and designing method of decoupling control strategy for single neuron is studied deeply. A cascaded STATCOM system simulation model is established based on decoupled control strategy for single neuron in the matlab/simulink, and the simulation results are given. Theoretical and simulation results show that, by comparing with the common decoupling control method, the decoupled control method based on single neuron has such advantages as fast response, no static error, high precision control and so on, which is a highly-efficient decoupled control method for cascaded STATCOM.