Analogue implementation of a neural network controller for UPS inverter applications

Xiao Sun, Martin H L Chow, Hung Fat Frank Leung, Dehong Xu, Yousheng Wang, Yim Shu Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)


An analogue neural-network controller for UPS inverter applications is presented. The proposed neural-network controller is trained off-line using patterns obtained from a simulated controller, which had an idealized load-current-reference. Simulation results show that the proposed neural-network controller can achieve low total harmonic distortion under nonlinear loading condition and good dynamic responses under transient loading condition. To verify the performance of the proposed NN controller, a hardware inverter with an analogue neural network (NN) controller (using mainly operational amplifiers and resistors) is built. Additionally, for comparison purposes, a PI controller with optimized parameters is built. Experimental results confirm the simulation results and show the superior performance of the NN controller especially under rectifier-type loading condition. Implementing the analogue neural-network controller using programmable integrated circuits is also discussed.
Original languageEnglish
Pages (from-to)305-313
Number of pages9
JournalIEEE Transactions on Power Electronics
Issue number3
Publication statusPublished - 1 May 2002


  • Neural network control
  • UPS inverter

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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