Minimax control of nonlinear systems using Universal Learning Networks

Hongping Chen, Kotaro Hirasawa, Jinglu Hu, Junichi Murata

Research output: Contribution to journalArticlepeer-review


A Minimax robust control method is proposed for nonlinear systems based on the use of the higher order derivatives calculation of Universal Learning Networks (ULNs). An extended criterion function containing sensitivity terms is considered for controller design and the criterion function is evaluated at several specific operating points corresponding to certain system parameters. The ULNs learning is then performed in such a way that, at each step, it minimizes the worst criterion function among several operating points. It is found that the proposed control method is less time-consuming in the ULNs learning and obtained controller has better performance than the conventional methods.

Original languageEnglish
Pages (from-to)51-56
Number of pages6
JournalResearch Reports on Information Science and Electrical Engineering of Kyushu University
Issue number1
Publication statusPublished - Mar 2000

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


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