Min Max control of nonlinear systems using Universal Learning Networks

Hongping Chen, Kotaro Hirasawa, Jinglu Hu, Junichi Murata

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)


A Min Max 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 a obtained controller has better performance than the conventional methods.

Original languageEnglish
Number of pages6
Publication statusPublished - 2000
EventInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
Duration: Jul 24 2000Jul 27 2000


OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence


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