Improved robust control of nonlinear stochastic systems using uncertain models

Randa Herzallah, David Lowe

Research output: Chapter in Book/Published conference outputConference publication

Abstract

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear stochastic control systems. The approach is suboptimal though robust and relies upon the approximation of the forward and inverse plant models by neural networks, which also estimate the intrinsic uncertainty. Sampling from the resulting Gaussian distributions of the inversion based neurocontroller allows us to introduce a control law which is demonstrably more robust than traditional adaptive controllers.
Original languageEnglish
Title of host publicationProceedings of CONTOLO 2002
Subtitle of host publication5th Portuguese conference on automatic control
Pages507-512
Number of pages6
Publication statusPublished - Sep 2002
Event5th Portuguese Conference on Automatic Control - Aveiro, Portugal
Duration: 5 Sep 20027 Sep 2002

Conference

Conference5th Portuguese Conference on Automatic Control
Abbreviated titleControlo 2002
CountryPortugal
CityAveiro
Period5/09/027/09/02

Keywords

  • uncertainity
  • Neural Networks
  • Stochastic Systems
  • error bar
  • Distribution modelling

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