Set-membership identification based adaptive robust control of systems with unknown parameter bounds

Lu Lu, Bin Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, a hybrid control architecture is proposed for the adaptive robust control of a class of nonlinear systems with uncertain parameter variation ranges. Specifically, the standard set-membership description of uncertainty is adopted - the bounds of the structural approximation errors associated with the parametrized models are assumed to be known but the variation ranges of model parameters are not available or poorly known. To effectively control this class of systems, set-membership identification (SMI) is performed in discrete-time domain and a simple bound-shrinking algorithm is developed to obtain non-conservative real-time estimation of the regions where model parameters could actually be. The estimated parameter variation bounds are subsequently used to construct a continuous-time domain projection type parameter adaptation law with varying boundaries to achieve a controlled learning process. An adaptive robust control (ARC) algorithm is then synthesized to handle the effect of both parametric uncertainties and the model approximation error effectively. It is theoretically shown that in general the proposed approach achieves a guaranteed transient and steady-state output tracking performance. In addition, asymptotic output tracking can also be achieved when certain conditions hold.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Pages847-852
Number of pages6
DOIs
StatePublished - Dec 1 2009
Externally publishedYes
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
CountryChina
CityShanghai
Period12/15/0912/18/09

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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