Dual adaptive extremum control of Hammerstein models

Simon G Fabri, Björn Wittenmark, Marvin K Bugeja

Research output: Contribution to journalArticlepeer-review

Abstract

A novel dual adaptive controller for extremum control of stochastic and uncertain nonlinear Hammerstein systems is proposed. The design is based on the innovations dual control cost function originally developed for conventional adaptive control of linear systems. However, the design process is extensively modified and developed so as to cater for the extremum control scenario. This is a more challenging problem because the reference input is itself a nonlinear function of the unknown system parameters, rather than an independent and predefined external reference signal. As in all dual adaptive schemes, it leads to a control law that balances out the need for caution, due to parameter uncertainty, with the conflicting requirement of probing that acts to quickly reduce parameter uncertainty. The proposed controller’s performance is analysed through extensive Monte Carlo simulation trials and compared with several other non-dual adaptive extremum controllers. It is shown that the novel extremum innovations dual controller is superior to other types of adaptive control systems that are based on a certainty
equivalence assumption. In addition, a novel statistical measure is introduced that yields a more objective evaluation of the Monte Carlo simulation results.
Original languageEnglish
Pages (from-to)1271-1286
JournalInternational Journal of Control
Volume88
Issue number6
DOIs
Publication statusPublished - 2015

Subject classification (UKÄ)

  • Control Engineering

Free keywords

  • dual control
  • adaptive control
  • extremum control
  • Hammerstein systems

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