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LPV and State-Dependent Nonlinear Optimal Control

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Nonlinear Industrial Control Systems

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Abstract

In this chapter, a more general modelling paradigm is introduced. That is, the linear plant subsystem used previously is replaced by a linear parameter varying or a state-dependent state-space model. Taken together with a black-box operator subsystem very general nonlinear systems may be considered. The nonlinear generalized minimum variance controller provides an obvious starting point because of its simplicity, which is valuable when the problem becomes more complex. The most important message from this chapter is that the basic solution procedure is conceptually as simple as for the linear state-space system case, even if there are subtle differences in stability analysis and implementation. The automotive engine control example at the end of the chapter illustrates the value of the control approach and also considers the plant modelling and system identification problem.

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Authors and Affiliations

  1. Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

    Michael J. Grimble

  2. Industrial Systems and Control Limited, Glasgow, UK

    Paweł Majecki

Authors
  1. Michael J. Grimble
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  2. Paweł Majecki
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Correspondence to Michael J. Grimble .

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Grimble, M.J., Majecki, P. (2020). LPV and State-Dependent Nonlinear Optimal Control. In: Nonlinear Industrial Control Systems. Springer, London. https://doi.org/10.1007/978-1-4471-7457-8_10

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