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Nonlinear Industrial Control Systems pp 469–549Cite as

LPV/State-Dependent Nonlinear Predictive Optimal Control

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Abstract

This is the second chapter where the nonlinear plant is represented by a more general LPV or state-dependent model combined with a black-box operator term. However, in this case the model predictive control problem is considered with some enhancements including, for example, a connection matrix defining the pattern of control moves allowed in the prediction horizon. The generalized predictive controller is first considered for the plant without the operator term since this provides a simple model predictive control solution. In the later part of the chapter, the full plant model is considered and a nonlinear control weighting term is also included in the cost-function . The rotational link example considered has a natural state-dependent form and it illustrates the modelling and control design options. The final section considers the problem of restricted structure control where the aim is to use a low-order controller within the feedback loop to simplify retuning. There are several lessons since the approach is unusual, particularly regarding the improvement in robustness properties that may occur, and the way the gains vary similar to an adaptive system.

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Author information

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/State-Dependent Nonlinear Predictive Optimal Control. In: Nonlinear Industrial Control Systems. Springer, London. https://doi.org/10.1007/978-1-4471-7457-8_11

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