An integrated model predictive control scheme with disturbance preview
This paper proposes an integrated model predictive control (MPC) framework with disturbance preview information for nonlinear systems. It is assumed that the disturbance can be previewed within the prediction horizon but unknown outside the horizon. First an integrated terminal control law consisting of both feedback and feedforward is considered. Based on that, a procedure is presented to calculate the associated terminal constraints and terminal cost. A new MPC formulation is then presented with these terminal elements and it is shown that stability and recursive feasibility can be guaranteed under the proposed design using the input-to-state stability tool. Another distinctive feature of the proposed MPC scheme is that the disturbance and the reference information in the horizon is integrated in online optimisation, rather than treating disturbance rejection and trajectory following separately, which makes it possible to make full use of the predictable disturbance if it is beneficial to the control task. Numerical examples show that this integrated MPC yields a larger stability region and better performance under prescribed disturbance in comparison with the existing MPC algorithms with disturbance preview.
Funding
Goal-Oriented Control Systems (GOCS): Disturbance, Uncertainty and Constraints
Engineering and Physical Sciences Research Council
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National Natural Science Foundation of China
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National Natural Science Foundation of China
Find out more...China Postdoctoral Science Foundation grant no. 2021M702505
111 Project grant no. B12018
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
International Journal of Robust and Nonlinear ControlPublisher
WileyVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This is an Open Access Article. It is published by Wiley under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2022-06-17Publication date
2022-07-01Copyright date
2022ISSN
1049-8923eISSN
1099-1239Publisher version
Language
- en