Efficient move blocking strategy for multiple shooting-based non-linear model predictive control

Move blocking (MB) is a widely used strategy to reduce the degrees of freedom (DoFs) of the optimal control problem (OCP) arising in receding horizon control. The size of the OCP is reduced by forcing the input variables to be constant over multiple discretisation steps. In this study, the authors f...

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Bibliographic Details
Published in:IET control theory & applications Vol. 14; no. 2; pp. 343 - 351
Main Authors: Chen, Yutao, Scarabottolo, Nicoló, Bruschetta, Mattia, Beghi, Alessandro
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 29.01.2020
Subjects:
Brief Paper
computation complexity
computational complexity
discretisation accuracy
DoFs
efficient move blocking strategy
MB schemes
multiple discretisation steps
multiple shooting‐based nonlinear model predictive control
nonlinear control systems
nonuniform grid NMPC
optimal control
optimal control problem
optimisation
prediction horizon
predictive control
receding horizon control
shooting step
warm‐start strategy
efficient move blocking strategy
warm-start strategy
optimal control problem
MB schemes
receding horizon control
shooting step
optimal control
multiple discretisation steps
optimisation
prediction horizon
computation complexity
nonlinear control systems
discretisation accuracy
DoFs
multiple shooting-based nonlinear model predictive control
nonuniform grid NMPC
predictive control
computational complexity
ISSN:1751-8644, 1751-8652
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Summary:Move blocking (MB) is a widely used strategy to reduce the degrees of freedom (DoFs) of the optimal control problem (OCP) arising in receding horizon control. The size of the OCP is reduced by forcing the input variables to be constant over multiple discretisation steps. In this study, the authors focus on developing computationally efficient MB schemes for multiple shooting-based non-linear model predictive control (NMPC). The DoFs of the OCP is reduced by introducing MB in the shooting step, resulting in a smaller but sparse OCP. Therefore, the discretisation accuracy and level of sparsity are maintained. A condensing algorithm that exploits the sparsity structure of the OCP is proposed, that allows to reduce the computation complexity of condensing from quadratic to linear in the number of discretisation nodes. As a result, active-set methods with warm-start strategy can be efficiently employed, thus allowing the use of a longer prediction horizon. A detailed comparison between the proposed scheme and the non-uniform grid NMPC is given. Effectiveness of the algorithm in reducing computational burden while maintaining optimisation accuracy and constraints fulfilment is shown by means of simulations with two different problems.
ISSN:1751-8644
1751-8652
DOI:10.1049/iet-cta.2019.0168