Move blocking strategies in receding horizon control
By Raphael Cagienard, Pascal Grieder, Eric C. Kerrigan, Manfred Morari. IEEE Conference on Decision and Control, 2004
368 citations recorded by the source corpus.
In order to deal with the computational burden of optimal control, it is common practice to reduce the degrees of freedom by fixing the input or its derivatives to be constant over several time-steps. This policy is referred to as "move blocking". This paper addresses two issues. First, a survey of various move blocking strategies is presented and the shortcomings of these blocking policies, such as the lack of stability and constraint satisfaction guarantees, are illustrated. Second, a novel move blocking scheme, "moving window blocking" (MWB), is presented. In MWB, the blocking strategy is time-dependent such that the scheme yields stability and feasibility guarantees for the closed-loop system. Finally, the results of a large case-study are presented that illustrate the advantages and drawbacks of the various control strategies discussed in this paper.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/60ea3aee7eba1de28c0da3fb3fb6ce2e56e5c702
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In Control and Systems Engineering
- Alberto Bemporad
- Manfred Morari
- Francesco Borrelli
- Stephen P. Boyd
- Yang Wang
- Colin Neil Jones
- Dirk Abel
- Thomas Bergs
Citations in the corpus
- Review on model predictive control: an engineering perspective (2021, background): “One way to overcome this is to adapt the fixed time steps, such that the degree of freedom is defined at the same time [16].”
- Fast Model Predictive Control Using Online Optimization (2010, methodology): “This technique is often combined with a strategy known as move blocking, where the input is assumed to be constant for fixed portions of the horizon, and so the number of optimization variables is further reduced (see, e.g., [5] and [6]).”
- Computational Complexity Certification for Real-Time MPC With Input Constraints Based on the Fast Gradient Method (2012, background): “Note that alternative optimization-based approaches exist that either change the problem formulation by introducing conservatism or simplifying assumptions [31]–[34] or that look for an approximate solution to the original problem only [35].”
- Predictive Control for Linear and Hybrid Systems (2017, methodology): “By choosing the blocking strategies carefully, the available RHC stability results remain applicable [72].”