Control Horizon Selection is a method in Model Predictive Control that determines the number of future control moves optimized over the prediction horizon, distinguishing itself by specifying the subset of control actions actually parameterized and adjusted during optimization to balance performance and computational complexity.
91
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9K
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237
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109
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Publications per year
2017–2026
23
Parents
Publications
91
Generalized predictive control—Part I. The basic algorithm
D.W. Clarke, C. Mohtadi, P.S. Tuffs · Automatica · 1987 · 3.8K citations
46th IEEE conference on decision and control
2007 · 836 citations
Engineering, Electrical Engineering, Systems Engineering +10
34th IEEE Conference on Decision and Control
IEEE Control Systems · 2011 · 306 citations
Engineering, Electrical Engineering, Systems Engineering +12
1–5 of 91
Authors
237
- LG
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- LV
3
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- RE
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- DC
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- RK
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1–5 of 237
Institutions
109
University of Alberta
Edmonton, Canada
3 h-index
5 publications
614 citations
Politecnico di Milano
Milan, Italy
3 h-index
7 publications
243 citations
Science Oxford
Oxford, United Kingdom
3 h-index
5 publications
7.6K citations
University of Pavia
Pavia, Italy
2 h-index
4 publications
129 citations
Deakin University
Burwood, Australia
2 h-index
9 publications
428 citations
University of Minnesota
Minneapolis, United States
2 h-index
4 publications
230 citations
Budapest University of Technology and Economics
Budapest, Hungary
2 h-index
2 publications
24 citations
TH Köln - University of Applied Sciences
Cologne, Germany
2 h-index
4 publications
48 citations
1–8 of 109
Venues
- Automatica
8 publications · 4.3K citations
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- Control Engineering Practice
4 publications · 230 citations
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- IFAC Proceedings Volumes
3 publications · 44 citations
3
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- Journal of Process Control
3 publications · 168 citations
3
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- IEEE Control Systems
3 publications · 735 citations
3
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1–5