2010/03/15 by Dario Bauso, Bauso, Dario
Engineering · Mathematics · #49M37 #Advanced Control Systems Optimization #Control Systems and Identification #Dynamical Systems (math.DS) #FOS: Mathematics #Fault Detection and Control Systems #Optimization and Control (math.OC) #math.DS #math.OC #msc:49M37
paper · pdf · doi:10.48550/arxiv.1003.2889
arxiv created 2010/03/15 · openalex publication_date 2010/03/15 · arxiv updated 2010/03/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Mixed integer predictive control deals with optimizing integer and real control variables over a receding horizon. The mixed integer nature of controls might be a cause of intractability for instances of larger dimensions. To tackle this little issue, we propose a decomposition method which turns the original n-dimensional problem into n indipendent scalar problems of lot sizing form. Each scalar problem is then reformulated as a shortest path one and solved through linear programming over a receding horizon. This last reformulation step mirrors a standard procedure in mixed integer programming. The approximation introduced by the decomposition can be lowered if we operate in accordance with the predictive control technique: i) optimize controls over the horizon ii) apply the first control iii) provide measurement updates of other states and repeat the procedure.