logo-polimi
Loading...
Degree programme
Show/Search Programme
Course Details
Print
Save Document
Course Details
Context
Academic Year 2023/2024
Name Dott. - MI (1380) Ingegneria dell'Informazione / Information Technology
Programme Year 1

Course Details
ID Code 061663
Course Title MODEL PREDICTIVE CONTROL
Course Type MONO-DISCIPLINARY COURSE
Credits (CFU / ECTS) 5.0
Course Description "REFERENCE AREA: SYSTEMS AND CONTROL SSD: ING-INF/04 AUTOMATICA SUBJECT AND PROGRAMME: The course describes the main properties of Model Predictive Control (MPC), the most widely used and successful control method in the process industry and nowadays also applied in distribution networks, coordination of autonomous systems, automotive, and in many other fields of application. First, the MPC basic problem formulation is introduced, along with its main properties. Also, the tools used for guaranteeing theoretical properties (i.e., recursive feasibility and convergence) are discussed in a simplified framework. Then, the most popular industrial MPC formulations will be described. Advanced problem formulations will be described in details. More specifically, we will deal with: - robust and stochastic MPC formulations, with special focus on analytic and scenario-based methods; - explicit MPC and its approximated implementations; - Hybrid MPC, to include logic constraints and integer decision variables; - economic MPC, that guarantees plant-wide optimality; - distributed and decentralized MPC implementations. Constrained optimization-based state estimation will be also considered and a prototype Moving Horizon Estimation algorithm will be presented. An overview of successful application case studies of different MPC-based algorithms will be presented. Finally, the main computational tools for MPC implementations in the linear and nonlinear setting will be presented. A dedicated computer session will be devoted to implementation details, possibly considering selected case studies."
Scientific-Disciplinary Sector (SSD) --

Details
Alphabetical group Name Teaching Assignment Details
From (included) To (excluded)
A ZZZZ Farina Marcello, Fagiano Lorenzo Mario, La Bella Alessio, Scattolini Riccardo
manifestidott v. 1.10.0 / 1.10.0
Area Servizi ICT
22/07/2024