227-0221-00L | ||
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Professor(en): M. Morari |
Betreuer: D. Sturzenegger, C. Fischer, M. Quack, R. Vujanic, J. Warrington, A. Zgraggen | |
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Vorlesung: |
Link zum Kurskatalog Spring 2013 |
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Ziele: SHORT COURSE (BLOCKKURS) ON MODEL PREDICTIVE CONTROL 6 credits, offered to diploma/master and PhD students. Undergraduate electrical engineering students can also receive credits for this course. Testat condition: Participation in all exercise sessions. Prerequisites: One semester course on automatic control, Matlab, linear algebra Date and time: 18 - 22 February 2013, 09:15-17:00 h 25 - 28 February 2013, 09:15-17:00 h Rooms: - Lectures 09:15-12:00: 18, 19, 21, 25 and 26 February: VAW B1 20 February: CAB G1 22 February: HG D 1.1 27 February: CAB G 11 - Exercises 13:15-17:00 (28 February: 10.00-17.00): ETZ D61.1/61.2 (Map of ETH buildings). Instructors: Prof. Manfred Morari Dr. Paul Goulart Alex Domahidi Location: ETH Zurich 8092 Zurich The script costs amount to roughly 20.-. Exam Written Exam: March 18 2013, 9.30-11.30 in HG E3 Office hour (for questions): March 13 14.00-15.00 in ETL K25 Allowed material: 2 sheets (4 pages) of hand- or machinewritten notes (no calculator) Last year's exam: MPC Exam 2012 Registration NOTE: THE COURSE IS FULLY BOOKED AND THE REGISTRATION IS CLOSED We have only a limited number of places in the course, it is "first come, first served"! ETH students: As participation is limited, a reservation (e-mail: bolleal@control.ee.ethz.ch) is required. Please give information on your "Studienrichtung", semester, institute, etc. After your reservation has been confirmed, please register online at www.mystudies.ethz.ch. Interested persons from outside ETH: It is not possible/needed to enrol as external auditor for this course. Please contact Alain Bolle to register for the course (bolleal@control.ee.ethz.ch). Exercise Material Exercise 1 Exercise 6 aircraft model Additional Lecture Materials New book by M. Morari, F. Borrelli and A. Bemporad on predictive control for linear and hybrid systems: Predictive Control. Note that this is a draft version and not for distribution outside ETH. A newly published report by the IEEE control systems society discusses and exemplifies the accomplishments of control technology and future opportunities for the field. IEEE IoCT Report Presentations from the invited speaker talks: Prof. Morari: Traction Control, River Power Plant, Driver Assistance Lorenzo Fagiano: Airborne Wind Energy Generation George Papafotiou: Model Predictive Direct Torque Control Summary (2013) Increased system complexity and more demanding performance requirements have rendered traditional control laws inadequate regardless if simple PID loops are considered or robust feedback controllers designed according to some H2/infinity criterion. Applications ranging from the process industries to the automotive and the communications sector are making increased use of Model Predictive Control (MPC) where a fixed control law is replaced by on-line optimization performed over a receding horizon. The advantage is that MPC can deal with almost any time-varying process and specifications, limited only by the availability of real-time computer power. In the last few years we have seen tremendous progress in this interdisciplinary area where fundamentals of systems theory, computation and optimization interact. For example, methods have emerged to handle hybrid systems, i.e. systems comprising both continuous and discrete components. Also, it is now possible to perform most of the computations off-line thus reducing the control law to a simple look-up table. The first part of the course is an overview of basic concepts of system theory and optimization, including hybrid systems and multi-parametric programming. In the second part we will show how these concepts are utilized to derive MPC algorithms and to establish their properties. On the last day, speakers from various industries will talk about a wide range of applications where MPC was used with great benefit. There will be exercise sessions throughout the course, where the students can test their understanding of the material. We will make use of the Multi-Parametric Toolbox for Matlab that is developed by the automatic control group at ETH. |
Vorlesungslevel: D-ITET Master, Systems and Control specialization Recommended Core Courses | |
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Voraussetzungen: One semester course on automatic control, Matlab, linear algebra. | ||
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Inhalt: TENTATIVE PROGRAM Day 1 - Linear Systems Theory Fundamentals of linear system theory – Review (system representations, poles, zeroes, stability, controllability & observability, stochastic system descriptions, modelling of noise). Day 2 - Optimal Control and Estimation Optimal Control and Filtering for Linear Systems (Liner Quadratic Regulator, Linear Observer, Kalman Filter, Separation Principle, Riccati Difference Equation). Days 3 & 4 - Basics on Optimization Convex sets, Polyhedra and norms. Convex functions, convex optimization problems, linear and quadratic programming. Duality theory, Lagrange dual function, KKT optimality conditions. Smooth unconstrained minimization methods (steepest descent, Newton’s method, etc.), sequential unconstrained minimization methods. Exercises. Day 5 - Introduction to MPC General formulation, finite horizon optimal control, receding horizon control, specialization to linear systems, implementations using linear and quadratic programming, stability and feasibility. Exercises. Day 6 - Explicit Solution to MPC for linear constrained systems Explicit solution to MPC for linear constrained systems. Motivation. Introduction to (multi)-parametric programming through a simple example. Multi-parametric linear and quadratic programming: geometric algorithm. Formulation of MPC for linear constrained systems as a multi-parametric linear/quadratic program. Illustrative example: double integrator. Demonstration of the performance on "ball-and-plate". A brief introduction to Multi-parametric Toolbox. Exercises. - MPC for discrete time hybrid systems MPC for discrete-time hybrid systems. Introduction to hybrid systems. Models of hybrid systems (MLD, DHA, PWA, etc.). Equivalence between different models. Modelling using HYSDEL. MLD systems. MPC based on MILP/MIQP. Explicit solution: mpMILP. Short introduction into dynamic programming (DP). Computation of the explicit MPC for PWA systems based on DP. Examples. MPT and hybrid systems: short overview of the features and demonstration. Other topics: estimation, verification. Day 7 - Numerical Methods for MPC Day 8 - Applications - Prof. Manfred Morari, ETH Zurich - Dr. George Papafotiou, ABB Schweiz - Dr. Lorenzo Fagiano, UC Santa Barbara The final list of seminars will be decided during the course. Day 9 - Design exercise (using MPC to control an aircraft model), computer tools. |
Dokumentation: Script will be handed out during the lecture. | |
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