Systems Control Course Catalogue
Updated for 2012-13
ECE 557H1F Systems Control (Core Course)
Professor M.E. Broucke
Fundamentals of linear time-invariant control systems. State space modeling and control design, controllability, stabilization, pole placement controllers, observability, Kalman filters, observer design, optimal control, tracking controllers. Labs: real-time control experiments on design techniques. Course credit is not available for students who have taken ECE 410. Prerequisite: ECE356.
ECE 1617H Large Scale System Theory and Control I
Professor E.J. Davison
This course is an introduction to the control of large scale systems: decentralized fixed mode characterization/computation, interconnected systems, decentralized control, decentralized pole assignment, decentralized robust servomechanism problem, expanding system control problem. Prerequisites: ECE 410/411 or 557.
ECE1619H Linear Geometric Control Theory
Professor M.E. Broucke
The course presents a more advanced treatment of linear control theory via the geometric approach. The coverage roughly corresponds to the first six chapters of “Linear Multivariable Control: A Geometric Approach”, by W.M. Wonham. We adopt the abstract algebra approach of the text to study controllability, observability, controlled invariant subspaces, controllability subspaces, and controllability indices. These concepts are applied to solve the problems of stabilization, output stabilization, disturbance decoupling, and the restricted regulator problem. Areas of current research in linear geometric control will also be discussed.
Prerequisite: ECE410 or ECE557 or an equivalent State Space Control course.
ECE 1635H Special Topics in Control I: Modern Control Methodology: Case Studies in Practical Control
Professor J. Apkarian
This is a project based course involving mathematical modeling, real-time systems, control design, hardware in the loop simulations and VR simulations as applied to real-world industry control problems. The course will cover the following: modelling and control design, integration and testing using supplied VR simulator, hardware experiments to validate models and controllers, implementation of complete simulation solutions using real hardware and 3D simulation environment in the lab. This term’s offering will focus on automotive controls.
Please note: enrolment limited to 20 students
ECE 1636H Control of Discrete Event Systems I
Professor W.M. Wonham
This course is an introduction to the control of discrete, asynchronous, nondeterministic systems like manufacturing systems, traffic systems, and certain communication systems. Architectural issues (modular, decentralized and hierarchical control) are emphasized. The theory is developed in an elementary framework of automata and formal languages, and is supported by a software package for creating applications. There are no special prerequisites.
ECE 1637H Control of Discrete Event Systems II
Professor W.M. Wonham
This course is a continuation of ECE 1636H, and is conducted on a seminar basis. Participants will present and discuss articles in the current literature, and complete a project that could lead into graduate research in the discrete-event system area. Topics recently examined include controlled Petri nets, min-max algebra, real-time control via timed-transition-models (TTMs), recursive process algebras, and state charts. Prerequisite: ECE1636.
ECE 1639H Analysis and Control of Stochastic Systems I
Professor R.H. Kwong
This is the first course of a two-term sequence on stochastic systems designed to cover some of the basic results on estimation, identification, stochastic control and adaptive control. Topics include: stochastic processes and their descriptions, analysis of linear systems with random inputs; prediction and filtering theory: prediction for ARMAX systems, the Kalman filter and the Riccati equation; stochastic control methods based on dynamic programming; the LQG problem and the separation theorem; minimum variance control.
ECE 1640H Analysis and Control of Stochastic Systems II
Professor R.H. Kwong
This course is the continuation of ECE 1639H. Topics include: parameter estimation theory for parametric models: least squares and maximum likelihood estimators; offline identification methods for linear systems; identifiability, convergence, and consistency; recursive methods for system identification; introduction to convergence analysis of recursive schemes using the ordinary differential equation method and the martingale method. Adaptive control of stochastic systems: self-tuning regulators, direct adaptive control schemes, stability and convergence analysis using martingale theory. Prerequisite: ECE1639.
ECE 1641H Multivariable Control Design
Professor B.A. Francis
Design techniques for linear multivariable systems. State variable and transfer matrix models; performance measures in terms of norms of signals and systems; design by optimization; uncertainty models, including structured uncertainty; stability and performance robustness; design by synthesis. Students do a major design project using MATLAB and µ -Tools. Prerequisites: ECE 410/411 or 557.
ECE 1643H Special Topics in Control II: Game Theory and Evolutionary Games
Professor L. Pavel
This course presents a mathematical treatment of classical and evolutionary game theory. Topics covered in classical game theory: matrix games, continuous games, Nash equilibrium (NE) solution, existence and uniqueness, Stackelberg solution, Pareto optimal solution. Topics covered in evolutionary games: replicator dynamics, evolutionary stable strategy (ESS) concept, NE versus ESS, population (frequency) dynamics, adaptation (strategy) dynamics, stability concepts and relation to dynamic asymptotic stability. The two areas will be connected by learning in games via imitation dynamics, fictitious play and their relation to replicator dynamics. Engineering applications to communication networks, multi-agent learning, network formation will be discussed.
Prerequisites: ECE410 or ECE557 or equivalent.
ECE 1644H Large Scale System Theory and Control II
Professor E.J. Davison
This course is a continuation of ECE 1617H: model reduction problem, approximate decentralized fixed modes, decentralized control of descriptor systems, robust control, optimal decentralized control, computer-aided design, case studies - traffic light control, control of flexible space structures, building temperature control, load and frequency power control. Prerequisites: ECE 1617.
ECE 1646H Digital Control
Professor B.A. Francis
An advanced course on digital control. Topics: sample-and-hold; discretization of analog systems; discrete-time systems analysis and design; simulation; effects of sampling on controllability and observability; internal stability; digital loop-shaping; induced norms; L1, H2, and H¥
optimization; multirate systems. Prerequisites: ECE 410/411 or 557.
ECE1647H Introduction to Nonlinear Control Systems (Core Course)
Professor M. Maggiore
- Dynamics: Finite dimensional phase flows and their relationship to vector fields. Continuity and differentiability. Existence and uniqueness of solutions of ODEs. Stable and unstable manifolds, and structural stability.
- Stability Theory: Stability definitions. Lyapunov theorems for autonomous systems. Invariance and LaSalle’s invariance principle for autonomous systems. Control design using Lyapunov functions.
- Passivity-based stabilization: Passive systems. Detectability and stabilization.
- Applications: Research examples illustrating the design approaches.
ECE1648H Nonlinear Control Systems
Professor M. Maggiore
This course is a continuation of ECE1647F. It covers the design and analysis of nonlinear control systems from a geometric perspective, with emphasis on properties of the system that do not change under coordinate transformations. Frequent references to linear system theory and linear geometric methods are made. A detailed list of topics will be posted on the course website (http://www.control.utoronto.ca/~maggiore/) before the course starts. Prerequisites to take this course are ECE1647F and ECE557 (or an advanced linear systems course).
ECE 1649H Adaptive Control
Professor M. Maggiore
Course is a state-of-the art presentation of adaptive control from a deterministic (versus stochastic) viewpoint. Control of linear, time-invariant, continuous-time plants with unknown parameters is emphasized, although straightforward extensions to linearly parameterized nonlinear plants are explored. Stability is analyzed rigorously. Measures to improve robustness are presented. Examples are drawn from robotics, mechanics, process control, etc.
ECE 1651H Adaptive Signal Processing and Control
Professor R.H. Kwong
This course provides an introduction to the theory and applications of adaptive signal processing and control. Topics include: the structure of adaptive algorithms, performance surfaces; the LMS algorithm in adaptive signal processing, adaptive IIR filters; applications to echo cancellation, noise cancellation, channel equalization, etc.; model reference adaptive control systems, adaptive stabilization robustness issues, stochastic adaptive control; applications to process control. Prerequisites: Linear Systems and Signal Processing (e.g. ECE 310/311 or ECE 355/356), and Probability and Stochastic Processes (e.g. ECE 302).
ECE 1652H Stochastic Processes with Applications
Professor R.H. Kwong
Review of probability. Definition and examples of stochastic processes. Markov chains and applications, introduction to queueing. Renewal processes, generalized semi-Markov processes, stochastic discrete event systems. Introduction to dynamic programming and optimization applications. Stationary processes, spectral analysis and linear systems, state space models. Introduction to estimation and filtering. Prerequisites: Linear systems and signal processing (e.g. ECE 310/311 or ECE 355/356), undergraduate course on probability theory (e.g., ECE 302).
ECE 1653H Hybrid Systems and Control Applications
Professor M. Broucke
This course concerns hybrid control systems, which are control systems combining both discrete event and continuous time behavior. The course topics represent areas of recent research activities in this field. Topics include: theoretical and practical motivations for hybrid control systems; modeling; zeno phenomena; stability analysis; controllability; reachability analysis; synthesis of controllers for reachability specifications; and non-smooth analysis and its role in the stabilization problem. Applications are drawn from multi-agent systems and nonlinear control.
Prerequisites: ECE410 or ECE557 or equivalent.
ECE 1654H Optical Networks: A Systems Control Perspective
Professor L. Pavel
Topics in system control for communication networks, specifically optical networks. This is an interdisciplinary research direction emerging in the context of re-configurable, dynamic networks. Topics include: dynamics and control of network elements: optical amplifiers, dynamic filters; adaptive filters concepts (LMS algorithm); stability of interconnected systems (time-scale decomposition); robust stability concepts (H-infinity control, small gain theorem); network modeling as time-delay system; stability analysis via robust control; end-to-end network control: wireless, optical and congestion control examples; network control based on SNR optimization (decentralized iterative algorithms); introduction to game theory concepts.
ECE 1655H Optimal Control
Professor B.A. Francis
This is a graduate course on optimal control. The pre-requisite is an undergraduate course on state-space control systems, such as ECE557.
For more information, please go to: http://sites.google.com/site/ece1655/
ECE1656H Nonlinear Modeling and Analysis of Biological Systems
Professor L. Scardovi
This course studies dynamical models used in biology and introduces the nonlinear dynamics tools necessary for their analysis. The first part reviews basic nonlinear dynamics concepts with illustrations on biological models like population growth and logistic models. The second part focuses on biochemical reactions and genetic regulation while the third part reviews and analyzes basic neuronal models. The last part of the course introduces specific nonlinear systems concepts (such as passivity, monotonicity, cooperativity) for the quantitative study of biological networked systems (such as biochemical reaction networks and neuron populations). Selected topics will be covered independently via small research projects or paper reading and presented in workshop style meetings.
