University of Utah                               

Department of Electrical & Computer Engineering

ECE 6570                                  Adaptive Control                         Spring 2014

 

Instructor:                   Professor Marc Bodson

Office:                        MEB 3268, Tel.: 581-8590

E-mail:                        bodson@eng.utah.edu

Class:                          MW 1:25PM-2:45PM, WBB 617

Class web page:          http://www.ece.utah.edu/~bodson/6570/

Please consult the class web page regularly for information on due dates and other items.

 

1.       Introduction

The concept of adaptation in control is appealing and many applications have been studied. In aerospace, adaptive control has been proposed to account for changes in the dynamics of flight vehicles, due to variations in altitude and velocity. In process control, it has been used to compensate for deviations due to aging and varying set points. In robotics, adaptation is helpful to control manipulators with unknown loads or changing configurations.

 

2.       Course Objectives

The course has two main objectives:

·       to provide a knowledge of existing algorithms for adaptive control, with a basic understanding of how to implement them;

·       to provide the theoretical foundations of the field and to introduce the student to research in adaptive control.

 The theory of adaptive control systems is challenging, due to their nonlinear, time-varying nature. However, the theory is necessary to understand the dynamic properties of adaptive systems. The two objectives are therefore complementary, and we will keep a balance between methodologies for adaptive control (algorithms), and analytical methods and results.

 

3.       Course Contents     

Introduction: Basic approaches to adaptive control. Applications of adaptive control.

Gradient and least-squares algorithms: Linear error equation. Gradient and normalized gradient algorithms. Least-squares algorithms (batch, recursive, recursive with forgetting factor). Convergence properties.

Identification: Identification of linear time-invariant systems. Adaptive observers. Sufficient richness condition for parameter convergence. Equation error and output error methods.

Indirect adaptive control: Pole placement adaptive control. Model reference adaptive control. Predictive control. Singularity regions and methods to avoid them.

Direct adaptive control: Filtered linear error equation. Gradient and pseudo-gradient algorithms. Strictly positive real transfer functions and Kalman-Yacubovitch-Popov lemma. Lyapunov redesign. Passivity theory. Direct model reference adaptive control.

Frequency-domain analysis and averaging approximations: Averaging of signals. Averaging theory for one-time scale and two-time scale systems. Applications to adaptive systems.

 

4.       Prerequisites

ECE 3510: Introduction to Feedback Systems. A course on state-space control methods (such as ME EN 5210 or 6210) is also recommended, but not required.

 

5.       Textbook

Course notes will be available for purchase at the University’s bookstore by the first week of classes.

 

6.       Recommended Books

K.J. Astrom and B. Wittenmark, Adaptive Control, Addison-Wesley, 2nd edition, 1995.

G.C. Goodwin and K.S. Sin, Adaptive Filtering, Prediction, and Control, Prentice-Hall, 1984.

P. Ioannou & B. Fidan, Adaptive Control Tutorial, SIAM, Philadelpia, PA, 2006.

P.A. Ioannou & J. Sun, Robust Adaptive Control, Prentice Hall, Upper Saddle River, NJ, 1996. The book is available (for free) in PDF form through the web page: http://www-bcf.usc.edu/~ioannou/RobustAdaptiveBook95pdf/Robust_Adaptive_Control.pdf.

I.D. Landau, R. Lozano, and M. M'Saad, Adaptive Control, Springer Verlag, London, 1998.

K.S. Narendra and A.M. Annaswamy, Stable Adaptive Systems, Prentice-Hall, 1989.

S. Sastry and M. Bodson, Adaptive Control: Stability, Convergence, and Robustness, Prentice-Hall, 1989. The book is available (for free) in PDF form through the web page: http://www.ece.utah.edu/~bodson/acscr. Also republished by Dover Publications, 2011.

P.E. Wellstead & M.B. Zarrop, Self-Tuning Systems: Control and Signal Processing, J. Wiley & Sons, Chichester, England, 1991.

 

7.       Grading

There will be no final exam. Grades will be determined based on homeworks and a final project report (50/50). A grade B will correspond to a satisfactory completion of the homeworks and of the final project. Students who perform particularly well in both categories will receive a grade A. Grades of C or less will be given in cases where homeworks or reports are below average.

 

8.       Homeworks

Homeworks will consist in exercises and in computer simulations. The simulations will illustrate the properties derived analytically and will help to gain insight into the dynamic behavior of adaptive systems.

 

9.       Project

Completion of a project is required for the course. A project consists in an independent investigation of a topic of current interest related to the course. Students are responsible for the selection of the topic of their project. Suggestions are given on the class web site, but subjects that are of particular interest to the students, or are related to their research, are welcome. The topic must approved by the instructor.

The requirements for the project are as follows (please find the due dates for all assignments on the class web site):

For all reports, students should remember to include their name, the title of their project, and a list of references. The recommended format is 1.2 line spacing, 11pt font size, and 1in margins.

A typical project consists in a survey of at least 3 papers from the research literature, organized around a common topic. The most convenient source is the IEEE Xplore database freely available to users of the University of Utah’s network (www.ieeexplore.ieee.org). Journals with contributions to the field of adaptive control include IEEE Trans. on Automatic Control and IEEE Trans. on Control Systems Technology. Journals outside of IEEE may be harder to obtain, but include Automatica, the International Journal of Control, and the International Journal of Adaptive Control and Signal Processing. Publications available from the university’s library system should also be consulted, and web search engines such as Google can be useful to find on-line resources.

The criteria for the grading of the reports are:

(a) originality and critical thinking (how interesting is the work?);

(b) technical challenges, accuracy, and completeness (how good is the work?);

(c) scope of the project (how much work was done?);

(d) quality of presentation: logical organization, clarity and neatness of the report (how well is the work presented?).

Copying from papers (or simply paraphrasing) will not be considered a valid contribution. Students are expected to write the report in their own words and to demonstrate that they have read the papers, understood them, and thought about them in a critical and investigative manner. Examples of contributions expected in the report include: critical evaluation of the significance of the results, comparison of different approaches, simplified or expanded analysis of the results, and independent verification of the results (e.g., through simulations or experiments). A small number of papers or a more limited comparison of the papers is acceptable if extensive validation of a concept is performed in simulations or in experiments.