Syllabus
The Ohio State University
Dept. Electrical Engineering

EE 858 Intelligent Control

Spring 2003

Office Hours: Stop by any time (but try to set an appointment)

Course Book/Notes: This course is taught out of the book: K. Passino, Biomimicry for Optimization, Control, and Automation, the web site of which you can go to by clicking here.

Relevant Texts (not needed for this course but both are available for a free download by clicking here):

1. Kevin M. Passino and Stephen Yurkovich, Fuzzy Control, Addison Wesley Longman, Menlo Park, CA, 1998.
2. Antsaklis P.J., Passino K.M., eds., An Introduction to Intelligent and Autonomous Control, Kluwer Academic Publishers, Norwell, MA, 1993.

Course Objectives:

The course will involve (i) gaining an understanding of the functional operation of a variety of intelligent control techniques and their bio-foundations, (ii) the study of control-theoretic foundations (e.g., robustness), (iii) learning analytical approaches to study properties (especially stability analysis), and (iv) use of the computer for simulation and evaluation. The objective will be to gain a "hands-on" working knowledge of several of the main techniques of intelligent control and an introduction to some promising research directions.

Outline: Topics to be covered include:

• Week 1: Introduction (control foundations, biomimicry), Instinctual neural control (multilayer perceptron, radial basis function neural network, design example, stability analysis)
• Week 2: Fuzzy and expert control (standard, Takagi-Sugeno, mathematical chararacterizations, design example)
• Week 3: Planning systems (autonomous vehicle guidance for obstacle avoidance, model predictive control), Attentional systems (attentional strategies for predators/prey)
• Week 4: Learning and function approximation (function approximation problem), adaptive control introduction
• Week 5: Learning/adaptation (training neural networks and fuzzy systems with least squares and gradient methods), stable fuzzy/neural adaptive control
• Week 6: Evolutionary methods (genetic algorithm, evolutionary design)
• Week 7: Foraging, bacteria and connections to optimization and control
• Week 8: Foraging, bees and connections to optimization
• Week 9: Swarm stability (cohesion, foraging)
• Week 10: Competitive foraging games, coordinated vehicular guidance applications

Grading: Homeworks, Projects, Final examination

Graduate standing
EE 551 Feedback Control Systems (classical control) or an equivalent course
EE 750 Linear Systems
EE 754 Nonlinear Control Systems is highly recommended (at least as a co-requisite)
Or permission from the instructor

Last updated: 2/14/03