1. Aims and Objectives

1.1 Aim

This course presents some fundamental knowledge of fuzzy sets, fuzzy logic, fuzzy information processing, fuzzy decision-making, and fuzzy control systems.

The aim is to equip the first-year postgraduate students with some state-of-the-art fuzzy-logic technology, fuzzy informatics, and fuzzy intelligent systems design methodologies, thereby better preparing them for the rapidly evolving high-tech and information-based financial market and modern industry.

1.2 Objectives

1.2.1 To introduce basic knowledge of fuzzy sets and fuzzy logic

1.2.2 To introduce basic knowledge of fuzzy information processing

1.2.3 To introduce basic fuzzy inference and approximate reasoning

1.2.4 To introduce basic notion of fuzzy rule base

1.2.5 To introduce basic fuzzy system modeling methods

1.2.6 To introduce basic fuzzy PID control systems

1.2.7 To introduce computational verb controllers

2. Syllabus

2.1 Introduction to fuzzy sets and fuzzy logic

The uncertain and inexact nature of the real world: ideas and examples; fuzzy membership functions; fuzzy numbers and fuzzy arithmetic; basic concepts and properties of fuzzy logic versus classical two-valued logic

2.2 Introduction to fuzzy information processing

Basic concepts and techniques for fuzzy information processing

2.3 Introduction to fuzzy inference

Fuzzy inference principles; fuzzy decision-making; approximate reasoning

2.4 Introduction to fuzzy rule base

If-Then rules; general format of fuzzy rule base; establishment of fuzzy rule base

2.5 Introduction to fuzzy modeling

Static fuzzy modeling; dynamic fuzzy modeling

2.6 Introduction to fuzzy control systems

Basic fuzzy control principle: set-point tracking; open-loop and closed-loop fuzzy control systems; basic fuzzy PID controllers design methods and applications; computational verb controllers

3. Teaching Methods

Lecturing is the core of teaching. Substantial reading material will be assigned, followed by students' practice. Two computer projects on fuzzy decision-making and tracking control will be given for which simulation reports are required. One set of homework is assigned every week and then due in the following week.

4. Grading

Homework:                                                       15%
Projects and class presentations:                    25%
Midterm Exam:                                                20%

Final Exam                                                        40%