Applied Artificial Intelligence

Figure. FLC Response with non-linear control surface (a) Depth Response (b) Heave Velocity “w’(c) Pitch Angle “Theta” (d) Pitch Velocity “q”

Course Code:             EE-7705
Credit Hours:             3

Undergraduate course in MATLAB or consent of the instructor.

Target Audience      
MS/Ph.D students wishing to pursue research in the areas of applied control or applied artificial intelligence.


A Course that provides sufficient skills to design fuzzy logic and neural network based systems to solve practical problems.
This course introduces students to the fundamentals of two techniques of artificial intelligence (AI), namely, fuzzy logic and neural networks.  Both techniques have been successfully applied by many industries in consumer products and industrial systems.  Fuzzy logic offers flexibility in developing rule-based systems using natural language type of rules. Neural networks on the other hand, have strong generalization properties and offer a simple way of developing system models and function approximation.  They are highly applicable for many pattern recognition applications.  This course give the students appropriate knowledge and skills to develop, design and analyze effectively these two AI techniques for practical problems with some degree of accuracy.  The students will also be given a hands-on programming experience in developing fuzzy logic and neural networks system to effectively solve real world problems.


The course will be taught by Dr. Kashif Ishaque ( Dr. Kashif Ishaque received his B.E. in Industrial Electronics Engineering from Institute of Industrial Electronics Engineering, NEDUET, Karachi, Pakistan, in 2007. He received his M.E. and PhD degree from Universiti Teknologi Malaysia (UTM), Malaysia. His research interests include modelling and control of photovoltaic (PV) system, intelligent control, nonlinear system control and application of optimization techniques such as genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE).


Recommended Books:

  • K. M. Passino and S. Yurkovich, “Fuzzy Control”, Addison-Wesley, California, 2001.
  • P. J. Antsaklis and K. M. Passino, “An Introduction to Intelligent and Autonomous Control”, Kluwer Academic Publishers, Massachusetts, 1993.
  • Li, Hongxing, Chen, C. L. P. and Huang, H. P., “Fuzzy Neural Intelligent Systems”, CRC Press, U.S.A., 2001.