Intelligent Control Systems

Semester: 
Fall
Offered: 
2012

Dynamic Linear Systems Identification
Problem statement
The identification process
Linear time invariant models
Parameter estimation: least squares
Model validation 
RLS
Adaptive Control
Introduction
Functional models
Pole placement
Artificial Neual Networks
Introduction
The neuron 
Activation functions
Proactive multi-layer networks
Approxiamtion properties
Supervised training in multi-layer networks 
Generelization and validation
Control neural architectures 
Fuzzy Control
Fuzzy systems fundamentals 
Defuzzyfying time variables
Inference with linguistic variables
Defuzzyfying linguistic variables
Fuzzy control design