Written as a result of a seven year research project using computational intelligence techniques for solving mineral processing problems at the U.S. Bureau of Mines, this book is about intelligent, adaptive process control. It brings together ideas from the field of computational intelligence , a part of the larger field of artificial intelligence, including fuzzy mathematics, genetic algorithms, and neural networks and uses these ideas to develop a generic architecture for accomplishing adaptive process control. In the development of this architecture, the requisite tools are described and then demonstrated on a number of problems. Moreover, most of the examples are of interest in industrial settings (although some simple examples are provided in the beginning so that the reader can focus on technique and not be overburdened with the complexity of the problems being solved.)
The focus of Practical Applications of Computational Intelligence for Adaptive Control is on practical applications. It provides practicing engineers and scientists with the information they need to solve process control problems in industry and academia.
If the reader is interested in solving difficult control problems or interested in the mechanics of basic computational intelligence techniques, then this book is an excellent place to start.
Table of Contents
Why Fuzzy Process Control?
The First Fuzzy Controller
A Cart-Pole Fuzzy Controller
A Satellite Rendezvous Fuzzy Controller
Genetic Algorithms as Search Procedures
Genetic Algorithms Design of a Liquid Level Controller
GA-Tuned Cart-Pole Control
Satellite Rendezvous Using a Genetic Algorithm
Time-Varying Cart-Pole Controller
Genetic Algorithms for Model Tuning
Neural Networks for Computer Modelling
Fuzzy Rules for Computer Modelling
Adaptive Control of a pH system
Adaptive Control of A Hexamine Production System
Adaptive Control of Column Flotation
Control of a Chaotic System
Helicopter Flight control
Fuzzy Classifier System