There are many intelligent phenomena in the nature, for example: the thinking process of human brain, the cooperative mechanism of birds when they are foraging, the complex tasks completed by the ant colony although every ant in it behaves in a simple way, the producing of more adaptive individuals with the cross variation between chromosomes, and so on. Then, is it possible that we can reproduce these intelligent phenomena by computer programming, and use the programs to simulate the natural phenomena in nature，so as to serve the control process? The answer is yes. Human beings have been exploring this for decades, and have also achieved some preliminary results. This course is aimed to learn and explore intelligent phenomena in nature, and then serving the intelligent control.
Then, compared with the traditional classic control theory and modern control theory, what advantages and features does intelligent control have?
To put it in a simple way, the most prominent characteristic of intelligent control is that there is no need to establish the mathematical model of the object. However, in some aspects like large-scale system, nonlinear link and lagging link, it’s quite hard even impossible to conduct mathematical simulation accurately. Therefore, there is, in control theory, a promising future for intelligent control without mathematical model.
What is about in the course?
(1) Expert Control
Expert Control System mainly refers to an intelligent computer programming system, which contains a large amount of knowledge and experience of experts in a certain field and it can use the knowledge and experience of human experts to solve the high-level problems in this field. That is to say, Expert System is a programming system with a lot of specialized knowledge and experience. It uses artificial intelligence technology and computer technology to ratiocinate and judge based on the knowledge and experience of one or more experts in a certain field, and to simulate the decision-making process of human experts, so as to solve the complex problems which originally require human experts to deal with. In short, Expert System is one kind of computer programming system simulating human experts to solve domain problems.
(2) Fuzzy Control
Fuzzy control is to use fuzzy set theory, fuzzy language variable and fuzzy logic to realize the intelligent control of the system. This method avoids the accurate description of the input and output parameters of the controlled objects, it describes the expert control strategy with natural language, and achieves the effective control of the system with the fuzzy thoughts from the machine simulating the human. In the actual control process, the input quantity (accurate quantity) of computer sampling is fuzzified, and the fuzzy value of the control quantity is determined by fuzzification, finally the actual output of the control quantity is obtained by anti-fuzzy processing to control the controlled object.
(3) Artificial Neural Network Control
Artificial neural network is a way of processing information that simulates the biological neural network system of human brain. Learning and training are carried out by experience rather than well designed program, these constitute the basis of the ability of artificial neural network to recognize, predict, evaluate and optimize decision. Neural network control refers to the application of neural network technology in the control system to identify neural network models of complex nonlinear objects that are difficult to model accurately, it may act as a controller, or make optimal computation, it may make inferences or diagnose failures, or it may have all the functions above at the same time.
(4) Genetic Algorithm
Using the theory of biological evolution as a reference, the genetic algorithm simulates the problem to be solved as a process of biological evolution, The solutions of next generation is produced by replication, crossover, mutation, etc. this gradually eliminates the solutions to lower fitness function values, and increases the higher fitness function value solutions. In this way, after several generations of evolution, it is likely to produce individuals with high fitness function values.
This course makes detailed explanations clearly with the knowledge map. It strives to achieve an accurate and clear introduction of knowledge by comprehensive case analysis, exercise explanation, linking theory with practice, etc. It also introduces MATLAB programming knowledge in a separate chapter, which can help students to solve their problem of no programming background.
In a word, this course realizes the combination of artificial intelligence and automatic control task through theoretical study and program design. By studying this course, you will have a deeper understanding of automatic control theory, which lays a good foundation for the subsequent work and scientific research.
