智能控制及其应用论文翻译

英文翻译

Intelligence Control and its Application

ZOU En1，2，LIN Yi-qin3,ZHANG Tai-Shan1

Abstract: The author introduces some basic concepts about intelligence control in this paper, which includes fuzzy control, adaptive fuzzy-neural control, expert fuzzy system and artificial neural networks and so on, and features of fuzzy theory and artificial neural network are briefly analyzed. Finally, the author combines artificial neural network techniques with PID control, the neural network PID control method is applied to the temperature control system, seeing from the output curve, the present method has many advantages of small overshoot, short setting-time, and an excellent control result has provided for the system.

Key words: intelligence control; neural network; temperature control system.

It is well known that the emergence of intelligent control has made it conducive to integrate fuzz logic control and artificial neural networks and expert system for the development of control systems. The ability of these systems to complex non-linear function of many variables through a learning control driven by an error signal is particularly attractive. On the other hand, the intelligent control has found various applications in industrial produce as well as household applications. For example, for some complex or ill-defined systems that are not easily controlled by conventional schemes, the advanced control can provide a feasible alternative to get the approximate and qualitative data of human experts knowledge. As developing industrial control, the flourishing field of intelligent control technology has already provided some significant applications in the new control technology.

Some basic concepts about intelligent control have been attempted to set out in this paper and also uses an example to show the application of intelligent control in the temperature control system.

1fuzzy control

The development of fuzzy theory comes from the inability to describe some physical phenomena with the exact mathematical or conventional model. So, fuzzy theory is a powerful tool in the exploration of complex problems, because of it has ability to determine outputs for a given set of inputs without using a conventional or mathematical model. it is a no model controller The basic motivation of fuzzy theory is that complex problems become simplicity [1-3].

Fuzzy subset A of an universe of discourse U is characterized by a membership functionμ(χ):χ∈→[0,1]，representing the grade of membership of χin A .Fuzzy theory owes a great A

deal to human language, it is a language controller; each word or linguist term in a natural language can be viewed as a

label for a fuzzy subset A of a universe of discourse U. This language labels describing words,