| This thesis takes temperature system of glass furnace as research object, discusses the application of intelligent control to nonlinear time-vary complicated system in industrial process, and uses simulation experiments by MATLAB verifying the intelligent control algorithms.The temperature of glass furnace is a main parameter in glass production process; unduly high or low are detrimental to products quality. Maintaining temperature on its set point is the key factor for assuring high glass products quality. The thesis firstly introduces the structure, technological process and temperature control requirement of glass furnace, and then presents a dynamic characteristic analysis of it. The controlled object is a self-balance process with features of large time lag and inertia; all the parameters are changed with the temperature and operating mode of furnace. Therefore, the furnace temperature is difficult to be controlled with the above uncertain factors.At present, the mainly method used in glass furnace temperature control is PID control. Although PID control can achieve satisfied result in small range near temperature set point, it can't control temperature to its set point rapidly and smoothly at the time of the work condition change by a wide margin due to the influence of time lag and parameters varying. So PID control is subjected to comparatively big limitation. For this reason, researchers try to improve the control of this kind of systems continuously. For the large time lag and inertia system, many control methods have been put forward since the Smith predicator control rose in 1957, but the problem has not been solved completely. So it is of theoretical and practical significance to conduct researches in this respect. After review of control methods for large time lag process and their improvements in recent years, the thesis design an intelligent control scheme based on intelligent control theory.The advances in intelligent control theory and computer technology provide new methods and means for the control of large time lag and parameters varying system like glass furnace. Based on the foundation of intelligent control theory, the thesis expounds the intelligent control algorithms for glass furnace temperature in detail. The research emphases are fuzzy logical control, neural network control, genetic algorithm and the application of combination of the three aspects in glass furnace temperature control.The particular research work of this thesis are as the follows:1. Combine intelligent control technology with parameter identification technology to control glass furnace temperature. Use intelligent control technology to solve the control problem of process with time varying gain and large inertia; Use parameter on-line identification technology and optimal predication to solve the output predication problem of process with large time varying time lag.2. Use genetic algorithm to optimise the parameters of fuzzy logical controller off-line to solve the problem of excessive dependence of experience on designing of fuzzy logical controller and to enable the fuzzy neural network controller has relatively good initial parameters.3. Use new type of optimisation method梘enetic algorithm as parameter identification method to estimate the time varying parameter and time lag of the controlled process and realize the tracking to the dynamic parameters of process.4. Improve genetic algorithm by using double mutation operators in optimum process. In the earlier optimum stage a uniform mutation operator is used and in the later optimum stage an adaptive mutation operator is used, thus enhance the partial search ability of genetic algorithm besides its general search ability.5. Implement adaptive fuzzy logical control based on feed forward neural network through the combination of fuzzy logical inference and neural network. The combination remedies the defects of each in performance and makes the controller possess not only the advantage of non-linear control of fuzzy logical...
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