自動化專業畢業論文外文文獻翻譯(存儲版)

　　

【正文】 TLAB, the simulation modal is as and Setp2 are the given value disturbance and superheating water disturb amp。 目 錄Part 1 PID type fuzzy controller and parameters adaptive method 1Part 2 Application of self adaptation fuzzyPID control for main steam temperature control system in power station 7Part 3 Neurofuzzy generalized predictive control of boiler steam temperature ………13Part 4 為Part3譯文：鍋爐蒸汽溫度模糊神經網絡的廣義預測控制2126 / 27Part 1 PID type fuzzy controller and Parameters adaptive method Wu zhi QIAO, Masaharu Mizumoto Abstract: The authors of this paper try to analyze the dynamic behavior of the productsum crisp type fuzzy controller, revealing that this type of fuzzy controller behaves approximately like a PD controller that may yield steadystate error for the control system. By relating to the conventional PID control theory, we propose a new fuzzy controller structure, namely PID type fuzzy controller which retains the characteristics similar to the conventional PID controller. In order to improve further the performance of the fuzzy controller, we work out a method to tune the parameters of the PID type fuzzy controller on line, producing a parameter adaptive fuzzy controller. Simulation experiments are made to demonstrate the fine performance of these novel fuzzy controller structures. Keywords: Fuzzy controller。s error. With the parameter adaptive fuzzy controller, the oscillation of the system is strongly restrained and the settling time is shortened considerably. We have presented the simulation results to demonstrate the fine performance of the proposed PID type fuzzy controller and the parameter adaptive fuzzy controller structure. Part 2 Application of self adaptation fuzzyPID control for main steam temperature control system in power stationZHIBIN LIAbstract: In light of the large delay, strong inertia, and uncertainty characteristics of main steam temperature process, a self adaptation fuzzyPID serial control system is presented, which not only contains the antidisturbance performance of serial control, but also bines the good dynamic performance of fuzzy control. The simulation results show that this control system has more quickly response, better precision and stronger antidisturbance ability．Keywords：Main steam temperature；Self adaptation；Fuzzy control；Serial control1. IntroductionThe boiler superheaters of modem thermal power station run under the condition of high temperature and high pressure, and the superheater’s temperature is highest in the steam channels．so it has important effect to the running of the whole thermal power station．If the temperature is too high, it will be probably burnt out. If the temperature is too low ,the efficiency will be reduced So the main steam temperature mast be strictly controlled near the given value．Fig l shows the boiler main steam temperature system structure. boiler main steam temperature systemIt can be concluded from Fig l that a good main steam temperature control system not only has adequately quickly response to flue disturbance and load fluctuation, but also has strong control ability to desuperheating water disturbance. The general control scheme is serial PID control or double loop control system with derivative. But when the work condition and external disturbance change large, the performance will bee instable. This paper presents a self adaptation fuzzyPID serial control system. which not only contains the antidisturbance performance of serial control, but also bines the good dynamic character and quickly response of fuzzy control．1. Design of Control System The general regulation adopts serial PID control system with load feed forward．which assures that the main steam temperature is near the given value 540℃in most condition．If parameter of PID control changeless and the work condition and external disturbance change large, the performance will bee in stable．The fuzzy control is fit for controlling nonlinear and uncertain process. The general fuzzy controller takes error E and error change ratio EC as input variables．actually it is a nonlinear PD controller, so it has the good dynamic performance．But the steady error is still in existence. In linear system theory, integral can eliminate the steady error. So if fuzzy control is bined with PI control, not only contains the antidisturbance performance of serial control, but also has the good dynamic performance and quickly response.In order to improve fuzzy control self adaptation ability, Prof．Long ShengZhao and Wang Peizhuang take the located in bringing forward a new idea which can modify the control regulation online．This regulation is: This control regulation depends on only one fixed．the weight of E and EC will be fixed and the self adaptation ability will be very small．It was improved by Prof. Li Donghui and the new regulation is as follow。從實驗方案的仿真結果中可以看出，此方案的控制品質優于傳統的控制方案。作為GPC的推導應該盡量減少這些波動，它是眾多的控制器中最適合實現這一目標的。從模糊神經網絡可以考慮到作為一個網絡構成的若干項，其中每一項包含一個局部線性模型，在非線性預測控制的基礎上模糊神經網絡可以設計和使用各自的地方線性模型把當地所有的廣義預測控制器。非線性系統（1）分割成為幾個作業區域，如每個區域可以近似當成線性模型。該NFN輸出為 （8）3. 過熱蒸汽溫度的神經模糊塑造和有預測性的控制設是過熱蒸汽溫度，為水流噴射到高溫過熱器后的溫度。控制系統也防止了噴水閥門和水/蒸汽混合而影響設計的方案。圖5 控制策略仿真曲線比較4. 結論 本文通過對一個200MW的電廠模型的建立和控制分析提出了模糊神經網絡控制策略。設計的結果在圖7所示，顯示出預期最好的表現是從NFGPC獲得的，因為它的目的是基于一個更準確過程的模型。 對于一個30s的采樣間隔，估計線性模型的一個區域使用的NFN如表1所示。圖2 模糊神經網絡從模糊規則所產生的模糊變量的隸屬函數可以得到衍生的模糊規則。2. 模糊神經網絡的建模考慮以下的一般單輸入單輸出的非線性動態系統： （1）其中f[.]是一個光滑的非線性函數，將其按泰勒級數展開，其中是零均值、Δ是差分算子。然而，設計模糊邏輯控制器是非常消費時間的，由于模糊規則的不確定，往往得到的試驗是錯誤的。水變成噴涂的蒸汽，以控制過熱蒸汽的溫度。 Superheated steam temperature1. Introduction Continuous process in power plant and power station are plex systems characterized by nonlinearity, uncertainty and load disturbance. The superheater is an important part of the steam generation process in the boilerturbine syste