1、 本科毕业设计（英文文献翻译）英文题目：Gain-scheduling fuzzy temperature controller or one-way input system译文题目：增益规划的模糊温度控制器的单向输入系统学 院：专业名称：年级班级：学生姓名：指导教师：Gain-scheduling fuzzy temperaturecontroller for one-way input systemShiuh-Jer Huang1,2 and Chen-Chuan Wang21Department of Vehicle Engineering, National Taipei Unive
2、rsity of Technology, No. 1, Sec. 3, Chung-Hsiao East Road, Taipei, Taiwan 1062Department of Mechanical Engineering, National Taiwan University of Science andTechnology, No. 43, Keelung Road, Sec. 4, Taipei, Taiwan 106In many chemical and semiconductor manufacturing processes, temperature is an impor
3、tant control parameter for obtaining the desired product quality. Generally, the temperature control system has non-linear time-varying, slow response, time-delay and one-way control input characteristics. It is difficult to estimate accurately the dynamic model and design a general-purpose temperat
4、ure controller to achieve good control performance. Here a model-free intelligent gain-scheduling fuzzy control strategy is proposed to design a temperature controller for an iron closed chamber with heater input only. The concept of gain scheduling is employed to adjust the mapping ranges of fuzzy
5、membership functions during the control process for improving the control performance. The experimental results show that the steady-state errors of the step input responses are always less than 0.28C without overshoot by using this control scheme. It is suitable for industrial temperature control s
6、ystems.Key words: fuzzy control; gain scheduling; temperature control and one-way input.1. IntroductionTemperature is an important control parameter in chemical, material and semiconductor manufacturing processes. For example, material annealing, thin film deposition and TV glass melting furnace all
7、 need appropriate temperature control systems. Some of the temperature control systems have heating and cooling control phases and others only have a heating input control phase. Their dynamic behaviours have significant differences. The temperature control system witch input only isAddress for corr
8、espondence: Shiuh-Jer Huang, Department of Vehicle Engineering, National Taipei University of Technology, No. 1, Sec. 3, Chung-Hsiao East Road, Taipei, Taiwan 106. E-mail: hd3601ntut.edu.twFigures 1and 611appears in colour online: more difficult to monitor than two phase control systems to obtain go
9、od control performance. How to design a general-purpose temperature controller with good response speed, smaller steady-state error and without overshoot for industrial implementation is still a challenge in the control research field. Currently, onoff control and PID control schemes are employed in
10、 commercial products. A PID controller was proposed in 1936. It has been widely used in industrial automatic control systems. However, how to adjust the control gains is the key factor of implementing a PID controller. If the accurate dynamic model of a control system is available, the Ziegler and N
11、ichols rule (Ziegler and Nichols, 1942) and IMC control strategy (Chien and Fruehauf, 1990; Rivera et al., 1986) can be used to calculate the appropriate gains. However, the heating plant has time-delay and temperature dependence non-linear behaviours. It is hard to establish an accurate dynamic mod
12、el for a PID controller design. Generally, it needs a trial-and-error process to obtain a good control response. When the system has external disturbance or set-point change, its transient response may deteriorate. It needs an online operator to readjust it or switch it to manual control. This is no
13、t a convenient application and the production parameters may not maintain in a good level in manufacturing processes. Hence model-free intelligent control schemes have gained the attention of researchers.A self-tuning PID control strategy was proposed to control water bath temperature(Yusof et al.,
14、1994). A frequency loop-shaping technique is employed to tune the PID gains of the temperature controller of a chemical vapour deposition (CVD) diffusion furnace (Grassi and Tsakalis, 2000). The appropriate gains of this approach are searched based on the system output response of an onoff open-loop
15、 relay control. In addition, fuzzy control has been successful employed in many industrial processes, as it has model-free intelligent characteristics. Recently, fuzzy control theory has been used to improve the adaptivity and robustness of a PID controller. A hybrid fuzzy and PI control for TV glass melting furnace temperature control has been proposed (Moon and Lee, 2000, 2003). The fuzzy
