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Design and Experimentation of Digital Two-Degree-of-Freedoms Temperature Controllers for PET Blow Molding Machines
|關鍵字:||溫度控制;Temperature control;PID控制;雙自由度控制;延遲系統;PID control;Two degree of freedom control;Delay system||出版社:||電機工程學系所||引用:|| http://big5.chinabgao.com/gate/big5/www.chinabgao.com/reports/29246.html, 2012-02.  R. Yusof, and S. Omatu, "A Multivariable Self-Tuning PID Controllers," International Journal of Control, vol.57, no.6, pp.1387-1403 ,1993.  R. Yusof, S. Omatu, and M. Khalid," Self-Tuning PID Control: a Multivariable Derivation and Application," Automatica, vol.30, no.12, pp.1975-1981 ,1994.  C. C. Tsai, and C. H. Lu, "Adaptive Generalized Predictive Control of Plastic Extrusion Heating Process," Proc. of 1996 Automatic Control Conference, Taipei, Taiwan, pp.550-557, April ,1996.  M. Khalid, S. Omatu, and R. Yuof, "MIMO Furnace Control with Neural Networks," IEEE Transactions on Control System Technology, vol.1, no.4, pp.238-245, December 1993.  J. S. Taur, and C. C. 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This thesis presents two novel two-degree-of-freedoms stable digital controllers for a PET blow molding machine, in order to achieve satisfactory temperature control of the PET embryo passing through both heating boxes. This first type of controller is composed of a feedforward controller used to improve the transient performance, and a feedback Proportional-Integral-Derivative (PID) controller employed to eliminate remaining temperature errors and achieve disturbances rejection. Such a controller not only retains the practical expertise of the control practitioners working for PET blow molding machines, but also takes advantages of simple structure and easy operation of the conventional PID controller. The second kind of controller consists of a self-tuning PID controller whose three-term parameters are tuned by radial basis function neural networks (RBFNN), and the aforementioned feedforward controller. The second controller not only can automatically tune the three-term parameters by on-line learning the dynamic mathematical model of controlled plants, but also can extend to control a class of nonlinear industrial plants. Moreover, simulations and experimental results are conducted to show the effectiveness and merit of the proposed controllers with capabilities of set-point tracking and disturbance rejection.
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