多元微积分
控制理论(社会学)
模型预测控制
解耦(概率)
温度控制
稳健性(进化)
过程控制
自适应控制
控制系统
计算机科学
控制工程
工程类
过程(计算)
控制(管理)
人工智能
基因
操作系统
电气工程
化学
生物化学
作者
Chi‐Huang Lu,Ching‐Chih Tsai
摘要
This paper presents an adaptive decoupling temperature control for an extrusion barrel in a plastic injection molding process. After establishing a stochastic polynomial matrix model of the system, a corresponding decoupling system representation was then developed. The decoupling control design was derived based on the minimization of a generalized predictive performance criterion. The set-point tracking, disturbance rejection, and robustness capabilities of the proposed method can be improved by appropriate adjustments to the tuning parameters in the criterion function. A real-time control algorithm, including the recursive least-squares method, is proposed which was implemented using a digital signal processor TMS320C31 from Texas Instruments. Through the experimental results, the proposed method has been shown to be powerful under set-point changes, load disturbances, and significant plant uncertainties. The proposed control law is shown to be less computational and more effective than other well-known multivariable control strategies, and more powerful than single-loop temperature-zone control policies.
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