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工程设计学报
Chinese Journal of Engineering Design  2013, Vol. 20 Issue (6): 529-533    DOI:
    
Research on the policy of multivariate autocorrelation process adjustment with colored noises
 ZHANG  Zhi-Jie, NIU  Zhan-Wen, HE  Zhen
School of Management and Economic，Tianjin University，Tianjin 300072， China
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Abstract  For the finite horizon multivariate autocorrelation manufacturing process， the optimal adjustment scheme is developed to minimize the total process quality loss with quadratic adjustment cost and process dynamic noises with AutoRegressive model. Based on the statespace process control model， the optimal adjustment scheme was derived by Kalman filter on line estimation and linear quadratic Gaussian（LQG） theory. A simulation case was presented to illustrate the implementation method of the optimal adjustment policy.  The optimal adjustment scheme was compared with quality adjustment policy with white noise by simulations. The results show that the proposed adjustment solution is more effective than other to reduce the total quality loss of the process．

Key words： multivariate process      statistical process adjustment      state-space model      Kalman filter      optimal adjustment     
Published: 28 December 2013
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ZHANG Zhi-Jie
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HE Zhen
Cite this article:

ZHANG Zhi-Jie, NIU Zhan-Wen, HE Zhen. Research on the policy of multivariate autocorrelation process adjustment with colored noises. Chinese Journal of Engineering Design, 2013, 20(6): 529-533.

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https://www.zjujournals.com/gcsjxb/     OR     https://www.zjujournals.com/gcsjxb/Y2013/V20/I6/529


有色动态噪声下多变量自相关过程调整策略研究

针对生产阶段有限的多变量自相关生产制造过程，研究了过程动态噪声为有色噪声、调整花费成本为二次型函数情形下的过程调整策略问题.在建立过程状态空间方程的基础上，利用卡尔曼滤波方法在线估计过程的状态变量，根据随机二次型最优控制理论，得到了使过程质量损失最小的最优调整策略.通过算例解释了最优调整策略的实现方法，并进行了仿真验证.结果表明，提出的调整策略与过程噪声为白噪声时的调整策略相比，能更有效地减少过程的总体质量损失.

关键词： 多变量过程,  统计过程控制,  状态空间模型,  卡尔曼滤波,  最优调整 
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