Consideration about the stability and performance of a minimum variance control system
2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)(2020)
摘要
This paper presents a stability and performance analysis of a self-tuning minimum variance control system. Designed through a cost function minimization, the control law is described by a linear difference model with time varying parameters. Based on a linearized process model around an operating point and by using a parameter estimator, the control system automatically adapts itself when process parameters change (as effect of a disturbance). However, the performance of the control system is strongly conditioned by an a priori setting of a factor that weights the control variance term of the cost function. The goal of this stability analysis is to provide a strategy regarding how to tune this control penalty factor, which significantly influences the stability and performance of the control system. Two approaches were considered: one based on the control system response in relation to the disturbance, validated by a second one based on frequency response analysis.
更多查看译文
关键词
self-tuning,minimum variance control,stability analysis
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要