摘要
针对实际工业控制中出现的系统的随机噪声和量测噪声会严重影响现场生产的控制效果,传统的内模控制方式无法很有效地解决这一问题。将Kalman滤波器引入到传统的内模控制原理中,通过Kalman滤波器来减小甚至消除噪声对控制系统的影响,提高系统的控制精度。同时,利用NLJ算法在考察系统性能指标的情况下,对传统内模原理中的低通滤波器的滤波参数进行自动寻优。通过对滤波环节的改善,充分发挥Kalman滤波和NLJ自动寻优的特点,使得控制系统的鲁棒性和快速性都得到了提高。仿真结果表明提出的设计方法能较好解决单变量和多变量被控对象的实时性和时滞性,并且具有良好的抗噪性,该方法参数调节容易,易于实施。
In the practical industrial control process, system random noise and measurement noise could seriously affect the system control effectiveness. Kalman-fiher was used in tradition IMC construct to resolve the problem. Through Kalman filter to reduce or even eliminate the impact of noise on the control system to improve the control accuracy. At the same time, NLJ algorithm was used to examine system performance indicators and automatically opti- mized the filtering parameters of low-pass filter in traditional internal model principles. By improving filtering links and gave full play of Kalman filtering and NLJ automatic optimization features, the robustness and rapidity of control system had been improved. Simulation shows that this method can overcome the influence on control performance come from the parameter variation and system noise of the controlled object with time delay, has stronger antinoise and stability, In addition, the proposed method is easy to regulate, and it is fit for engineering applications.
出处
《化工自动化及仪表》
CAS
北大核心
2009年第6期11-14,共4页
Control and Instruments in Chemical Industry
基金
国家"863"计划资助项目(2008AA042131)
国家"973"计划资助项目(2007CB714300)
