过程动力学辨识优化控制

P. Eykhoff, O. Smith
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引用次数: 8

摘要

说明了过程辨识、自适应控制和最优控制的含义。这些类型的控制与普通控制的基本区别在于需要一个“学习过程”。使用乘法加积分作为最简单的“学习”类型,得到了简单的方案,其中正弦或随机波动可以用作测试信号。对该优化系统进行了较为详细的研究和模拟仿真。这种方法不存在以前提出的系统的缺陷,即:系统动力学对优化控制作用的不利影响,当过程动力学随时间变化时,优化控制回路的回路增益会发生变化,甚至不稳定。这是通过引入过程动力学模型来实现的,该模型的参数由识别控制回路控制。最优控制收敛速度的典型值可以给出如下:使用正弦测试信号,阶跃扰动的瞬态近似为\epsilon ^{-t/\tau},其中τ的值对应于所使用的测试信号的三个周期。虽然系统是非线性和时变的,但得到的一些分析结果与计算机计算结果相吻合。所提出的思想可以推广到多维优化和多参数辨识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimalizing control with process-dynamics identification
The meaning of the terms process identification, adaptive and optimalizing control is indicated. The basic difference between these types of control and the ordinary ones is the need for a "learning process". Using multiplication plus integration as the simplest possible type of "learning", simple schemes are obtained in which sinusoidals or random fluctuations may be used as test signals. A more detailed study and an analog simulation have been made of such an optimalizing system. This one is free from the defects of formerly proposed systems, i.e.: - the detrimental effects of system dynamics on the optimalizing control action, - the loop gain changes and even instability of the optimalizing control loop when the process dynamics change with time. This has been achieved by introducing a model of the process dynamics, the parameter(s) of which are controlled by an identifying-control loop. A typical value for the convergence speed towards the optimum of the optimalizing control can be given as follows: using a sinusoidal test signal, the transient for a step-disturbance is approximately of the form \epsilon^{-t/\tau} where the value of τ corresponds with three periods of the test signal used. Although the system is nonlinear and time varying, some analytical results have been obtained which check the computer results. The ideas presented can be extended to more-dimensional optimalization and more-parameter identification.
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