论文标题
迈向不确定非线性系统的PID控制的理论基础
Towards a Theoretical Foundation of PID Control for Uncertain Nonlinear Systems
论文作者
论文摘要
众所周知,经典的PID控制在工业过程的各种控制循环中起着主导作用。但是,可以解释为什么线性PID可以成功处理无处不在的非线性动力学系统以及可以为PID参数提供显式设计公式的方法的理论。本文是作者最近致力于建立PID理论基础的努力的延续。我们将研究一类高维二阶非不确定系统的PID控制的基本原理。我们将证明可以明确构建一个三维参数集,以便每当从该集合中选择PID参数时,闭环系统将在全球范围内保持稳定,并且在系统不确定性的某些适当条件下,调节误差将呈呈指数快速的零。此外,我们将证明PD(PI)控制可以在全球范围内稳定几类高维不确定的非线性系统。此外,我们将在微分方程中应用Markus-Yamabe定理,以为选择PI参数的必要条件,以适用于一类非携带不确定系统的类别。这些理论上的结果明确表明,控制器参数不是高增益的必要条件,并且无处不在的PID控制确实相对于系统结构不确定性和控制器参数的选择确实具有很强的鲁棒性。
As is well-known, the classical PID control plays a dominating role in various control loops of industrial processes. However, a theory that can explain the rationale why the linear PID can successfully deal with the ubiquitous uncertain nonlinear dynamical systems and a method that can provide explicit design formulae for the PID parameters are still lacking. This paper is a continuation of the authors recent endeavor towards establishing a theoretical foundation of PID. We will investigate the rationale of PID control for a general class of high dimensional second order non-affine uncertain systems. We will show that a three dimensional parameter set can be constructed explicitly, such that whenever the PID parameters are chosen from this set, the closed-loop systems will be globally stable and the regulation error will converge to zero exponentially fast, under some suitable conditions on the system uncertainties. Moreover, we will show that the PD(PI) control can globally stabilize several special classes of high dimensional uncertain nonlinear systems. Furthermore, we will apply the Markus-Yamabe theorem in differential equations to provide a necessary and sufficient condition for the choice of the PI parameters for a class of one dimensional non-affine uncertain systems. These theoretical results show explicitly that the controller parameters are not necessary to be of high gain, and that the ubiquitous PID control does indeed have strong robustness with respect to both the system structure uncertainties and the selection of the controller parameters.