Theory and Design of Extended PID Control for Stochastic Systems with Structural Uncertainties

TL;DR

This paper develops an extended PID control framework for stochastic nonlinear systems with arbitrary relative degree, ensuring global stability and bounded tracking errors despite structural uncertainties and noise.

Contribution

It introduces a novel extended PID controller design for stochastic systems with arbitrary relative degree, guaranteeing stability and performance under uncertainties.

Findings

Global mean-square stability achieved with extended PID.

Steady-state error proportional to noise intensity.

Controller parameters can be tuned to reduce steady-state error.

Abstract

Since the classical proportional-integral-derivative (PID) controller has continued to be the most widely used feedback methods in engineering systems by far, it is crucial to investigate the working mechanism of PID in dealing with nonlinearity, uncertainty and random noises. Recently, Zhao and Guo (2022) has established the global stability of PID control for a class of uncertain nonlinear control systems with relative degree two without random perturbations. In this paper, we will consider a more general class of nonlinear stochastic systems with an arbitrary relative degree $n$, and discuss the stability and design of extended PID controller (a natural extension of PID). We demonstrate that, the closed-loop control systems will be globally stable in mean square with bounded tracking errors provided the extended PID parameters are selected from an $(n+1)$-dimensional unbounded set, even if both the system nonlinear drift and diffusion terms contain a wide range of structural uncertainties. Moreover, the steady-state tracking error is proved to be proportional to the noise intensity at the setpoint, which can also be made arbitrarily small by choosing the controller parameters suitably large.