Stability of the integral control of stable nonlinear systems

TL;DR

This paper rigorously analyzes the stability of integral control in stable nonlinear systems, showing that small gain PI controllers with saturating integrators ensure local exponential stability and effective tracking within bounded input ranges.

Contribution

It provides a theoretical foundation for the stability of PI controllers with saturating integrators in nonlinear systems under specific assumptions.

Findings

Small gain PI controllers achieve local exponential stability.

A larger region of attraction is possible with smaller controller gains.

The controller ensures asymptotic tracking of the reference signal.

Abstract

PI controllers are the most widespread type of controllers and there is an intuitive understanding that if their gains are sufficiently small and of the correct sign, then they always work. In this paper we try to give some rigorous backing to this claim, under specific assumptions. Let $\bf P$ be a nonlinear system described by $\dot x=f(x,u)$, $y=g(x)$, where the state trajectory $x$ takes values in $R^n$, $u$ and $y$ are scalar and $f,g$ are of class $C^1$. We assume that there is a Lipschitz function $\Xi:[u_{min},u_{max}]\rightarrow R^n$ such that for every constant input $u_0\in[u_{min},u_{max}]$, $\Xi(u_0)$ is an exponentially stable equilibrium point of $\bf P$. We also assume that $G(u)=g(\Xi(u))$, which is the steady state input-output map of $\bf P$, is strictly increasing. Denoting $y_{min}=G(u_{min})$ and $y_{max}=G(u_{max})$, we assume that the reference value $r$ is in $(y_{min},y_{max})$. Our aim is that $y$ should track $r$, i.e., $y\rightarrow r$ as $t\rightarrow\infty$, while the input of $P$ is only allowed to be in $[u_{min},u_{max}]$. For this, we introduce a variation of the integrator, called the saturating integrator, and connect it in feedback with $\bf P$ in the standard way, with gain $k>0$. We show that for any small enough $k$, the closed-loop system is (locally) exponentially stable around an equilibrium point $(Xi(u_r),u_r)$, with a large region of attraction $X_T\subset R^n\times[u_{min},u_{max}]$. When the state $(x(t),u(t))$ of the closed-loop system converges to $(\Xi(u_r),u_r)$, then the tracking error $r-y$ tends to zero. The compact set $X_T$ can be made larger by choosing a larger parameter $T>0$, resulting in smaller $k$.