Higher-order sliding mode observer design for linear time-invariant multivariable systems based on a new observer normal form

TL;DR

This paper introduces a new observer normal form for linear systems that enables the design of higher-order sliding mode observers capable of finite-time convergence despite unknown inputs, broadening applicability beyond existing methods.

Contribution

A novel observer normal form for strongly observable LTI multivariable systems that incorporates unknown inputs, facilitating robust finite-time state estimation without restrictive conditions.

Findings

The proposed observer achieves global finite-time convergence.

Numerical simulations demonstrate effectiveness in unknown input scenarios.

The method extends applicability beyond classical observer limitations.

Abstract

In various applications in the field of control engineering the estimation of the state variables of dynamic systems in the presence of unknown inputs plays an important role. Existing methods require the so-called observer matching condition to be satisfied, rely on the boundedness of the state variables or exhibit an increased observer order of twice the plant order. In this article, a novel observer normal form for strongly observable linear time-invariant multivariable systems is proposed. In contrast to classical normal forms, the proposed approach also takes the unknown inputs into account. The proposed observer normal form allows for the straightforward construction of a higher-order sliding mode observer, which ensures global convergence of the estimation error within finite time even in the presence of unknown bounded inputs. Its application is not restricted to systems which satisfy the aforementioned limitations of already existing unknown input observers. The proposed approach can be exploited for the reconstruction of unknown inputs with bounded derivative and robust state-feedback control, which is shown by means of a tutorial example. Numerical simulations confirm the effectiveness of the presented work.