Robust internal model-based control of sampled-data systems: An adaptive sliding-mode approach

An adaptive discrete-time, internal model–based sliding mode control scheme is proposed for continuous-time linear time-invariant systems subject to disturbances assumed to be captured by an uncertain exosystem. Building upon a robust internal model-based control framework, an adaptive mechanism inspired by active disturbance rejection is introduced to estimate online the disturbance, eliminating the need for a priori knowledge of disturbance bounds. The proposed approach explicitly accounts for discretization effects inherent to digital implementations and ensures bounded tracking error under an output-feedback configuration. To this end, an observer is designed to reconstruct the required states and disturbance-related dynamics. Experimental results on a quarter-car suspension setup demonstrate improved disturbance rejection and robustness compared to internal model–based and adaptive sliding mode controllers.

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Publication Details

Journal
Control Engineering Practice
Published
2026-08-26
DOI
https://doi.org/10.1016/j.conengprac.2026.107223
Primary Topic
Control Systems and Identification
Type
article
Field-Weighted Citation Impact
0.00
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article

Robust internal model-based control of sampled-data systems: An adaptive sliding-mode approach

Markus Reichhartinger, Stefan Koch, Atabak Azimi, Denis Efimov
Control Engineering Practice
Control Systems and Identification
article

Robust internal model-based control of sampled-data systems: An adaptive sliding-mode approach

Markus Reichhartinger, Stefan Koch, Atabak Azimi, Denis Efimov
article en

Abstract

An adaptive discrete-time, internal model–based sliding mode control scheme is proposed for continuous-time linear time-invariant systems subject to disturbances assumed to be captured by an uncertain exosystem. Building upon a robust internal model-based control framework, an adaptive mechanism inspired by active disturbance rejection is introduced to estimate online the disturbance, eliminating the need for a priori knowledge of disturbance bounds. The proposed approach explicitly accounts for discretization effects inherent to digital implementations and ensures bounded tracking error under an output-feedback configuration. To this end, an observer is designed to reconstruct the required states and disturbance-related dynamics. Experimental results on a quarter-car suspension setup demonstrate improved disturbance rejection and robustness compared to internal model–based and adaptive sliding mode controllers.

Control Engineering PracticeVol. 177
Centre National de la Recherche Scientifique (FR), Université de Lille (FR), Graz University of Technology (AT)
Openalex Percentile: Top 15%
Control Systems and Identification
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