Abstract
Sliding mode control (SMC) has been widely used to control linear and nonlinear dynamics systems because of its robustness against parametric uncertainties and matched disturbances. Although SMC design has traditionally addressed process model-based approaches, the rapid advancements in instrumentation and control systems driven by Industry 4.0, coupled with the increased complexity of the controlled processes, have led to the growing acceptance of controllers based on data-driven techniques. This review article aims to explore the landscape of SMC, focusing specifically on data-driven techniques through a comprehensive systematic literature review that includes a bibliometric analysis of relevant documents and a cumulative production model to estimate the deceleration point of the scientific production of this topic. The most used SMC schemes and their integration with data-driven techniques and intelligent algorithms, including identifying the leading applications, are presented.
| Original language | English |
|---|---|
| Article number | 543 |
| Journal | Algorithms |
| Volume | 17 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2024 |
Bibliographical note
Publisher Copyright:© 2024 by the authors.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- applications
- data-driven techniques
- intelligent algorithms
- sliding mode control
- systematic literature review
Types Minciencias
- Artículos de investigación con calidad A2 / Q2
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