Sliding Mode and Robust Control: Theory and Applications

Dear Colleagues,

Advanced control strategies are critical to ensuring the effectiveness and performance of modern engineering systems. Sliding mode and robust control are effective schemes that can provide stability and precise performance under adverse conditions—such as unknown disturbances, unmodeled dynamics, parametric variations, and nonlinear interactions. These methods have been increasingly applied across fields, including autonomous systems, robotics, aerospace, power electronics, and intelligent manufacturing.

The developments of theory and applications in sliding mode and robust control are continuously evolving to address increasingly complex engineering challenges. Combined with the observers, learning-based methods and data-driven methods, sliding mode and robust control have shown particular promise in nonlinear mechanical systems, which can effectively deal with multi-input–multi-output, high nonlinearity, strong coupling, and uncertainties. In addition, for some special sliding mode methods, the finite-time convergence, fixed-time convergence, and predefined-time convergence characteristics have also been fully guaranteed.

This Special Issue, entitled “Sliding Mode and Robust Control: Theory and Applications”, aims to provide a scientific platform for presenting recent breakthroughs and applications of these control strategies. We welcome original research articles and comprehensive reviews that address both theoretical advances and practical applications, highlighting the role of sliding mode and robust control in enhancing the effectiveness, performance, stability, and safety of modern engineering systems.

Research articles and comprehensive reviews are welcome. Topics of interest include, but are not limited to, the following:

(1) Advanced sliding mode control methods.

(2) Robust control theory and synthesis methods.

(3) Adaptive sliding mode control methods.

(4) Higher-order sliding mode control methods.

(5) Active disturbance rejection control methods.

(6) Disturbance observer and uncertainty estimation methods.

(7) Event-triggered and sampled-data robust control methods.

(8) Learning-based and data-driven robust control methods.

(9) Fault-tolerant control and secure control methods.

(10) Sliding mode and robust control in cyber–physical systems.

(11) Emerging applications in intelligent and autonomous systems.

We look forward to receiving your contributions.

Dr. Xiaolei Li
Prof. Dr. Yi Zeng
Dr. Chengwei Wu
Dr. Xiangyu Shao
Guest Editors

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