Nowadays, humanity is experiencing an era of increasing and accelerated interdisciplinary scientific and technological changes; it is known as Industry 4.0. Control theory and has an essential role in the solution of interdisciplinary engineering problems of Industry 4.0, through mathematical techniques that guarantee a more complete and rigorous analysis to increase efficiency and effectiveness in devices, processes, and systems such as mobile devices, Internet of things (IoT) platforms, advanced human-machine interfaces, cyber-physical systems, artificial intelligence (AI), intelligent factories, or ecosystems, among others.

Hence, improvements on traditional control techniques, such as feedback linearization, backstepping, robust control, and classical delayed-approaches, should be developed, perhaps by combining them with modern techniques such as convex approaches (linear matrix inequalities, or convex models), artificial intelligence algorithms, and adaptive control. The resulting approach should be able to provide performance requirements such as safety, reliability, and numerical tractability for systematic procedures in modern applications on cyber physical systems, process control, biomedical engineering, robotics, aircraft, and spacecraft systems, to name a few.

The aim of this Special Issue is to contribute new mathematical tools and recent advances in the analysis and design of nonlinear control systems to solve engineering problems where classical techniques are unattractive. We invite authors to contribute articles that describe novel results on nonlinear control systems to solve engineering problems and their related applications. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Robust control of uncertain systems
• Feedback control of time delay systems
• Control based on networks
• Control of complex systems
• Non-model-based control
• Control of variable structure systems
• Control of cyber physical systems
• Advanced approaches to industrial process control
• Control using convex approaches