Singular systems, also referred to as descriptor systems, semistate systems, differential-algebraic systems, or generalized state-space systems, have been one of the main branches in control theory for nearly half a century. 

Many classical control theories and new concepts have been developed for singular systems in the last twenty years because such systems have appeared in the Leontief dynamic model, electrical systems, and mechanical systems. In recent years, with the development of communication systems, computer network, and biological systems, there are some new trends in optimization and control theory of singular systems based on data analysis.

Control systems are developing fast with new technologies as well as new systems such as network control, biological systems, and quantum control systems. As we know, singular systems can deal with dynamic systems in a more general framework and we should pay attention to the development of singular systems with currently occurring applications. Recently, notable advances in biological systems, communication systems, and computer network have increasingly promoted some important new directions in the study of singular systems.

This special issue is intended to present and discuss the new developments in singular systems based on data analysis, machine learning, and approximation theory. We will solicit high quality, original research articles as well as review articles focused on singular system theory with new applications.

Potential topics include but are not limited to the following:

• Data analysis and control related to singular biological systems
• Networked control of singular systems
• MPC of singular systems
• Model reduction of singular systems
• Analysis and control of singularly perturbed systems
• Data driven control based on SVM approximation
• Robust control of singular systems
• Analysis of nonlinear singular systems
• Singular Markovian systems