Manuscript Topics

The recent trend of amalgamating different mathematical technologies has profoundly transformed research in dynamical systems. Researchers have been developing hybrid algorithms, evaluating mathematical modeling accuracy, and designing optimization and control strategies for physical controlled dynamical systems, particularly those with nonlinear dynamics or network constraints. As an emerging class of these systems, autonomous unmanned systems (AUSs) have received much attention in the research community, covering a wide range of vehicular domains, including aerial, terrestrial, and underwater robotics. The recent breakthroughs in artificial intelligence and computational hardware have revolutionized the development of autonomous unmanned systems, enabling many high-impact applications in the fields ranging from disaster response to industrial automation. Examples include search-and-rescue operations in complicated environments, inspection and supervision of critical infrastructure, and large-scale logistics and transportation. While conventional modelling and control strategies enable considerable coordination in AUSs, the integration of emerging advanced techniques, such as distributed optimization, game theory, and machine learning, has revitalized the field. Furthermore, the deployments in complex or adversarial environments present both significant challenges and novel opportunities. Heterogeneous system dynamics, communication constraints (e.g., delays, cyber threats), energy limitations, and safety-critical requirements necessitate breakthroughs in high-fidelity modeling, optimization, and intelligent control strategies.    

This special issue endeavors to provide a platform for the dissemination of recent developments, discoveries, and advancements in the fields of modelling, optimization, and control of AUSs. The objective of the contributions is to consolidate recent developments relevant to the topics of this special issue. Researchers are encouraged to contribute their original works that contribute to the advancement of modeling, optimization, and intelligent control for AUS coordination.

Key areas of interest within this Special Issue include, but are not limited to:  
- Identification and mathematical modelling for AUS
- Optimization algorithm for AUS
- Learning-based control and its applications in AUS
- Data-driven method for modelling and control of AUS
- Secure issues and control protocols for AUS
- Dynamic analysis of AUS with hybrid or complex performance
- Performance guarantees and intelligent control for AUS
- Cyber-physical systems  
- Multi-agent systems
- Extensive Applications for AUSs in target detection, monitoring, localization, tracking, safety, among many others

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