Nonlinear Analysis: Hybrid Systems (NAHS) welcomes all original research papers on mathematical concepts, tools, and techniques from control theory, computer science, and applied mathematics for the modelling, analysis and design of hybrid dynamical systems, i.e., systems involving the interplay between discrete and continuous dynamic behaviors.
Hybrid systems are ubiquitous in many branches of engineering and science as they can model broad ranges of dynamical systems. In particular, in cyber-physical systems, which integrate sensing, computation, control and communication (cyber) parts into physical objects and infrastructures, hybrid systems play an instrumental role. The description of the behavior of the cyber parts often calls for discrete models (automata, finite-state machines, switching logic, etc.), while the physical (thermal, mechanical, electrical, physical, biological) parts are well captured by continuous modelling formalisms (e.g., differential equations), thereby naturally resulting in hybrid system models such as (stochastic) hybrid automata, timed automata, switched systems, impulsive systems, jump-flow models, piecewise affine systems, non-smooth systems, etc. Also, many physical phenomena can often be well described by non-smooth or hybrid models, including mechanical systems with impacts and friction (walking robots), switched power converters and biological systems (e.g., firing neuron models).
Hybrid systems can exhibit very rich dynamics and their analysis calls for new and strong theorical foundations to guarantee their stability, safety, functionality, and performance. The development of systematic methods for efficient and reliable design of hybrid systems is therefore a key challenge on the crossroads of control theory and computer science. It is currently of high interest to control engineers, computer scientists and mathematicians in research institutions as well as in many industrial sectors.
Contributions to Nonlinear Analysis: Hybrid Systems are invited in all areas pertaining to hybrid dynamical systems including:
Modeling, modeling languages and specification;
Analysis, computability and complexity;
Stochastic hybrid systems;
Formal verification and abstraction;
Optimization and controller synthesis;
Control over communication networks including self- and event-triggered control;
Network Science and multi-agent systems;
Fault diagnosis and fault-tolerant control;
Simulation, implementation and tools;
Safety, security, privacy, and resilience for cyber-physical systems;
Planning and integrated control in dynamical systems.
Contributions on applications of hybrid dynamical systems methods are also encouraged. Fields of interest include: process and manufacturing industries, automotive and mobility systems, avionics, communication networks and networked control systems, energy and power systems, transportation networks, cyber-physical and embedded systems, (synthetic) biology and biomedical applications, life sciences, safety-critical systems, mobile and autonomous robotics, and other related areas.