Nonlinear Analysis-Hybrid Systems

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官方网站：http://www.journals.elsevier.com/nonlinear-analysis-hybrid-systems/

投稿网址：http://ees.elsevier.com/nahs

PMC链接：http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1751-570X%5BISSN%5D

非线性分析混合系统欢迎在混合动力系统领域的所有重要研究和说明论文，即涉及离散和连续动力行为之间相互作用的系统。计算机和嵌入式无功控制系统，包括离散开关逻辑和与连续系统的事件驱动交互，在日常生活中无处不在。这些系统变得越来越复杂，难以设计和验证，同时对动力学性能和安全性的要求也越来越高。混合动力系统高效可靠设计的系统方法的开发是控制技术和工业信息领域的一个关键问题，因此控制工程师、计算机科学家和数学家在研究机构以及许多工业部门都非常感兴趣。在所有与混合动力系统相关的领域，包括：建模、建模语言和规范；分析、可计算性和复杂性；随机系统；脉冲系统；验证；抽象；优化；控制合成和实时控制；网络计算和控制；神经或模糊混合系统的方法；振荡器和混沌系统的同步；故障诊断和可靠性；仿真、实现和工具。还鼓励对混合动力系统方法的应用作出贡献。感兴趣的领域包括：工艺工业、汽车、航空电子、通信网络、能源系统、运输网络、嵌入式系统、生物学和其他科学、制造和机器人。

Nonlinear Analysis-Hybrid Systems welcomes all important research and expository papers in the area of hybrid dynamic systems, i.e., systems involving the interplay between discrete and continuous dynamic behaviors.Computer and embedded reactive control systems which includes discrete switching logic and event-driven interactions with continuous systems are ubiquitous in everyday life. These systems become increasingly complex and difficult to design and to verify while the requirements for dynamics performances and safety are also increasing. The development of systematic methods for efficient and reliable design of hybrid systems is a key issue in control technology and industrial information, and thus it is currently of high interest to control engineers, computer scientists and mathematicians in research institutions as well as in many industrial sectors.Contributions are invited in all areas pertaining to hybrid dynamic systems including: Modeling, modeling languages and specification; Analysis, computability and complexity; Stochastic systems; Impulsive systems; Verification; Abstraction; Optimization; Control synthesis and real-time control; Computation and control over networks; Neural or fuzzy approaches to hybrid systems; Synchronization of oscillators and chaotic systems; Fault diagnosis and dependability; Simulation, implementation and tools.Contributions on applications of hybrid dynamic systems methods are also encouraged. Fields of interest include: process industry, automotive, avionics, communication networks, energy systems, transportation networks, embedded systems, biology and other sciences, manufacturing and robotics.