中文简介
《鲁棒与非线性控制国际期刊》旨在鼓励对不确定线性和非线性系统的分析和设计技术的发展。该期刊的主要研究方向是调节和跟踪系统的理论和设计，但包括线性和非线性滤波、状态监测和故障估计等相关领域。对可能是不确定或非线性的系统进行物理建模、仿真和识别是有意义的。考虑协调控制问题的多智能体系统领域的论文也很受欢迎。处理共识和同步的一般问题的论文，如果不能证明一个应用程序和/或包含重要的新奇性，将不予考虑。证明鲁棒或非线性控制器在应用中的潜力的论文也将受到欢迎，但这些论文必须包含足够的新材料。该杂志提供了一个自然论坛的论文，关于鲁棒控制设计和估计技术的理论和应用，包括H∞或H2设计，多目标优化，变结构和滑模控制设计方法。也欢迎关于提高不确定系统鲁棒性的非最优方法的论文，如QFT设计方法。此外，还鼓励研究基于线性和非线性模型的预测控制算法，以及与线性参数变化、切换或混合系统相关的论文。在非线性控制和估计中使用的理论和技术的所有方面也包括从增益调度到网络鲁棒或非线性控制系统。利用反馈线性化、反推、基于李雅普诺夫的技术、学习控制、合作控制和基于代理的系统来实现非线性补偿和设计方法的发展是人们关注的热点。对鲁棒控制的数值算法的贡献，例如使用线性矩阵不等式，以及控制器的调优，调试和实现的主题都包括在内。
英文简介
The International Journal of Robust and Nonlinear Control aims to encourage the development of analysis and design techniques for uncertain linear and nonlinear systems. The main focus of the journal is on the theory and design of regulating and tracking systems, but related areas such as linear and nonlinear filtering, condition monitoring and fault estimation are included. The physical modelling, simulation and identification of systems that may be uncertain or nonlinear is of interest. Papers are also welcome in the area of multi-agent systems considering coordinated control problems. Papers dealing with the general problem of consensus and synchronization that fail to demonstrate an application and/or include significant novelty will not be considered.Papers that demonstrate the potential for robust or nonlinear controllers in applications will also be welcome, but such papers must include sufficient novel material. The Journal provides a natural forum for papers on the theory and application of robust control design and estimation techniques, including H∞ or H2 design, multi-objective optimization, and variable structure and sliding mode control design methods. Papers will also be welcome on non-optimal methods of improving the robustness of uncertain systems, such as QFT design methods. Papers on linear and nonlinear model based predictive control algorithms are also encouraged, and those concerned with linear parameter varying, switched or hybrid systems.All aspects of the theory and techniques used in nonlinear control and estimation are also included ranging from gain scheduling to networked robust or nonlinear control systems. The development of nonlinear compensation and design methods using feedback linearization, back-stepping, Lyapunov based techniques, learning control, cooperative control and agent based systems are all of interest. Contributions on numerical algorithms for robust control, using for example linear matrix inequalities, and the topics of controller tuning, commissioning and implementation are all included.
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