《魯棒與非線性控制國際期刊》旨在鼓勵對不確定線性和非線性系統(tǒng)的分析和設計技術的發(fā)展。該期刊的主要研究方向是調(diào)節(jié)和跟蹤系統(tǒng)的理論和設計，但包括線性和非線性濾波、狀態(tài)監(jiān)測和故障估計等相關領域。對可能是不確定或非線性的系統(tǒng)進行物理建模、仿真和識別是有意義的。考慮協(xié)調(diào)控制問題的多智能體系統(tǒng)領域的論文也很受歡迎。處理共識和同步的一般問題的論文，如果不能證明一個應用程序和/或包含重要的新奇性，將不予考慮。證明魯棒或非線性控制器在應用中的潛力的論文也將受到歡迎，但這些論文必須包含足夠的新材料。該雜志提供了一個自然論壇的論文，關于魯棒控制設計和估計技術的理論和應用，包括H∞或H2設計，多目標優(yōu)化，變結構和滑模控制設計方法。也歡迎關于提高不確定系統(tǒng)魯棒性的非最優(yōu)方法的論文，如QFT設計方法。此外，還鼓勵研究基于線性和非線性模型的預測控制算法，以及與線性參數(shù)變化、切換或混合系統(tǒng)相關的論文。在非線性控制和估計中使用的理論和技術的所有方面也包括從增益調(diào)度到網(wǎng)絡魯棒或非線性控制系統(tǒng)。利用反饋線性化、反推、基于李雅普諾夫的技術、學習控制、合作控制和基于代理的系統(tǒng)來實現(xiàn)非線性補償和設計方法的發(fā)展是人們關注的熱點。對魯棒控制的數(shù)值算法的貢獻，例如使用線性矩陣不等式，以及控制器的調(diào)優(yōu)，調(diào)試和實現(xiàn)的主題都包括在內(nèi)。

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.