Recent Developments in Stability and Control of Dynamical Systems

Dear Colleagues,

Mathematical modeling is an essential tool in studying a diverse range of dynamical systems. It describes the behaviors of complex and nonlinear phenomena in mathematics and physics, but it also has a long and rich tradition of applications in engineering, biology, economics, statistics, etc. In real-world problems, mathematical modeling of dynamical system is largely based on the abstraction that information is transmitted along perfect communication channels and that computation is either instantaneous (continuous-time) or periodic (discrete-time). In principle, there are two major sources of error in modelling of physical events: approximation errors due to the inherent inaccuracies incurred in the discretization of the events and modeling errors due to the natural imperfections in abstract models of actual physical phenomena. In order to deal with these issues, sophisticated mathematical techniques are needed. On the other hand, the important properties of dynamical systems play a central role in control systems. The stability concept is essential, because almost every practical control system is designed to be stable.

The objective of this Special Issue is to compile recent developments in methodologies and techniques for stability and control design of dynamical systems to deal with issues such as nonlinear events, kinematics of the actuators, reliability and security of communications, bandwidth allocation, development of data communication protocols, fault detection and fault tolerant control, real-time information collection, and efficient processing of sensor data. Relevant topics include, but are not limited to, the following areas:

• Stability and control design;
• Qualitative behaviors of dynamical systems;
• Linear and nonlinear system modeling;
• Stochastic dynamical systems;
• Fuzzy systems and its applications;
• Networked control systems.

Dr. Shengda Zeng
Prof. Dr. Stanisław Migórski
Guest Editors

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• optimal control
• differential equations and differential inclusions
• stability
• sensitivity
• optimal conditions
• fuzzy systems
• variational analysis
• numerical analysis
• qualitative analysis
• shape optimization