Robust Control, Optimization, and Applications to Markovian Jumping Systems
1School of Electrical Engineering and Automation, Anhui University, Hefei, Anhui, China
2National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, Zhejiang, China
3School of Electrical Engineering and Information, Anhui University of Technology, Ma'anshan, Anhui, China
4Department of Mathematics and Statistics, Curtin University, Perth, WA, Australia
5Institute of Finance and Statistics, School of Mathematical Sciences, Nanjing Normal University, Nanjing, Jiangsu 210023, China
Robust Control, Optimization, and Applications to Markovian Jumping Systems
Description
Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits.
The overall aims of this special issue are to focus on theoretical and practical aspects on new control method: optimization for Markovian jumping systems. Solicited papers must bring new ideas, approaches, clearly indicating the advances made through problem statements, and methodologies with applications to Markovian jumping systems. Topics to be covered in this special issue include, but are not limited to:
- Adaptive control and robust control
- Optimization and optimal control
- Predictive control
- Intelligent control using fuzzy modeling or neural network
- Control strategies to Markovian jumping systems with constraints or sensor failures
- Stochastic signal processing
- Applications of novel control algorithms to Markov jump systems
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