Shuang Wang, Tao Han, Bo Xiao, Xiao‐Feng Zhao, Huaicheng Yan
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Predefined‐time hierarchical control for bipartite time‐varying formation tracking of networked Euler–Lagrange systems with parametric uncertainties
This paper mainly addresses the bipartite time‐varying formation tracking (BTVFT) problem for networked Euler–Lagrange systems (NELSs) with external disturbances and parametric uncertainties, considering a directed signed communication network that encompasses both cooperative and competitive interactions. A novel nonsingular sliding mode control (SMC) method serves as the foundation for a predefined‐time hierarchical control algorithm (PTHCA), introduced to tackle the BTVFT challenge for NELSs in a predefined time. This approach enables the settling time to be predetermined as a control parameter. Moreover, sufficient conditions for establishing the predefined‐time stability of closed‐loop systems are provided based on the Lyapunov argument. Simulations are conducted to demonstrate the effectiveness of the main findings.
期刊介绍:
The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application.
Published six times a year, the Journal aims to be a key platform for control communities throughout the world.
The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive.
Topics include:
The theory and design of control systems and components, encompassing:
Robust and distributed control using geometric, optimal, stochastic and nonlinear methods
Game theory and state estimation
Adaptive control, including neural networks, learning, parameter estimation
and system fault detection
Artificial intelligence, fuzzy and expert systems
Hierarchical and man-machine systems
All parts of systems engineering which consider the reliability of components and systems
Emerging application areas, such as:
Robotics
Mechatronics
Computers for computer-aided design, manufacturing, and control of
various industrial processes
Space vehicles and aircraft, ships, and traffic
Biomedical systems
National economies
Power systems
Agriculture
Natural resources.