Lin He, Ziang Xu, Yujiang Wei, Mingwei Wang, Chunrong Huang, Qin Shi
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引用次数: 0
Abstract
The sliding mode control has to design a sliding manifold for manipulating the system motion in engineering practice, making system asymptotic stability paramount. This is particularly challenging for using variable sliding manifold parameters to formulate the sliding manifold for fast convergence and precise control. While much of the research on sliding mode control has focused on constant sliding manifold parameters, comparatively little is known about the variable approach of the sliding manifold parameters. Therefore, sliding manifold parameters are treated as variables and are computed by a parameter tuning algorithm. Regarding the parameter tuning algorithm, its input is the sliding mode control law with variable sliding manifold parameters, and its output is the computed sliding manifold parameters that will be transmitted back to the sliding mode control law. Through tuning the sliding manifold parameters by an optimal method of lowest cost with the measuring value and model computing value of system states based on the historical information, the difference between the nominal model and the real system will be removed. Here we discuss a series of studies on the algorithm of tune sliding control that, collectively, develop an application of how the tune sliding controller steers the front wheels of the full self-driving vehicle. The designed approach has been tested in a steering test vehicle to realize a good angle tracking performance of the electric motor steer-by-wire system.
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.