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An adaptive robust controller for time delay maglev transportation systems
Authors:Reza Hamidi Milani  Hassan Zarabadipour  Reza Shahnazi
Institution:1. Department of Electrical Engineering, Imam Khomeini, International University, Qazvin, Iran;2. Islamic Azad University, South Tehran Branch, Tehran, Iran;1. School of Automation, China University of Geosciences, Wuhan 430074, China;2. Department of Electronics and Information Systems, Akita Prefectural University, 84-4 Tsuchiya-Ebinokuchi, Honjo, Akita 015-0055, Japan;3. Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;4. School of Science, Tianjin University of Technology and Education, Tianjin 300222, China
Abstract:For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov–Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
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