Abstract
This paper presents the two-dimensional fuzzy sliding mode control of a field-sensed magnetic suspension system. The fuzzy rules include both the sliding manifold and its derivative. The fuzzy sliding mode control has advantages of the sliding mode control and the fuzzy control rules are minimized. Magnetic suspension systems are nonlinear and inherently unstable systems. The two-dimensional fuzzy sliding mode control can stabilize the nonlinear systems globally and attenuate chatter effectively. It is adequate to be applied to magnetic suspension systems. New design circuits of magnetic suspension systems are proposed in this paper. ARM Cortex-M3 microcontroller is utilized as a digital controller. The implemented driver, sensor, and control circuits are simpler, more inexpensive, and effective. This apparatus is satisfactory for engineering education. In the hands-on experiments, the proposed control scheme markedly improves performances of the field-sensed magnetic suspension system.
Highlights
Sliding mode control (SMC) is a powerful nonlinear control technique [1, 2]
This paper has successfully demonstrated the 2DFSMC of a field-sensed magnetic suspension system (FSMSS)
For 2DFSMC technique, the sliding manifold and its derivative are both considered for fuzzy rules
Summary
Sliding mode control (SMC) is a powerful nonlinear control technique [1, 2]. SMC applies a discontinuous control signal that forces the system trajectory to slide along the boundaries of the control structures. The FSMC integrates the sliding mode control (SMC) and the fuzzy logic control (FLC). The two-dimensional fuzzy sliding mode control (2DFSMC) improves the problem of chattering effectively. Cho et al [10] provided an experimental comparison between a sliding mode controller and a classical controller for a magnetic levitation system (MLS). In [17], the sliding-mode control system using a radial basis function network (RBFN) is proposed to control the position of a levitated object of a MLS. In [18], a robust dynamic sliding mode control system using a recurrent Elman neural network (RENN) is proposed to control the position of a levitated object of a MLS. Li and Wu [20] proposed the two-dimensional fuzzy sliding mode control (2DFSMC) of the MLS.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
