Fault-tolerant Control for Maglev Suspension System Based on Simultaneous Stabilization

Zhang, Zhizhou; Li, Zhiqiang; Long-hua, She; Wen-sen, Chang

doi:10.1109/ical.2007.4338575

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…Finally, in Section 5, we draw conclusions about our work and highlight the implications for the maglev system. The maglev model we study is similar to that presented in [11,12,13,20]. Following the approach of [11,12,13], we make the simplification that the deformation of the track is zero.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear analysis of a maglev system with time-delayed feedback control

Zhang

Campbell

Huang

2011

Physica D: Nonlinear Phenomena

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This paper undertakes a nonlinear analysis of a model for a maglev system with time-delayed feedback. Using linear analysis, we determine constraints on the feedback control gains and the time delay which ensure stability of the maglev system. We then show that a Hopf bifurcation occurs at the linear stability boundary. To gain insight into the periodic motion which arises from the Hopf bifurcation, we use the method of multiple scales on the nonlinear model. This analysis shows that for practical operating ranges, the maglev system undergos both subcritical and supercritical bifurcations, and which give rise to unstable and stable limit cycles respectively. Numerical simulations confirm the theoretical results and indicate that unstable limit cycles may coexist with the stable equilibrium state. This means that large enough perturbations may cause instability in the system even if the feedback gains are such that the linear theory predicts that the equilibrium state is stable.

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Section: Introductionmentioning

confidence: 99%

Nonlinear analysis of a maglev system with time-delayed feedback control

Zhang

Campbell

Huang

2011

Physica D: Nonlinear Phenomena

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“…The data of sensor-controller network for maglev system are transmitted in numeric format, so events of data dropouts often occur. Together with the effectiveness of working condition and exterior disturbances, the uncertainties of system parameters always exist [1][2][3][4]. Integrality control is a special issue in the multivariable system, which is focusing on the failures of sensors or actuators.…”

Section: Introductionmentioning

confidence: 99%

“…Integrality control is a special issue in the multivariable system, which is focusing on the failures of sensors or actuators. The faults involves state-value lockup, saturation or open circuit and so on [3,4]. Thus, the designed controller needs to tolerate these failures and maintain the close-loop system stably.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Integrality Design for Maglev Networked Control System with Sensor Data Dropouts

Zhang

She

et al. 2010

AMM

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Considering the parameter’s uncertainty of Maglev networked control system, a fuzzy fault-tolerant control method possessing integrity based on T-S model was proposed with sensor data dropouts. When the sensor data of maglev networked system drops out, the state variable sampled at last control period is adopted by the controller. By setting different fault models of sensors and actuators, the fuzzy discrete close-loop model of maglev system was built with system parameter’s uncertainty. A passive integrality control method against sensor and actuator failures was designed with Linear Matrix Inequation (LMI). Simulation results well proved the effectiveness of the algorithm.

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“…Hence, being a critical fail-safe system substantially increases costs as it is requires a fault tolerant control structure [2]. Previous studies on fault tolerant controllers for MAGLEV suspensions, have concentrated on state feedback control [3], LMI-based H ∞ approaches [4], an encounter on simultaneous stabilisation [5], as well as duplex controllers to offer some form of hardware redundancy [6]. However, this paper presents a fault tolerant control which aims to reducing hardware sensor redundancy, while optimising the overall MAGLEV performance (both deterministic and ride quality terms).…”

Section: Introductionmentioning

confidence: 99%