2020
DOI: 10.1109/access.2020.2981840
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Robust Integral State Feedback Using Coefficient Diagram in Magnetic Levitation System

Abstract: Magnetic Levitation System or Maglev system is a modern and future technology that has many advantages and applications. Its characteristic is highly nonlinear, fast dynamics, and unstable, so it is challenging to make a suitable controller. The model of the Maglev system is in nonlinear state-space representation, and then feedback linearization is implemented to obtain the linear model system. Then, the integral state feedback control that tuned by the coefficient diagram method is implemented. The robustnes… Show more

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Cited by 15 publications
(11 citation statements)
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“…It does not need "landing" wheels because the suspension force is independent of the movement. However, at the same time, it is inherently unstable [30] and needs an active control system, which could be a point of failure. Still, the solution has a high technology readiness level (T RL = 9), and it is already used in Shanghai Transrapid maglev rail with an achieved speed of 430 km/h (not directly comparable to the proposed service speeds of the HTS).…”
Section: A Electro-magnetic Suspension (Ems)mentioning
confidence: 99%
“…It does not need "landing" wheels because the suspension force is independent of the movement. However, at the same time, it is inherently unstable [30] and needs an active control system, which could be a point of failure. Still, the solution has a high technology readiness level (T RL = 9), and it is already used in Shanghai Transrapid maglev rail with an achieved speed of 430 km/h (not directly comparable to the proposed service speeds of the HTS).…”
Section: A Electro-magnetic Suspension (Ems)mentioning
confidence: 99%
“…Control algorithms for magnetic levitation have long been a hot topic of research. In recent years, various control algorithms [15][16][17] have been proposed for magnetic levitation. They are no more than PID control, sliding mode control, fuzzy control, robust control, fractional order control, neural network control, etc., and the combinations of these.…”
Section: Introductionmentioning
confidence: 99%
“…In the literature, a number of traditional and soft-computing based PID controller design procedures are proposed and implemented by the researches for a class of systems [7,8]. The earlier works on the controller design confirms that the designing the controller for unstable system is very complex compared to the stable processes and the complexity also will increase with increase in the system's complexity [9][10][11][12][13][14][15].…”
Section: Introductionmentioning
confidence: 99%