A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

Yao, Xuan; Chen, Zhaobo; Jiao, Yu

doi:10.1109/access.2019.2937191

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…Du et al [17] and Xu et al [18] investigated the electromagnetic aspects of the rotor AMBs systems. Zheng et al [19,20], Yao et al [21], and Gao et al [22] introduced different advanced control techniques to stabilize the lateral vibrations of the rotor AMBs system.…”

Section: Introductionmentioning

confidence: 99%

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

et al. 2020

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Rotor active magnetic bearings system is the most efficient supporting technique of high-speed rotating machinery. This work aims to explore the dynamical behaviors of the 6-pole rotor active magnetic bearings system for the first time. Two different control strategies are introduced to mitigate the considered system lateral vibrations and the corresponding whirling motions. The first control technique (Radial control) is suggested such that the attractive magnetic force in each pole is proportional to both the radial displacement and radial velocity of the rotating disk toward that pole. The second control strategy (Cartesian control) is proposed such that the controlled magnetic force in each pole is designed to be proportional to both the cartesian displacement and cartesian velocity of the rotating disk in two perpendicular directions. Based on the proposed control strategies, two nonlinear dynamical models are derived and then analyzed by applying perturbation methods. Different response-curves and bifurcation diagrams are plotted utilizing the disk spinning-speed and the disk eccentricity as bifurcation control parameters. The main obtained analytical and numerical results illustrated that the considered system can perform a circular forward whirling motion only under the first control technique, while four whirling modes (that are forward whirling , backward whirling, both forward and backward whirling, and oscillation along a straight line) are noticed in the second control method depending on the disk spinning speed. Moreover, it is found that the radial control method is robust against the system instability than the cartesian control one, especially at large disk eccentricity. However, the cartesian control method could exhibit a vibration suppression efficiency higher than the radial control one at small disk eccentricity.

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Section: Introductionmentioning

confidence: 99%

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

et al. 2020

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“…where I n ∈ R n×n is the identity matrix, A(p), B(p), E(p) are computed from ( 13) and ( 14), and C, D are given in (10).…”

Section: Parameter Set Mappingmentioning

confidence: 99%

“…In order to tackle the difficulties of the AMB control system, PID [5], H ∞ [6] and Q-parametrization [7], [8] were proposed as linear controllers. NL controllers including feedback linearization [9], sliding mode control [10], and fuzzy control [11] also were considered. Moreover, several control techniques are proposed for the NL systems which can be applied onto the AMB system, e.g., [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control Based on Linear Parameter-Varying Models of Active Magnetic Bearing Systems

et al. 2021

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Active magnetic bearing (AMB) system has been recently employed widely as an ideal equipment for high-speed rotating machines. The inherent challenges to control the system include instability, nonlinearity and constricted range of operation. Therefore, advanced control technology is essential to optimize AMB system performance. This paper presents an application of model predictive control (MPC) based on linear parameter-varying (LPV) models to control an AMB system subject to input and state constraints. For this purpose, an LPV model representation is derived from the nonlinear dynamic model of the AMB system. In order to provide stability guarantees and since the obtained LPV model has a large number of scheduling parameters, the parameter set mapping (PSM) technique is used to reduce their number. Based on the reduced model, a terminal cost and an ellipsoidal terminal set are determined offline and included into the MPC optimization problem which are the essential ingredients for guaranteeing the closed-loop asymptotic stability. Moreover, for recursive feasibility of the MPC optimization problem, a slack variable is included into its cost function. The goal of the proposed feedback control system is twofold. First is to demonstrate high performance by achieving stable levitation of the rotor shaft as well as high capability of reference tracking without violating input and state constraints, which increases the overall safety of the system under disturbances effects. Second is to provide a computationally tractable LPVMPC algorithm, which is a substantial requirement in practice for operating the AMB system with high performance over its full range. Therefore, we propose an LPVMPC scheme with frozen scheduling parameter over the prediction horizon of the MPC. Furthermore, we demonstrate in simulation that such frozen LPVMPC can achieve comparable performance to a more sophisticated LPVMPC scheme developed recently and a standard NL MPC (NMPC) approach. Moreover, to verify the performance of the proposed frozen LPVMPC, a comparison with a classical controller, which is commonly applied to the system in practice, is provided.INDEX TERMS Model predictive control, linear parameter-varying models, magnetic bearing systems, parameter set mapping, asymptotic stability.

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“…The active control of AMBs is a major area of research. In literature various controllers and controlling techniques have been designed and developed for the active control of AMBs system [13,14]. For intelligent control of an AMB system, fuzzy logicbased controllers have been mostly used.…”

Section: Introductionmentioning

confidence: 99%

Modelling, simulation and performance comparison of different membership functions based fuzzy logic control for an active magnetic bearing system

Gupta

Biswas⃰

Aljafari

et al. 2023

The Journal of Engineering

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In-house prototype model of an active magnetic bearing is built and using its physical parameter values a linearized transfer function of order two, is mathematically obtained for a specific point of operation. In this work, a closed loop active magnetic bearing system is proposed and controller for this closed loop is designed using fuzzy logic control. Two different fuzzy inference systems: Mamdani and Sugeno fuzzy inference system constructed individually with eleven different types of membership functions separately. The considered membership functions are-linear, generalized bell-shaped, Gaussian distribution based, quadratic, cubic polynomial and sigmoidal curve-based membership functions. Calculating the transient state and steady state parameter values together with the controller output allows to see how these various membership functions perform on the proposed closed loop active magnetic bearing system. Observed data shows that changing the fuzzy inference system for a specific membership function will result in 67.41% reduction in the overshoot value, 29.70% reduction in settling time value, 10.42% change in rise time value and 2.91% variation is peak time value. Practicality of all membership functions are analysed based on calculated data and their performances with the proposed model.

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A Dual-Loop Control Approach of Active Magnetic Bearing System for Rotor Tracking Control

Cited by 11 publications

References 28 publications

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

Model Predictive Control Based on Linear Parameter-Varying Models of Active Magnetic Bearing Systems

Modelling, simulation and performance comparison of different membership functions based fuzzy logic control for an active magnetic bearing system

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