A New Method of Controlling Active Magnetic Bearing through Neural Network

Achkar, Roger; Nasr, Chaiban; Miras, Jerome; Charara, Ali

doi:10.1109/cca.2006.286041

Cited by 2 publications

(5 citation statements)

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“…For Z1 and Z2, there is no improvement, but the results are acceptable. This is normal, since theoretically, curves Z1 and Z2 are obtained without overshoot values [11], while in real application, overshoot exists. The value for the X axis is not acceptable compared to the theory, but the effect of this axis is minimal for the behavior of the machine in real time.…”

Section: Application Of External Disturbancesmentioning

confidence: 94%

“…Thus, another strategy must be adopted. 2-The second case corresponds to the first neural method [11]. In this method, we will add the MLP to our system by taking the current vector like entry to the system and the vector force like exit.…”

Section: V-conclusionmentioning

confidence: 99%

“…The first consists in adding the MLP to the system by taking, for the network, the current vector like entry and the vector force like exit [11]. In the second method, the MLP controls the parameters of the PID in order to stabilize the system around the desired answers [12], [13].…”

Section: Introductionmentioning

confidence: 99%

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Real Time Application of an AMB Using MLP: Study of Robustness

Achkar

Nasr

2010

2010 Second International Conference on Computational Intelligence, Modelling and Simulation

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The active magnetic bearing AMB presents a solution for all technical problems since it ensures the total levitation of a body in space eliminating any mechanical contact between the rotor and the stator. The goal of our work is to show that the control of the AMB by Multilayer perceptrons MLP involves an improvement of the response compared to the control of the AMB by classical controllers. The study of robustness and the application of external disturbances, for a system controlled with MLP, were done in order to highlight the advantage of controlling this non linear system by neural networks. The study of the internal disturbance (the balourd) created while rotation is also applied in order to reduce the effect of this unbalance.Keywords-component: Non linear dynamics, adaptive control dynamics, adaptive learning network, artificial neural network applications, back propagation algorithm learning, and dynamic neural network control.

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Section: Application Of External Disturbancesmentioning

confidence: 94%

Section: V-conclusionmentioning

confidence: 99%

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Real Time Application of an AMB Using MLP: Study of Robustness

Achkar

Nasr

2010

2010 Second International Conference on Computational Intelligence, Modelling and Simulation

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“…The training was online. The training of the MLP (Achkar et al, 2006) was also online and in two stages direct and backpropagation.…”

Section: Control System Architecturementioning

confidence: 99%

“…The model of the broche takes into consideration the disturbances which will be applied to both plans of control. The mathematical equations of the model are developed in (Achkar et al, 2006). In fact, this model reflect the real behavior of the system.…”

Section: Introductionmentioning

confidence: 99%

Accurate Wavelet Neural Network for Efficient Controlling of an Active Magnetic Bearing System

Harkouss¹

2010

Journal of Computer Science

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Problem statement:The synthesis of a command by the neural network has an excellent advantage over the classical one such as PID. This study presented a fast and accurate Wavelet Neural Network (WNN) approach for efficient controlling of an Active Magnetic Bearing (AMB) system. Approach: The proposed approach combined neural network with the wavelet theory. Wavelet theory may be exploited in deriving a good initialization for the neural network and thus improved convergence of the learning algorithm. Results: We tested two control systems based on three types of neural controllers: Multiplayer Perceptron (MLP) controller, RBF Neural Network (RBFNN) controller and WNN controller. The simulation results show that the proposed WNN controller provides better performance comparing with standard PID controller, MLP and RBFNN controllers. Conclusion: The proposed WNN approach was shown to be useful in controlling nonlinear dynamic mechanical system, such as the AMB system used in this study.

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A New Method of Controlling Active Magnetic Bearing through Neural Network

Cited by 2 publications

References 0 publications

Real Time Application of an AMB Using MLP: Study of Robustness

Real Time Application of an AMB Using MLP: Study of Robustness

Accurate Wavelet Neural Network for Efficient Controlling of an Active Magnetic Bearing System

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