Rotating electrical machines have several physical phenomena. Vibration is one of the important p... more Rotating electrical machines have several physical phenomena. Vibration is one of the important phenomena in the operation of rotating electrical machines. In addition, the vibration signal is considered an important source to have good information on the state of rotating electrical machinery. But this signal is rich in noise, especially under the presence of the bearing fault. This paper proposes a bearing fault diagnosis method based on EEMD and a denoising method based on three-sigma rule. In the first step, the EEMD decomposed the vibration signal into several components called Intrinsic Mode Functions (IMFs). After the calculation of the kurtosis of each IMF component, the signal is reconstructed by choosing components with higher values. To enhance periodic impulses, the three-sigma rule de-noising is applied to the reconstructed signal. As a final step, the envelope spectrum is used to determine the fault characteristic frequency. As a result of testing the bearing with inne...
In bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a reliable technique ... more In bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a reliable technique for treating rolling bearing vibration signals by dividing them into intrinsic mode functions (IMFs). Traditional methods used in EEMD consist of identifying IMFs containing the fault information and reconstructing them. However, an incorrect selection can result in the loss of useful IMFs or the addition of unnecessary ones. To overcome this drawback, this paper presents a novel method called combined modes ensemble empirical mode decomposition (CMEEMD) to directly obtain a combination of useful IMFs containing fault information. This is without needing to pass through the processes of IMF selection and reconstruction, as well as guaranteeing that no defect information is lost. Owing to the small signal-to-noise ratio, this makes it difficult to determine the fault information of a rolling bearing at the early stage. Therefore, improving noise reduction is an essential procedure for det...
Abstract: In this paper the speed control of a switched reluctance motor using fuzzy adaptive des... more Abstract: In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is proposed. First, a fuzzy adaptive design for speed control of SRM is descriped. Finally, the fuzzy adaptive controller is investigated. The effectiveness of the proposed control scheme is verified by numerical simulation. Digital simulation results shows that the designed adaptive fuzzy speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. 1.
020 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP), 2020
This paper proposes a cooperative evolution grey wolf optimizer algorithm for parameter identific... more This paper proposes a cooperative evolution grey wolf optimizer algorithm for parameter identification of a LuGre friction model. The considered friction is affecting the cart of an inverted pendulum system without the pendulum. The proposed identification technique optimizes both of the static and the dynamic parameters simultaneously. It takes the advantages of the exploration capability of the evolutionary algorithm and the exploitation capability of the grey wolf optimizer to handle such nonlinear and multimodal optimization problem. Simulations have been conducted to assess the effectiveness of the proposed cooperative identification technique, and it is found to be significant in identifying both of the static and dynamic parameters accurately.
This paper presents an evolution search methodology to automatically design a sectorial fuzzy con... more This paper presents an evolution search methodology to automatically design a sectorial fuzzy controller (SFC). The evolution search methodology is an integer-coded evolutionary algorithm (EA) which involves two stages. At first stage, the proposed EA optimises the SFC for disturbance-free model of the plant to be controlled. The principal aim of the second stage is the robustness enhancement of the evolved SFC resulting from the former stage. Specifically, the proposed EA looks in the vicinity of the best SFC found in the first stage for a SFC that provide the best compromise between the control performance for a disturbance-free model and for disturbed model. The sectorial properties were accommodated in the evolutionary search through a special parameterization of the fuzzy rule base (FRB) and the membership functions (MFs) of the SFC, repairing operator and special initialization of FRB chromosome part. Simulations were performed for direct-drive DC motor. The evolved SFC with the proposed design methodology found to provide very satisfactory performance under different types of disturbances. The trade-off between the accuracy performance and the robustness performance is also analysed during the evolution process.
IU-Journal of Electrical & Electronics Engineering, 2011
In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is pro... more In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is proposed. First, a fuzzy adaptive design for speed control of SRM is descriped. Finally, the fuzzy adaptive controller is investigated. The effectiveness of the proposed control scheme is verified by numerical simulation. Digital simulation results shows that the designed adaptive fuzzy speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance.
In this paper, for skin lesion segmentation, we propose an encoder-decoder structure based on U-N... more In this paper, for skin lesion segmentation, we propose an encoder-decoder structure based on U-Net, combining dilated convolution and pyramid pooling module (PPM). The dilated convolution computes the feature maps with a high spatial resolution instead to down-sampling feature maps, and the aim of pyramid pooling module is to obtain more contextual information (multi-scale context information with multi-scale pooling). on the official test set of ISBI 2016, and in terms of three evaluation metrics, Our proposed model is tested and achieved better performance over U-Net and another published method with (JC=82.7, DC=89.6, SE =92.0).
2017 6th International Conference on Systems and Control (ICSC)
This paper discusses the off-line identification of friction encountered in the cart motion of an... more This paper discusses the off-line identification of friction encountered in the cart motion of an inverted pendulum system. A LuGre model is chosen as the parametric model to represent this phenomenon. We propose an identification technique based on a differential evolution algorithm. The proposed identification technique distinguishes itself from the previous works by optimizing both of the static and the dynamic parameters simultaneously. This fact is possible through adopting closed loop identification where the velocity is controlled and using a sequence of static and dynamic signals as the reference signal to enhance the effects of the different friction phenomena. The simulation results demonstrate that the proposed differential evolution based identification method is effective in finding the parameters precisely despite the nonlinearity of the LuGre friction model and the coupling between the parameters.
In this paper, we propose a Random Scaling-based Bat Algorithm (RSBA) for parametric identificati... more In this paper, we propose a Random Scaling-based Bat Algorithm (RSBA) for parametric identification of a greenhouse thermal model. The proposition includes modifying the exploitation of the standard BA by making the scaling parameter changes randomly over the iterations. The proposed thermal model identification method has been assessed first on a simulated greenhouse thermal model with known parameters. The simulation results have shown the superiority of the proposed RSBA compared to the standard BA in term of convergence and performance accuracy. To experimentally investigate the proposed identification method, we used a greenhouse prototype under arid climate conditions located in M’ziraa, Biskra, Algeria. The obtained prediction results are found to be in a good agreement with the measured ones which show the effectiveness of the proposed RSBA in identifying the real greenhouse thermal model.
2012 IEEE International Conference on Complex Systems (ICCS), 2012
ABSTRACT The proportional and integral (PI) control plays an important role in industry. The PI c... more ABSTRACT The proportional and integral (PI) control plays an important role in industry. The PI controller is still widely used, due to its simplicity and effectiveness. For a system with predictable and low order dynamic behavior, PI control works well. However, it is far from perfect, its performance is not satisfactory in the case of nonlinear systems. Then, we have to find a new PI design or tuning method. This paper proposes a new design of adaptive fuzzy PI controllers to achieve optimal control performance. By applying numerical optimization, the fuzzy PI design problem is transferred to a numerical optimization problem. First, a fuzzy parameter tuner is built to generate initial PI parameters, including positions and shapes of fuzzy membership functions and scaling factors. Then the gradient-based sequential quadratic programming (SQP) algorithm is employed to minimize the cost function by adjusting the parameters. The proposed scheme is applied to control the speed of the switched reluctance motor. The effectiveness of this control technique is verified by numerical simulation.
Rotating electrical machines have several physical phenomena. Vibration is one of the important p... more Rotating electrical machines have several physical phenomena. Vibration is one of the important phenomena in the operation of rotating electrical machines. In addition, the vibration signal is considered an important source to have good information on the state of rotating electrical machinery. But this signal is rich in noise, especially under the presence of the bearing fault. This paper proposes a bearing fault diagnosis method based on EEMD and a denoising method based on three-sigma rule. In the first step, the EEMD decomposed the vibration signal into several components called Intrinsic Mode Functions (IMFs). After the calculation of the kurtosis of each IMF component, the signal is reconstructed by choosing components with higher values. To enhance periodic impulses, the three-sigma rule de-noising is applied to the reconstructed signal. As a final step, the envelope spectrum is used to determine the fault characteristic frequency. As a result of testing the bearing with inne...
In bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a reliable technique ... more In bearing fault diagnosis, ensemble empirical mode decomposition (EEMD) is a reliable technique for treating rolling bearing vibration signals by dividing them into intrinsic mode functions (IMFs). Traditional methods used in EEMD consist of identifying IMFs containing the fault information and reconstructing them. However, an incorrect selection can result in the loss of useful IMFs or the addition of unnecessary ones. To overcome this drawback, this paper presents a novel method called combined modes ensemble empirical mode decomposition (CMEEMD) to directly obtain a combination of useful IMFs containing fault information. This is without needing to pass through the processes of IMF selection and reconstruction, as well as guaranteeing that no defect information is lost. Owing to the small signal-to-noise ratio, this makes it difficult to determine the fault information of a rolling bearing at the early stage. Therefore, improving noise reduction is an essential procedure for det...
Abstract: In this paper the speed control of a switched reluctance motor using fuzzy adaptive des... more Abstract: In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is proposed. First, a fuzzy adaptive design for speed control of SRM is descriped. Finally, the fuzzy adaptive controller is investigated. The effectiveness of the proposed control scheme is verified by numerical simulation. Digital simulation results shows that the designed adaptive fuzzy speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. 1.
020 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP), 2020
This paper proposes a cooperative evolution grey wolf optimizer algorithm for parameter identific... more This paper proposes a cooperative evolution grey wolf optimizer algorithm for parameter identification of a LuGre friction model. The considered friction is affecting the cart of an inverted pendulum system without the pendulum. The proposed identification technique optimizes both of the static and the dynamic parameters simultaneously. It takes the advantages of the exploration capability of the evolutionary algorithm and the exploitation capability of the grey wolf optimizer to handle such nonlinear and multimodal optimization problem. Simulations have been conducted to assess the effectiveness of the proposed cooperative identification technique, and it is found to be significant in identifying both of the static and dynamic parameters accurately.
This paper presents an evolution search methodology to automatically design a sectorial fuzzy con... more This paper presents an evolution search methodology to automatically design a sectorial fuzzy controller (SFC). The evolution search methodology is an integer-coded evolutionary algorithm (EA) which involves two stages. At first stage, the proposed EA optimises the SFC for disturbance-free model of the plant to be controlled. The principal aim of the second stage is the robustness enhancement of the evolved SFC resulting from the former stage. Specifically, the proposed EA looks in the vicinity of the best SFC found in the first stage for a SFC that provide the best compromise between the control performance for a disturbance-free model and for disturbed model. The sectorial properties were accommodated in the evolutionary search through a special parameterization of the fuzzy rule base (FRB) and the membership functions (MFs) of the SFC, repairing operator and special initialization of FRB chromosome part. Simulations were performed for direct-drive DC motor. The evolved SFC with the proposed design methodology found to provide very satisfactory performance under different types of disturbances. The trade-off between the accuracy performance and the robustness performance is also analysed during the evolution process.
IU-Journal of Electrical & Electronics Engineering, 2011
In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is pro... more In this paper the speed control of a switched reluctance motor using fuzzy adaptive design is proposed. First, a fuzzy adaptive design for speed control of SRM is descriped. Finally, the fuzzy adaptive controller is investigated. The effectiveness of the proposed control scheme is verified by numerical simulation. Digital simulation results shows that the designed adaptive fuzzy speed controller realises a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance.
In this paper, for skin lesion segmentation, we propose an encoder-decoder structure based on U-N... more In this paper, for skin lesion segmentation, we propose an encoder-decoder structure based on U-Net, combining dilated convolution and pyramid pooling module (PPM). The dilated convolution computes the feature maps with a high spatial resolution instead to down-sampling feature maps, and the aim of pyramid pooling module is to obtain more contextual information (multi-scale context information with multi-scale pooling). on the official test set of ISBI 2016, and in terms of three evaluation metrics, Our proposed model is tested and achieved better performance over U-Net and another published method with (JC=82.7, DC=89.6, SE =92.0).
2017 6th International Conference on Systems and Control (ICSC)
This paper discusses the off-line identification of friction encountered in the cart motion of an... more This paper discusses the off-line identification of friction encountered in the cart motion of an inverted pendulum system. A LuGre model is chosen as the parametric model to represent this phenomenon. We propose an identification technique based on a differential evolution algorithm. The proposed identification technique distinguishes itself from the previous works by optimizing both of the static and the dynamic parameters simultaneously. This fact is possible through adopting closed loop identification where the velocity is controlled and using a sequence of static and dynamic signals as the reference signal to enhance the effects of the different friction phenomena. The simulation results demonstrate that the proposed differential evolution based identification method is effective in finding the parameters precisely despite the nonlinearity of the LuGre friction model and the coupling between the parameters.
In this paper, we propose a Random Scaling-based Bat Algorithm (RSBA) for parametric identificati... more In this paper, we propose a Random Scaling-based Bat Algorithm (RSBA) for parametric identification of a greenhouse thermal model. The proposition includes modifying the exploitation of the standard BA by making the scaling parameter changes randomly over the iterations. The proposed thermal model identification method has been assessed first on a simulated greenhouse thermal model with known parameters. The simulation results have shown the superiority of the proposed RSBA compared to the standard BA in term of convergence and performance accuracy. To experimentally investigate the proposed identification method, we used a greenhouse prototype under arid climate conditions located in M’ziraa, Biskra, Algeria. The obtained prediction results are found to be in a good agreement with the measured ones which show the effectiveness of the proposed RSBA in identifying the real greenhouse thermal model.
2012 IEEE International Conference on Complex Systems (ICCS), 2012
ABSTRACT The proportional and integral (PI) control plays an important role in industry. The PI c... more ABSTRACT The proportional and integral (PI) control plays an important role in industry. The PI controller is still widely used, due to its simplicity and effectiveness. For a system with predictable and low order dynamic behavior, PI control works well. However, it is far from perfect, its performance is not satisfactory in the case of nonlinear systems. Then, we have to find a new PI design or tuning method. This paper proposes a new design of adaptive fuzzy PI controllers to achieve optimal control performance. By applying numerical optimization, the fuzzy PI design problem is transferred to a numerical optimization problem. First, a fuzzy parameter tuner is built to generate initial PI parameters, including positions and shapes of fuzzy membership functions and scaling factors. Then the gradient-based sequential quadratic programming (SQP) algorithm is employed to minimize the cost function by adjusting the parameters. The proposed scheme is applied to control the speed of the switched reluctance motor. The effectiveness of this control technique is verified by numerical simulation.
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Papers by Ahmed chaouki Megherbi