Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642519
Ching Yee Yong, K. Hamid, Jung Heng Chieng
SCADA stands for Supervisory Control and Data Acquisition. It helps industrials to control process remotely, monitor the real time data, interact directly with transmitter, control valves, motor through human interface technology and lastly to record data. Most of the SCADA system was installed for industrial automation. In housing distribution switchboard (DB), it is not common to install SCADA system. A DB with SCADA system that is capable to collect and transmit data to the control unit such as personal computer (PC) or smartphone and further remote control was proposed. Since it is dangerous when there is sudden cut-off of power supply of the main switch. Some user may face difficulty to re-activate the circuit breaker or main switch. The main objective is to integrate the serial communication between the IoT and the control unit. The fault alarm message will be sent to user when there is fault. The first domestic system for electrical energy monitoring by remote controlling using SCADA and human machine interface was developed. The main component of the proposed system is Arduino Uno, 8 channels relay module, miniature circuit breaker (MCB), auto manual AC contactor, and switch mode power supply (SMPS). Main supply is from the AC voltage 240V to the switchboard. The main switch is connected to the auto manual AC contactor for the auto and manual control of the electrical flow. A smart domestic switchboard was designed with the function of sending out the fault alarm message when overload (over current) happened. The proposed system is reliable, safer, environmentally sound and achieved 80% of accuracy for notification sent out and 100% of tripped if overload was detected.
{"title":"Domestic Electrical Energy Monitoring and Alerting Using SCADA and IoT","authors":"Ching Yee Yong, K. Hamid, Jung Heng Chieng","doi":"10.1109/ICIAS49414.2021.9642519","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642519","url":null,"abstract":"SCADA stands for Supervisory Control and Data Acquisition. It helps industrials to control process remotely, monitor the real time data, interact directly with transmitter, control valves, motor through human interface technology and lastly to record data. Most of the SCADA system was installed for industrial automation. In housing distribution switchboard (DB), it is not common to install SCADA system. A DB with SCADA system that is capable to collect and transmit data to the control unit such as personal computer (PC) or smartphone and further remote control was proposed. Since it is dangerous when there is sudden cut-off of power supply of the main switch. Some user may face difficulty to re-activate the circuit breaker or main switch. The main objective is to integrate the serial communication between the IoT and the control unit. The fault alarm message will be sent to user when there is fault. The first domestic system for electrical energy monitoring by remote controlling using SCADA and human machine interface was developed. The main component of the proposed system is Arduino Uno, 8 channels relay module, miniature circuit breaker (MCB), auto manual AC contactor, and switch mode power supply (SMPS). Main supply is from the AC voltage 240V to the switchboard. The main switch is connected to the auto manual AC contactor for the auto and manual control of the electrical flow. A smart domestic switchboard was designed with the function of sending out the fault alarm message when overload (over current) happened. The proposed system is reliable, safer, environmentally sound and achieved 80% of accuracy for notification sent out and 100% of tripped if overload was detected.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115435721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642687
A. Sadiq, N. Yahya
Neural Networks are indispensable tools in adaptive signal processing. Multi-layer perceptron (MLP) neural network is one of the most widely used neural network architecture. The performance is highly subjective to the optimization of learning parameters. In this study, we propose a learning algorithm for the training of MLP models. Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. It is a type of stochastic gradient descent algorithm where performance is governed by eigen spread of the input signal correlation matrix. In order to accelerate the performance, we design a combination of integral and fractional gradient terms. The proposed fractional back-propagation multi-layer perceptron (FBP-MLP) method is based on fractional calculus and it utilizes the concept of fractional power gradient which provides complementary information about the cost function that helps in rapid convergence. For the validation of our claim, we implemented leukemia cancer classification task and compared our method with standard BPMLP method. The proposed FBP-MLP method outperformed the conventional BP-MLP algorithm both in terms of convergence rate and test accuracy.
{"title":"Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks","authors":"A. Sadiq, N. Yahya","doi":"10.1109/ICIAS49414.2021.9642687","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642687","url":null,"abstract":"Neural Networks are indispensable tools in adaptive signal processing. Multi-layer perceptron (MLP) neural network is one of the most widely used neural network architecture. The performance is highly subjective to the optimization of learning parameters. In this study, we propose a learning algorithm for the training of MLP models. Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. It is a type of stochastic gradient descent algorithm where performance is governed by eigen spread of the input signal correlation matrix. In order to accelerate the performance, we design a combination of integral and fractional gradient terms. The proposed fractional back-propagation multi-layer perceptron (FBP-MLP) method is based on fractional calculus and it utilizes the concept of fractional power gradient which provides complementary information about the cost function that helps in rapid convergence. For the validation of our claim, we implemented leukemia cancer classification task and compared our method with standard BPMLP method. The proposed FBP-MLP method outperformed the conventional BP-MLP algorithm both in terms of convergence rate and test accuracy.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115344597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642688
H. Ramza, Emas Fiqry Nurdwiprasetio, Aditya Ervansyah, Sugianto, Saeed Salem Bahashwan, M. Khir
This paper describes 2-D modes analysis on the waveguide structure. Micro-Ring Resonator formation was simulated to able the chemical vapor detection by using COMSOL Multiphysics application. We present the simulation of mode analysis from a Micro-ring Resonator as sensing the chemical vapor. By implementing the device parameters. We have seen from the simulator that the optical mode is handled equally within the ring. Using the variation of effective refractive index, our simulator result of ring resonator generated the mode analysis in two-dimension perspective. We conclude that the ring resonator device has potential for generating the certain wavelength.
{"title":"2-D Modes Analysis of Micro-Ring Resonator: In case of chemical vapor sensing","authors":"H. Ramza, Emas Fiqry Nurdwiprasetio, Aditya Ervansyah, Sugianto, Saeed Salem Bahashwan, M. Khir","doi":"10.1109/ICIAS49414.2021.9642688","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642688","url":null,"abstract":"This paper describes 2-D modes analysis on the waveguide structure. Micro-Ring Resonator formation was simulated to able the chemical vapor detection by using COMSOL Multiphysics application. We present the simulation of mode analysis from a Micro-ring Resonator as sensing the chemical vapor. By implementing the device parameters. We have seen from the simulator that the optical mode is handled equally within the ring. Using the variation of effective refractive index, our simulator result of ring resonator generated the mode analysis in two-dimension perspective. We conclude that the ring resonator device has potential for generating the certain wavelength.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117001511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642570
P. Divya, B. Aruna Devi, Srinivasan Prabakar, K. Porkumaran, R. Kannan, N. M. Nor, I. Elamvazuthi
Contemporary application of machine learning has paved a way for the medical diagnosis automation without any manual intervention. Once such application is early deduction of the epileptic seizures. Earlier identification of seizures aids specialists towards diagnosis. This paper analyzes on the detection of EEG epileptic seizures using Autoencoders, Convolutional Neural Network (CNN), and a multi class Stacked Autoencoder-CN model. These prediction models were analyzed on the intracranial EEG data set from15 real time patients, CHB-MIT dataset and P300 dataset. The results in python, proved for Stacked Autoencoder-Convolution Neural (SAE-CN) model to give optimum and effective solution in terms of higher speed and reduction in training time of the classifier and better probability of 0.925. This analysis proposes the idea of pre-prepared systems for other EEGrelated applications.
{"title":"Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network","authors":"P. Divya, B. Aruna Devi, Srinivasan Prabakar, K. Porkumaran, R. Kannan, N. M. Nor, I. Elamvazuthi","doi":"10.1109/ICIAS49414.2021.9642570","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642570","url":null,"abstract":"Contemporary application of machine learning has paved a way for the medical diagnosis automation without any manual intervention. Once such application is early deduction of the epileptic seizures. Earlier identification of seizures aids specialists towards diagnosis. This paper analyzes on the detection of EEG epileptic seizures using Autoencoders, Convolutional Neural Network (CNN), and a multi class Stacked Autoencoder-CN model. These prediction models were analyzed on the intracranial EEG data set from15 real time patients, CHB-MIT dataset and P300 dataset. The results in python, proved for Stacked Autoencoder-Convolution Neural (SAE-CN) model to give optimum and effective solution in terms of higher speed and reduction in training time of the classifier and better probability of 0.925. This analysis proposes the idea of pre-prepared systems for other EEGrelated applications.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129636870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642545
F. E. Chinda, C. Sovuthy, M. Begam
This paper aims to demonstrate the design which improves the performance of RF Wireless Power Transfer (WPT) and charging system on the ground which can extend the charging voltage up to S.5 V and 12V for the transmitter to emit a low-power radio waves at the frequency of 500 MHz to 900 MHz the efficiency of 93% and the resonant frequency of 700 MHz at the surrounding space diameter of 300 mm are obtained.
{"title":"High-Efficiency Inductive Charging For High Frequency Wireless Power Transfer","authors":"F. E. Chinda, C. Sovuthy, M. Begam","doi":"10.1109/ICIAS49414.2021.9642545","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642545","url":null,"abstract":"This paper aims to demonstrate the design which improves the performance of RF Wireless Power Transfer (WPT) and charging system on the ground which can extend the charging voltage up to S.5 V and 12V for the transmitter to emit a low-power radio waves at the frequency of 500 MHz to 900 MHz the efficiency of 93% and the resonant frequency of 700 MHz at the surrounding space diameter of 300 mm are obtained.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121217023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642678
J. Tan, S. Cheab, G. S. Ng, S. Soeung
With the increasing demand of high-speed wireless communication, filter design plays an important role in selecting the targeted frequency spectrum to support higher data rates. This paper presents dual-mode waveguide filter with the aim to minimize the size of filter by having two modes in one single resonator and at the same time maintaining its performance in terms of losses and power handling capability. The filer is realized based on fourth-order Chebyshev polynomial. For demonstration, a dual-mode circular waveguide filter operated in 3.9 GHz is designed and simulated using the ANSYS High Frequency Structure Simulator (HFSS) software. It depicts a low passband insertion loss of 0.14 dB, good return loss performance of 15.11 dB within the passband and 30 dB of stopband rejection at 3.4 GHz, with all four transmission poles are observed within the passband. Both theoretical and simulation response are in good agreement with each other.
{"title":"Design & Simulation of Waveguide Filter for 5G Application","authors":"J. Tan, S. Cheab, G. S. Ng, S. Soeung","doi":"10.1109/ICIAS49414.2021.9642678","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642678","url":null,"abstract":"With the increasing demand of high-speed wireless communication, filter design plays an important role in selecting the targeted frequency spectrum to support higher data rates. This paper presents dual-mode waveguide filter with the aim to minimize the size of filter by having two modes in one single resonator and at the same time maintaining its performance in terms of losses and power handling capability. The filer is realized based on fourth-order Chebyshev polynomial. For demonstration, a dual-mode circular waveguide filter operated in 3.9 GHz is designed and simulated using the ANSYS High Frequency Structure Simulator (HFSS) software. It depicts a low passband insertion loss of 0.14 dB, good return loss performance of 15.11 dB within the passband and 30 dB of stopband rejection at 3.4 GHz, with all four transmission poles are observed within the passband. Both theoretical and simulation response are in good agreement with each other.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116376119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642647
R. Kannan, Bharanidharan Krishnan, Karantaraj Porkumaran, Srinivasan Prabakar, I. Elamvazuthi, Krishnamurthy Srinivasan
In most of the renewable energy sources power electronics devices are incorporated which introduce harmonics in grid connected system. In this paper, renewable energy sources are interconnected to grid by means of smart voltage source inverter which reduces harmonics. The main objective of this proposed work is to reduce Total Harmonic Distortion (THD). The smart voltage source inverter using Unified Power Quality Conditioner (UPQC) injects the power to the grid from photovoltaic sources to compensate reactive power demand. The effectiveness of the proposed schemes is demonstrated using MATLAB Simulink and provides better THD of grid connected Photovoltaic UPQC (PVUPQC).
{"title":"Power Quality Improvement Using UPQC for Grid Interconnected Renewable Energy Sources","authors":"R. Kannan, Bharanidharan Krishnan, Karantaraj Porkumaran, Srinivasan Prabakar, I. Elamvazuthi, Krishnamurthy Srinivasan","doi":"10.1109/ICIAS49414.2021.9642647","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642647","url":null,"abstract":"In most of the renewable energy sources power electronics devices are incorporated which introduce harmonics in grid connected system. In this paper, renewable energy sources are interconnected to grid by means of smart voltage source inverter which reduces harmonics. The main objective of this proposed work is to reduce Total Harmonic Distortion (THD). The smart voltage source inverter using Unified Power Quality Conditioner (UPQC) injects the power to the grid from photovoltaic sources to compensate reactive power demand. The effectiveness of the proposed schemes is demonstrated using MATLAB Simulink and provides better THD of grid connected Photovoltaic UPQC (PVUPQC).","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121686246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642605
M. Elkattan, H. Mostafa, A. Khalil
Fluxgate magnetic sensors measure weak magnetic fields in the range of 0.01nT to 1mT. They are one of the most used sensors in a wide range of applications because of their advantages over other types of sensors in a certain area of measured intensities and frequencies. The principle of operation of Fluxgate magnetometers is based on manipulating a nonlinear magnetic material as the sensing element to measure the strength of a surrounding dc or low-frequency ac magnetic field. During fluxgate design, the magnetic core is the most important element that determines the performance of the sensor. In this paper, evaluation of the response of the fluxgate core is done through numerical simulations under variable operating conditions. The fluxgate core is modeled using finite element method to involve the nonlinear hysteretic characteristics of the core into the conducted simulations. Thus, the proposed model helps to produce more reliable results about the behavior of the fluxgate sensing element. Furthermore, several simulations were conducted in this paper to provide a performance map for the fluxgate core that will help designers to choose the best operation conditions for the desired design.
{"title":"Responsivity of Fluxgate Sensing Element Under Different Excitation Conditions","authors":"M. Elkattan, H. Mostafa, A. Khalil","doi":"10.1109/ICIAS49414.2021.9642605","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642605","url":null,"abstract":"Fluxgate magnetic sensors measure weak magnetic fields in the range of 0.01nT to 1mT. They are one of the most used sensors in a wide range of applications because of their advantages over other types of sensors in a certain area of measured intensities and frequencies. The principle of operation of Fluxgate magnetometers is based on manipulating a nonlinear magnetic material as the sensing element to measure the strength of a surrounding dc or low-frequency ac magnetic field. During fluxgate design, the magnetic core is the most important element that determines the performance of the sensor. In this paper, evaluation of the response of the fluxgate core is done through numerical simulations under variable operating conditions. The fluxgate core is modeled using finite element method to involve the nonlinear hysteretic characteristics of the core into the conducted simulations. Thus, the proposed model helps to produce more reliable results about the behavior of the fluxgate sensing element. Furthermore, several simulations were conducted in this paper to provide a performance map for the fluxgate core that will help designers to choose the best operation conditions for the desired design.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134570152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642615
A. B. Aujih, M. I. Shapiai, F. Mériaudeau, T. Tang
Deep learning had become the leading methodology for detecting diabetic retinopathy (DR) from fundus images. Given a large samples of fundus images with labelled medical condition i.e., diabetic retinopathy, an efficient convolution neural network (CNN) classifier can be trained. Progress had been made previously by researchers to developed a good automatic detection of DR using deep learning architecture like convolution neural network (CNN). However, previously proposed architecture for detecting DR (DR-Net) are mainly based on previous architecture developed for natural images. Not much attention had been given on configuring DR-Net hyper-parameter i.e., depth. This paper developed a new CNN-based DR-Net architecture from scratch to detect referable diabetic retinopathy (rDR) from fundus images. This paper also report analysis of different number of DR-Net’s depth configuration. Compare to previous work on DR-Net, proposed architecture is simpler in terms of number of network layers while maintaining a considerably good performance.
{"title":"DR-Net with Convolution Neural Network","authors":"A. B. Aujih, M. I. Shapiai, F. Mériaudeau, T. Tang","doi":"10.1109/ICIAS49414.2021.9642615","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642615","url":null,"abstract":"Deep learning had become the leading methodology for detecting diabetic retinopathy (DR) from fundus images. Given a large samples of fundus images with labelled medical condition i.e., diabetic retinopathy, an efficient convolution neural network (CNN) classifier can be trained. Progress had been made previously by researchers to developed a good automatic detection of DR using deep learning architecture like convolution neural network (CNN). However, previously proposed architecture for detecting DR (DR-Net) are mainly based on previous architecture developed for natural images. Not much attention had been given on configuring DR-Net hyper-parameter i.e., depth. This paper developed a new CNN-based DR-Net architecture from scratch to detect referable diabetic retinopathy (rDR) from fundus images. This paper also report analysis of different number of DR-Net’s depth configuration. Compare to previous work on DR-Net, proposed architecture is simpler in terms of number of network layers while maintaining a considerably good performance.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127066830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-13DOI: 10.1109/ICIAS49414.2021.9642673
Mohd Heidir Mohd Shah, I. Mehedi, U. Al-Saggaf, A. H. Milyani, N. Saad, N. Yahaya
Balancing control of a double inverted pendulum is a great challenge as it is an unstable and non-linear system that requires fast control reaction. In this paper, a dynamic inversion controller is proposed for balancing control of a rotary double inverted pendulum system. The controller consists of two loops where the outer loop is responsible for generating desired position command while the inner loop takes the command to produce the actual control action. The robustness of the controller is added by the introduction of the sliding surface vector function. The effectiveness of the proposed controller is investigated through numerical simulations with two other types of controllers that are also tested for comparison purposes. The results prove that the proposed controller capable of balancing the rotary double inverted pendulum under the influence of disturbances, while comparisons with Sliding Mode Controller (SMC) and Linear Quadratic Regulator (LQR) in various scenarios suggested that the proposed controller was the most consistent controller as opposed to the other two.
{"title":"Balancing a Rotary Double Inverted Pendulum using Two-loops Adaptive Controller based on Dynamic Inversion Technique","authors":"Mohd Heidir Mohd Shah, I. Mehedi, U. Al-Saggaf, A. H. Milyani, N. Saad, N. Yahaya","doi":"10.1109/ICIAS49414.2021.9642673","DOIUrl":"https://doi.org/10.1109/ICIAS49414.2021.9642673","url":null,"abstract":"Balancing control of a double inverted pendulum is a great challenge as it is an unstable and non-linear system that requires fast control reaction. In this paper, a dynamic inversion controller is proposed for balancing control of a rotary double inverted pendulum system. The controller consists of two loops where the outer loop is responsible for generating desired position command while the inner loop takes the command to produce the actual control action. The robustness of the controller is added by the introduction of the sliding surface vector function. The effectiveness of the proposed controller is investigated through numerical simulations with two other types of controllers that are also tested for comparison purposes. The results prove that the proposed controller capable of balancing the rotary double inverted pendulum under the influence of disturbances, while comparisons with Sliding Mode Controller (SMC) and Linear Quadratic Regulator (LQR) in various scenarios suggested that the proposed controller was the most consistent controller as opposed to the other two.","PeriodicalId":212635,"journal":{"name":"2020 8th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116005083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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