Pub Date : 2023-04-05DOI: 10.1080/00051144.2023.2194097
M. Shanmuga sundari, Vijaya Chandra Jadala
In neurological field, Cerebellar Ataxia (CA) prediction is done with Gait values of human actions. The Analysis of Gait (AoG) may lead the good treatment. The goal of this work was to develop a machine-learning-based model for predicting AoG using the poor gait patterns that occur before AoG. While executing designed AoG-provoking walking tasks, an accelerometer was connected to the lower back of 21 subjects with 12 different walking positions to gather acceleration impulses. The exercise was walking for one minute at each of 12 varied walking speeds on a split-belt treadmill in the range [0.6, 1.7] m/s in 0.1 m/s increments. To reduce the effects of weariness, the speed sequence was randomized and kept a secret from the subjects. Machine-learning algorithms like support vector machine (SVM) and k-nearest neighbours (KNN) have been tested in existing research studies. These algorithms perform well when the amount of data is little and the classification is binary. SVM, KNN, decision trees, and XGBoost algorithms have all been used in the proposed study on the CA data set. We discovered that the AdaBoost algorithm provides a more accurate categorization of the severity of CA disease.
{"title":"Neurological disease prediction using impaired gait analysis for foot position in cerebellar ataxia by ensemble approach","authors":"M. Shanmuga sundari, Vijaya Chandra Jadala","doi":"10.1080/00051144.2023.2194097","DOIUrl":"https://doi.org/10.1080/00051144.2023.2194097","url":null,"abstract":"In neurological field, Cerebellar Ataxia (CA) prediction is done with Gait values of human actions. The Analysis of Gait (AoG) may lead the good treatment. The goal of this work was to develop a machine-learning-based model for predicting AoG using the poor gait patterns that occur before AoG. While executing designed AoG-provoking walking tasks, an accelerometer was connected to the lower back of 21 subjects with 12 different walking positions to gather acceleration impulses. The exercise was walking for one minute at each of 12 varied walking speeds on a split-belt treadmill in the range [0.6, 1.7] m/s in 0.1 m/s increments. To reduce the effects of weariness, the speed sequence was randomized and kept a secret from the subjects. Machine-learning algorithms like support vector machine (SVM) and k-nearest neighbours (KNN) have been tested in existing research studies. These algorithms perform well when the amount of data is little and the classification is binary. SVM, KNN, decision trees, and XGBoost algorithms have all been used in the proposed study on the CA data set. We discovered that the AdaBoost algorithm provides a more accurate categorization of the severity of CA disease.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"540 - 549"},"PeriodicalIF":1.9,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44612998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1080/00051144.2023.2196114
K. T., V. J.
Cervical malignant growth is the fourth most typical reason for disease demise in women around the world. In developing countries, women don’t approach sufficient screening methods because of the costly procedures to undergo examination regularly, scarce awareness and lack of access to the medical centre. Recently, deep learning-based radiomic methods have been introduced in differentiating vessel invasion from non-vessel invasion in Cervical Cancer (CC) by multi-parametric Magnetic Resonance Imaging (MRI). However, this model doesn’t produce sufficient results. In this work, the MRI images are initially pre-processed using bilateral filtering. After pre-processing, the image is segmented by modified U-Net model in order to identify the cancerous region. Extraction of deep semantic information from images by using residual blocks in the processes of contractions and expansions. The last layer of the contracting route uses tightly coupled convolutions in the second phase to speed up feature recycling and feature propagation. It was inferred from the observations that the proposed model was effective as a predictive tool for detecting vessel invasions in preoperative early stages of CC. Proposed model produces 94.00% detection accuracy which is better than the other existing methods.
{"title":"An automated cervical cancer detection scheme using deeply supervised shuffle attention modified convolutional neural network model","authors":"K. T., V. J.","doi":"10.1080/00051144.2023.2196114","DOIUrl":"https://doi.org/10.1080/00051144.2023.2196114","url":null,"abstract":"Cervical malignant growth is the fourth most typical reason for disease demise in women around the world. In developing countries, women don’t approach sufficient screening methods because of the costly procedures to undergo examination regularly, scarce awareness and lack of access to the medical centre. Recently, deep learning-based radiomic methods have been introduced in differentiating vessel invasion from non-vessel invasion in Cervical Cancer (CC) by multi-parametric Magnetic Resonance Imaging (MRI). However, this model doesn’t produce sufficient results. In this work, the MRI images are initially pre-processed using bilateral filtering. After pre-processing, the image is segmented by modified U-Net model in order to identify the cancerous region. Extraction of deep semantic information from images by using residual blocks in the processes of contractions and expansions. The last layer of the contracting route uses tightly coupled convolutions in the second phase to speed up feature recycling and feature propagation. It was inferred from the observations that the proposed model was effective as a predictive tool for detecting vessel invasions in preoperative early stages of CC. Proposed model produces 94.00% detection accuracy which is better than the other existing methods.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"518 - 528"},"PeriodicalIF":1.9,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43442956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-04DOI: 10.1080/00051144.2023.2195218
D. Pavithra, R. Nidhya, S. Shanthi, P. Priya
Patients now want a contemporary, advanced healthcare system that is faster and more individualized and that can keep up with their changing needs. An edge computing environment, in conjunction with 5G speeds and contemporary computing techniques, is the solution for the latency and energy efficiency criteria to be satisfied for a real-time collection and analysis of health data. The feature of optimum computing approaches, including encryption, authentication, and classification that are employed on the devices deployed in an edge-computing architecture, has been ignored by previous healthcare systems, which have concentrated on novel fog architecture and sensor kinds. To avoid this problem in this paper, an Optimized Deep Recurrent Neural Network (O-DRNN) model is used with a multitier secured architecture. Initially, the data obtained from the patient are sent to the healthcare server in edge computing and the processed data are stored in the cloud using the Elliptic Curve Key Agreement Scheme (ECKAS) security model. The data is pre-processed and optimal features are selected using the Particle Swarm Optimization (PSO) algorithm. O-DRNN algorithm hyper-parameters are optimized using Bayesian optimization for better diagnosis. The proposed work offers superior outcomes in terms of accuracy and encryption latency while using computational cloud services.
{"title":"A secured and optimized deep recurrent neural network (DRNN) scheme for remote health monitoring system with edge computing","authors":"D. Pavithra, R. Nidhya, S. Shanthi, P. Priya","doi":"10.1080/00051144.2023.2195218","DOIUrl":"https://doi.org/10.1080/00051144.2023.2195218","url":null,"abstract":"Patients now want a contemporary, advanced healthcare system that is faster and more individualized and that can keep up with their changing needs. An edge computing environment, in conjunction with 5G speeds and contemporary computing techniques, is the solution for the latency and energy efficiency criteria to be satisfied for a real-time collection and analysis of health data. The feature of optimum computing approaches, including encryption, authentication, and classification that are employed on the devices deployed in an edge-computing architecture, has been ignored by previous healthcare systems, which have concentrated on novel fog architecture and sensor kinds. To avoid this problem in this paper, an Optimized Deep Recurrent Neural Network (O-DRNN) model is used with a multitier secured architecture. Initially, the data obtained from the patient are sent to the healthcare server in edge computing and the processed data are stored in the cloud using the Elliptic Curve Key Agreement Scheme (ECKAS) security model. The data is pre-processed and optimal features are selected using the Particle Swarm Optimization (PSO) algorithm. O-DRNN algorithm hyper-parameters are optimized using Bayesian optimization for better diagnosis. The proposed work offers superior outcomes in terms of accuracy and encryption latency while using computational cloud services.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"508 - 517"},"PeriodicalIF":1.9,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45205482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1080/00051144.2023.2192380
M. Helaimi, H. Gabbar, R. Taleb, M. Regad
In this paper, we introduce a Coefficient Diagram Method (CDM) to design a conventional PID controller. This controller is used to decrease the frequency fluctuations of a microgrid system composed of two renewable energy sources (WTG and STPG) and four controlled elements (UC, FESS, BESS and DEG). The method compares two characteristic polynomials of the same order:, the coefficients of the first polynomial are a function of microgrid parameters and the unknown gains of the PID controller. The second is called the target polynomial; its coefficients are calculated by choosing the stability indices and the equivalent time constant to satisfy the desired performances of the closed-loop system. Mathematically, the order of the polynomial controller determines the type of linear system of equations to solve: undetermined or overdetermined. In our application, the least squares method is used to find an approximate solution to the overdetermined system resulting from this comparison. Digital simulation is performed to test the performance of the microgrid controlled by the CDM-PID controller. The obtained results are compared with two recently published works where the parameters of the PID controllers are tuned by DE and chaotic PSO algorithms. The results show that the CDM-PID controller gives better performance.
{"title":"Frequency control scheme based on the CDM-PID controller for the hybrid microgrid system with stochastic renewable generators","authors":"M. Helaimi, H. Gabbar, R. Taleb, M. Regad","doi":"10.1080/00051144.2023.2192380","DOIUrl":"https://doi.org/10.1080/00051144.2023.2192380","url":null,"abstract":"In this paper, we introduce a Coefficient Diagram Method (CDM) to design a conventional PID controller. This controller is used to decrease the frequency fluctuations of a microgrid system composed of two renewable energy sources (WTG and STPG) and four controlled elements (UC, FESS, BESS and DEG). The method compares two characteristic polynomials of the same order:, the coefficients of the first polynomial are a function of microgrid parameters and the unknown gains of the PID controller. The second is called the target polynomial; its coefficients are calculated by choosing the stability indices and the equivalent time constant to satisfy the desired performances of the closed-loop system. Mathematically, the order of the polynomial controller determines the type of linear system of equations to solve: undetermined or overdetermined. In our application, the least squares method is used to find an approximate solution to the overdetermined system resulting from this comparison. Digital simulation is performed to test the performance of the microgrid controlled by the CDM-PID controller. The obtained results are compared with two recently published works where the parameters of the PID controllers are tuned by DE and chaotic PSO algorithms. The results show that the CDM-PID controller gives better performance.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"484 - 495"},"PeriodicalIF":1.9,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45448804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-29DOI: 10.1080/00051144.2023.2190694
Youguo He, Yu Zhou, Dapeng Wang, S. Liu, Xiu-ling Wei
In this paper, a novel tracking control strategy is proposed to address the problem of stabilization of a class of nonlinear time delay systems with time-varying full-state constraints. The effect of the nonlinear system resulting from the time delays is canceled out with the utilization of the novel iterative procedures optimized by dynamic surface control (DSC) and the appropriate time-varying asymmetric barrier Lyapunov functions (ABLFs) are employed to stem the violation of time-varying states constraints. Finally, it is proved that the proposed control method guarantees the uniformly ultimate boundedness of all the signals in the closed-loop system, meanwhile, the tracking errors converge to a small interval. The effectiveness of the presented control strategy is confirmed by a simulation example provided in this paper.
{"title":"Stabilization analysis of a class of nonlinear time delay systems with time-varying full-state constraints","authors":"Youguo He, Yu Zhou, Dapeng Wang, S. Liu, Xiu-ling Wei","doi":"10.1080/00051144.2023.2190694","DOIUrl":"https://doi.org/10.1080/00051144.2023.2190694","url":null,"abstract":"In this paper, a novel tracking control strategy is proposed to address the problem of stabilization of a class of nonlinear time delay systems with time-varying full-state constraints. The effect of the nonlinear system resulting from the time delays is canceled out with the utilization of the novel iterative procedures optimized by dynamic surface control (DSC) and the appropriate time-varying asymmetric barrier Lyapunov functions (ABLFs) are employed to stem the violation of time-varying states constraints. Finally, it is proved that the proposed control method guarantees the uniformly ultimate boundedness of all the signals in the closed-loop system, meanwhile, the tracking errors converge to a small interval. The effectiveness of the presented control strategy is confirmed by a simulation example provided in this paper.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"496 - 507"},"PeriodicalIF":1.9,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47167713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-18DOI: 10.1080/00051144.2023.2190866
Mustafa Ayyıldız, U. Tilki
ABSTRACT In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.
{"title":"Adaptive sliding mode based fault tolerant control of wheeled mobile robots","authors":"Mustafa Ayyıldız, U. Tilki","doi":"10.1080/00051144.2023.2190866","DOIUrl":"https://doi.org/10.1080/00051144.2023.2190866","url":null,"abstract":"ABSTRACT In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"467 - 483"},"PeriodicalIF":1.9,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42367133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-18DOI: 10.1080/00051144.2023.2187525
Ayesha Shaik, V. Masilamani
E-health care is an emerging field where health services and information are delivered and offered over the Internet. So the health information of the patients communicated over the Internet has to protect the privacy of the patients. The patient information is embedded into the health record and communicated online which also induces degradation to the original information. So, in this article, a zero watermarking scheme for privacy protection is proposed which protects the privacy and also eliminates the degradation done during embedding of patient information into the health record. This method is based on simple linear iterative clustering (SLIC) superpixels and partial pivoting lower triangular upper triangular (PPLU) factorization. The novelty of this article is that the use of SLIC superpixels and PPLU decomposition for the privacy protection of medical images (MI). The original image is subjected to SLIC segmentation and non-overlapping high entropy blocks are selected. On the selected blocks discrete wavelet transform (DWT) is applied and those blocks undergo PPLU factorization to get three matrices, L, U and P, which are lower triangular, upper triangular and permutation matrix respectively. The product matrix is used to construct a zero-watermark. The technique has been experimented on the UCID, BOWS and SIPI databases. The test results demonstrate that this work shows high robustness which is measured using normalized correlation (NC) and bit error rate (BER) against the listed attacks.
{"title":"Zero watermarking scheme for privacy protection in e-Health care","authors":"Ayesha Shaik, V. Masilamani","doi":"10.1080/00051144.2023.2187525","DOIUrl":"https://doi.org/10.1080/00051144.2023.2187525","url":null,"abstract":"E-health care is an emerging field where health services and information are delivered and offered over the Internet. So the health information of the patients communicated over the Internet has to protect the privacy of the patients. The patient information is embedded into the health record and communicated online which also induces degradation to the original information. So, in this article, a zero watermarking scheme for privacy protection is proposed which protects the privacy and also eliminates the degradation done during embedding of patient information into the health record. This method is based on simple linear iterative clustering (SLIC) superpixels and partial pivoting lower triangular upper triangular (PPLU) factorization. The novelty of this article is that the use of SLIC superpixels and PPLU decomposition for the privacy protection of medical images (MI). The original image is subjected to SLIC segmentation and non-overlapping high entropy blocks are selected. On the selected blocks discrete wavelet transform (DWT) is applied and those blocks undergo PPLU factorization to get three matrices, L, U and P, which are lower triangular, upper triangular and permutation matrix respectively. The product matrix is used to construct a zero-watermark. The technique has been experimented on the UCID, BOWS and SIPI databases. The test results demonstrate that this work shows high robustness which is measured using normalized correlation (NC) and bit error rate (BER) against the listed attacks.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"453 - 466"},"PeriodicalIF":1.9,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44824833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-14DOI: 10.1080/00051144.2023.2173121
T. Jayakumar, G. Ramani, P. Jamuna, B. Ramraj, G. Chandrasekaran, C. Maheswari, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji
Pulse width modulation for Selective Harmonics Elimination (SHE) is mostly employed in the reduction of lower order harmonics. The PV system in this research provides input voltage to the reduced switch 31-level inverter, which is based on the Artificial Bee Colony algorithm. With a high gain DC-DC single-ended primary-inductor converter (SEPIC), the PV panel output voltage is kept constant. The Grey wolf optimization algorithm (GWO) approach is used to get the most power out PV scheme. Multi Carrier modulation, a high-frequency modulation technology, is also used in this novel design of the inverter to reduce upper order harmonics. The suggested Artificial Bee Colony (ABC) algorithm, harmonics is compared to a SHE technique based on a genetic algorithm. The hardware findings were confirmed using DSPIC30F2010 controller simulation, and the recommended system was validated using Matlab simulation.
{"title":"Investigation and validation of PV fed reduced switch asymmetric multilevel inverter using optimization based selective harmonic elimination technique","authors":"T. Jayakumar, G. Ramani, P. Jamuna, B. Ramraj, G. Chandrasekaran, C. Maheswari, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji","doi":"10.1080/00051144.2023.2173121","DOIUrl":"https://doi.org/10.1080/00051144.2023.2173121","url":null,"abstract":"Pulse width modulation for Selective Harmonics Elimination (SHE) is mostly employed in the reduction of lower order harmonics. The PV system in this research provides input voltage to the reduced switch 31-level inverter, which is based on the Artificial Bee Colony algorithm. With a high gain DC-DC single-ended primary-inductor converter (SEPIC), the PV panel output voltage is kept constant. The Grey wolf optimization algorithm (GWO) approach is used to get the most power out PV scheme. Multi Carrier modulation, a high-frequency modulation technology, is also used in this novel design of the inverter to reduce upper order harmonics. The suggested Artificial Bee Colony (ABC) algorithm, harmonics is compared to a SHE technique based on a genetic algorithm. The hardware findings were confirmed using DSPIC30F2010 controller simulation, and the recommended system was validated using Matlab simulation.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"441 - 452"},"PeriodicalIF":1.9,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47673503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-13DOI: 10.1080/00051144.2023.2170058
Yuming Yin, Z. Fu, Yan Lu
This paper presents an online adaptive approximate solution for the optimal tracking control problem of model-free nonlinear systems. Firstly, a dynamic neural network identifier with properly designed weights updating laws is developed to identify the unknown dynamics. Then an adaptive optimal tracking control policy consisting of two terms is proposed, i.e. a steady-state control term is established to ensure the desired tracking performance at the steady state, and an optimal control term is proposed to ensure the optimal tracking error dynamics optimally. The composite Lyapunov method is used to analyse the stability of the closed-loop system. Two simulation examples are presented to demonstrate the effectiveness of the proposed method.
{"title":"Online adaptive optimal tracking control for model-free nonlinear systems via a dynamic neural network","authors":"Yuming Yin, Z. Fu, Yan Lu","doi":"10.1080/00051144.2023.2170058","DOIUrl":"https://doi.org/10.1080/00051144.2023.2170058","url":null,"abstract":"This paper presents an online adaptive approximate solution for the optimal tracking control problem of model-free nonlinear systems. Firstly, a dynamic neural network identifier with properly designed weights updating laws is developed to identify the unknown dynamics. Then an adaptive optimal tracking control policy consisting of two terms is proposed, i.e. a steady-state control term is established to ensure the desired tracking performance at the steady state, and an optimal control term is proposed to ensure the optimal tracking error dynamics optimally. The composite Lyapunov method is used to analyse the stability of the closed-loop system. Two simulation examples are presented to demonstrate the effectiveness of the proposed method.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"431 - 440"},"PeriodicalIF":1.9,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41467835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a new approach of fault-tolerant control (FTC) for the transmission line as a neutral variable time-delay system. The main goal of this work guarantees faulty neutral variable time delay system stabilization using the state feedback control design based on Lyapunov function and the Linear Matrix Inequality resolution. The use of the FTC method is to achieve actuator and sensor fault compensation. This method is based on two steps. The first one is the synthesis of a nominal control, which remains to maintain the closed-loop system stability. The second step is based on adding a new control law to the nominal one to compensate the fault effect on system behaviour and maintain the desired performance in the closed loop system. Then, a conception of an adaptive observer is used to detect and estimate the fault. Finally, the developed approach is applied for the transmission line. The given results are presented to prove the effectiveness of this approach.
{"title":"Fault diagnosis and fault-tolerant control design for neutral time delay system","authors":"Benjemaa Rabeb, Elhsoumi Aicha, Abdelkrim Mohamed Naceur","doi":"10.1080/00051144.2023.2176855","DOIUrl":"https://doi.org/10.1080/00051144.2023.2176855","url":null,"abstract":"This paper presents a new approach of fault-tolerant control (FTC) for the transmission line as a neutral variable time-delay system. The main goal of this work guarantees faulty neutral variable time delay system stabilization using the state feedback control design based on Lyapunov function and the Linear Matrix Inequality resolution. The use of the FTC method is to achieve actuator and sensor fault compensation. This method is based on two steps. The first one is the synthesis of a nominal control, which remains to maintain the closed-loop system stability. The second step is based on adding a new control law to the nominal one to compensate the fault effect on system behaviour and maintain the desired performance in the closed loop system. Then, a conception of an adaptive observer is used to detect and estimate the fault. Finally, the developed approach is applied for the transmission line. The given results are presented to prove the effectiveness of this approach.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":"64 1","pages":"422 - 430"},"PeriodicalIF":1.9,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42332921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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