Pub Date : 1900-01-01DOI: 10.1109/CMI.2016.7413759
S. Chaudhuri, S. Mookherjee, D. Sanyal
An approximate system model for force tracking has been formulated here for a low-cost electrohydraulic system with a moderate-friction single-rod cylinder and a large-deadband proportional valve. A controller based on first-order sliding mode along with adaptation of controller parameters through Lyapunov functions has been developed to tackle the severe nonlinearities of the system. The system model has been recast in an input linearized form to develop the controller. A number of real-time experimental studies clearly established the controller as quite satisfactory.
{"title":"Adaptive force tracking in electrohydraulic system with first-order sliding mode control","authors":"S. Chaudhuri, S. Mookherjee, D. Sanyal","doi":"10.1109/CMI.2016.7413759","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413759","url":null,"abstract":"An approximate system model for force tracking has been formulated here for a low-cost electrohydraulic system with a moderate-friction single-rod cylinder and a large-deadband proportional valve. A controller based on first-order sliding mode along with adaptation of controller parameters through Lyapunov functions has been developed to tackle the severe nonlinearities of the system. The system model has been recast in an input linearized form to develop the controller. A number of real-time experimental studies clearly established the controller as quite satisfactory.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123860909","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413705
S. Sen, Shouvik Chakraborty, A. Dhar, A. Sutradhar
With increasing number of on-road transportation vehicles, the demand for passenger safety and comfort is inevitable. This inspired to develop technologically sophisticated automobiles with active safety systems that provide improved vehicle handling during critical driving situations. Yaw stability controller prevents the vehicle from spinning and drifting-out under loss of traction during a turning maneuver. This paper presents a controller design based on sliding mode principle with two-stage sliding surfaces considering yaw rate and body sideslip angle errors as primary and secondary surfaces respectively. A simplified model of the vehicle during a turning (Slalom + DLC) maneuver is been considered and the dynamic equations of the desired states were summed up and used to design the sliding surface. Computer simulations have been conducted to verify the proposed approach, with results indicating its effectiveness and robustness for yaw stability control.
{"title":"Two-stage adaptive sliding-mode controller for vehicle yaw stability using differential ABS","authors":"S. Sen, Shouvik Chakraborty, A. Dhar, A. Sutradhar","doi":"10.1109/CMI.2016.7413705","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413705","url":null,"abstract":"With increasing number of on-road transportation vehicles, the demand for passenger safety and comfort is inevitable. This inspired to develop technologically sophisticated automobiles with active safety systems that provide improved vehicle handling during critical driving situations. Yaw stability controller prevents the vehicle from spinning and drifting-out under loss of traction during a turning maneuver. This paper presents a controller design based on sliding mode principle with two-stage sliding surfaces considering yaw rate and body sideslip angle errors as primary and secondary surfaces respectively. A simplified model of the vehicle during a turning (Slalom + DLC) maneuver is been considered and the dynamic equations of the desired states were summed up and used to design the sliding surface. Computer simulations have been conducted to verify the proposed approach, with results indicating its effectiveness and robustness for yaw stability control.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125418592","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413782
Kishore Chimmula, Soumen Sen, Siva Ram KrishnaVadali
This article presents the characterization of inherent composite noise of a camera based position measurement system. Such an examination is needed to use a camera system as the position measurement sensor for direct implementation in Kalman filter based positional trajectory estimation of moving objects. Time and frequency domain analysis are carried out to characterize the noise in units of measured position values. The qualification of the noise to be White and Gaussian (WGN) makes it possible to use the position measurements for optimal estimation in a Kalman filter like estimation procedure. Further the observation is justified with an experiment of position tracking and subsequent trajectory estimation of a ball thrown under gravity with the help of linear kinematic model.
{"title":"Characterizing the composite noise of a camera used as a sensor for position estimation","authors":"Kishore Chimmula, Soumen Sen, Siva Ram KrishnaVadali","doi":"10.1109/CMI.2016.7413782","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413782","url":null,"abstract":"This article presents the characterization of inherent composite noise of a camera based position measurement system. Such an examination is needed to use a camera system as the position measurement sensor for direct implementation in Kalman filter based positional trajectory estimation of moving objects. Time and frequency domain analysis are carried out to characterize the noise in units of measured position values. The qualification of the noise to be White and Gaussian (WGN) makes it possible to use the position measurements for optimal estimation in a Kalman filter like estimation procedure. Further the observation is justified with an experiment of position tracking and subsequent trajectory estimation of a ball thrown under gravity with the help of linear kinematic model.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129228366","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413765
A. Chopade, S. Khubalkar, A. Junghare, M. Aware
The speed control of the DC motor fed through buck-converter is generally employed with conventional integer order PID. The closed loop speed control of these drives are prone to deteriorate in their performance over a period of time. This paper proposes the fractional order (FO) PID speed controller with DC motor. The feasibility of more tuning parameters enhances the performance. Oustaloup's approximation method is used to approximate the fractional order differentiator and integrator. This controller performances are tested in the simulation mode.
{"title":"Fractional order speed controller for buck-converter fed DC motor","authors":"A. Chopade, S. Khubalkar, A. Junghare, M. Aware","doi":"10.1109/CMI.2016.7413765","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413765","url":null,"abstract":"The speed control of the DC motor fed through buck-converter is generally employed with conventional integer order PID. The closed loop speed control of these drives are prone to deteriorate in their performance over a period of time. This paper proposes the fractional order (FO) PID speed controller with DC motor. The feasibility of more tuning parameters enhances the performance. Oustaloup's approximation method is used to approximate the fractional order differentiator and integrator. This controller performances are tested in the simulation mode.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127120220","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413745
Rajarshi Gupta, P. Kundu
Electrocardiography (ECG) is popular non-invasive technique for preliminary level investigation on cardiovascular assessment. Computerized analysis of ECG can significantly contribute towards assisted diagnosis and in early detection of many cardiac diseases. Conventional automated ECG classifiers employing soft computing tools may suffer from the inaccuracies that may result in different clinical feature extraction stages. In this paper, we propose the use of a statistical index, namely, dissimilarity factor (D) for classification of normal and Inferior Myocardial Infarction (IMI) data, without the need of any direct clinical feature extraction. Time aligned ECG beats were obtained through filtering, wavelet decomposition processes, followed by PCA based beat enhancement to generate multivariate time series data. The T wave and QRS segments of IMI datasets from Lead II, III and aVF were extracted and compared with corresponding segments of healthy patients using Physionet ptbdb data. With 35 IMI datasets, the average composite dissimilarity factor Dc between normal data was found to be 0.39, and the same between normal and abnormal data were found to be 0.65. This paper shows the promise of descriptive statistical tools as an alternative for medical signal analysis.
{"title":"Dissimilarity factor based classification of inferior myocardial infarction ECG","authors":"Rajarshi Gupta, P. Kundu","doi":"10.1109/CMI.2016.7413745","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413745","url":null,"abstract":"Electrocardiography (ECG) is popular non-invasive technique for preliminary level investigation on cardiovascular assessment. Computerized analysis of ECG can significantly contribute towards assisted diagnosis and in early detection of many cardiac diseases. Conventional automated ECG classifiers employing soft computing tools may suffer from the inaccuracies that may result in different clinical feature extraction stages. In this paper, we propose the use of a statistical index, namely, dissimilarity factor (D) for classification of normal and Inferior Myocardial Infarction (IMI) data, without the need of any direct clinical feature extraction. Time aligned ECG beats were obtained through filtering, wavelet decomposition processes, followed by PCA based beat enhancement to generate multivariate time series data. The T wave and QRS segments of IMI datasets from Lead II, III and aVF were extracted and compared with corresponding segments of healthy patients using Physionet ptbdb data. With 35 IMI datasets, the average composite dissimilarity factor Dc between normal data was found to be 0.39, and the same between normal and abnormal data were found to be 0.65. This paper shows the promise of descriptive statistical tools as an alternative for medical signal analysis.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131384444","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413722
Ayani Nandi, S. Debnath
One of the most important power quality problems is harmonic pollution in power system. In recent years there has been an increase in voltage and current distortion in the distribution network due to the extensive use of power electronic and computer controlled devices. In this paper, using fractal analysis the source of harmonic pollution has been identified in a radial power system distribution network. The fractal technique provides both time and spectral information of the nonlinear load harmonic patterns. The network is simulated using EMTP/ ATP software. Simulation results have been presented which show that the proposed method can successfully identify the location of the harmonic source in case of a single harmonic source and location of dominant source of harmonic pollution in case of multiple harmonic sources in the system.
{"title":"Recognition of harmonic sources in distribution network using fractal analysis","authors":"Ayani Nandi, S. Debnath","doi":"10.1109/CMI.2016.7413722","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413722","url":null,"abstract":"One of the most important power quality problems is harmonic pollution in power system. In recent years there has been an increase in voltage and current distortion in the distribution network due to the extensive use of power electronic and computer controlled devices. In this paper, using fractal analysis the source of harmonic pollution has been identified in a radial power system distribution network. The fractal technique provides both time and spectral information of the nonlinear load harmonic patterns. The network is simulated using EMTP/ ATP software. Simulation results have been presented which show that the proposed method can successfully identify the location of the harmonic source in case of a single harmonic source and location of dominant source of harmonic pollution in case of multiple harmonic sources in the system.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131500187","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413780
R. Nair, L. Behera
This paper deals with the design of a robust adaptive fuzzy nonsingular fast terminal sliding mode control strategy for the relative motion control of spacecraft in formation. A nonsingular terminal sliding surface, along with a fast reaching law, has been considered for fast and finite time convergence. Adaptive tuning algorithms are derived based on Lyapunov stability theory for updating the controller gains involved in the fast reaching law. In order to reduce the chattering, the discontinuous term in the reaching law has been replaced by a fuzzy inference mechanism. Lyapunov based adaptive tuning laws are derived for updating the fuzzy parameters involved. Numerical simulations based on nonlinear dynamics defined in leader centered Hill's frame, have been presented to prove the robustness of the proposed approach.
{"title":"Adaptive fuzzy nonsingular fast terminal sliding mode control for spacecraft formation flying","authors":"R. Nair, L. Behera","doi":"10.1109/CMI.2016.7413780","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413780","url":null,"abstract":"This paper deals with the design of a robust adaptive fuzzy nonsingular fast terminal sliding mode control strategy for the relative motion control of spacecraft in formation. A nonsingular terminal sliding surface, along with a fast reaching law, has been considered for fast and finite time convergence. Adaptive tuning algorithms are derived based on Lyapunov stability theory for updating the controller gains involved in the fast reaching law. In order to reduce the chattering, the discontinuous term in the reaching law has been replaced by a fuzzy inference mechanism. Lyapunov based adaptive tuning laws are derived for updating the fuzzy parameters involved. Numerical simulations based on nonlinear dynamics defined in leader centered Hill's frame, have been presented to prove the robustness of the proposed approach.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127922628","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413734
Vikram, L. Dewan
This paper presents the application of l-1 Regularized Least Square (H RLS)to Sparse identification of linear systems. The l-1 norm is the closest possible convex function to the function 1-0 norm and provides a convex optimization problem provided cost function without l-1 norm is convex. The sparse parameters of Output-Error (OE) model, which gives non-convex cost function, are estimated by combining Instrumental Variable method with 1-1 RLS resulting into a two stage algorithm. To support the speculation, the paper presents performance analysis using simulation results.
{"title":"Sparse identification of output error models using l-1 regularized least square","authors":"Vikram, L. Dewan","doi":"10.1109/CMI.2016.7413734","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413734","url":null,"abstract":"This paper presents the application of l-1 Regularized Least Square (H RLS)to Sparse identification of linear systems. The l-1 norm is the closest possible convex function to the function 1-0 norm and provides a convex optimization problem provided cost function without l-1 norm is convex. The sparse parameters of Output-Error (OE) model, which gives non-convex cost function, are estimated by combining Instrumental Variable method with 1-1 RLS resulting into a two stage algorithm. To support the speculation, the paper presents performance analysis using simulation results.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115584637","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413746
Govind V Waghmare, Sneha Borkar, V. Saley, Hemant Chinchore, Shivraj Wabale
This paper describes the use of two dimensional (2-D) laser scanner for locating badminton shuttlecock in real playing environment. It proposes a method to predict the end point of shuttlecock trajectory. The system is designed using two 2-D laser scanners to locate shuttlecock in midst of air in its trajectory. It helps to calculate shuttlecock's speed, orientation and hence, to predict an end point of its trajectory. This system acts as an intelligent feedback system to a badminton playing robot. The badminton playing robot requires enhanced and deterministic shuttlecock detection system for its accurate operations. The shuttlecock detection system can be implemented in designing of such badminton playing robots making the badminton sport more advanced as robots can be used to assist players in training programs. The paper deals with simulation and real experimental results obtained by two 2-D laser scanners to perform complex task of shuttlecock trajectory prediction. The physical implementation ensures minimum computational latency over traditional camera based shuttlecock detection methods. On field trials involved two scanners to locate shuttlecock at discrete time interval and promising results are obtained indicating such detection system with suitable modifications can be employed in shuttlecock trajectory prediction.
{"title":"Badminton shuttlecock detection and prediction of trajectory using multiple 2 dimensional scanners","authors":"Govind V Waghmare, Sneha Borkar, V. Saley, Hemant Chinchore, Shivraj Wabale","doi":"10.1109/CMI.2016.7413746","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413746","url":null,"abstract":"This paper describes the use of two dimensional (2-D) laser scanner for locating badminton shuttlecock in real playing environment. It proposes a method to predict the end point of shuttlecock trajectory. The system is designed using two 2-D laser scanners to locate shuttlecock in midst of air in its trajectory. It helps to calculate shuttlecock's speed, orientation and hence, to predict an end point of its trajectory. This system acts as an intelligent feedback system to a badminton playing robot. The badminton playing robot requires enhanced and deterministic shuttlecock detection system for its accurate operations. The shuttlecock detection system can be implemented in designing of such badminton playing robots making the badminton sport more advanced as robots can be used to assist players in training programs. The paper deals with simulation and real experimental results obtained by two 2-D laser scanners to perform complex task of shuttlecock trajectory prediction. The physical implementation ensures minimum computational latency over traditional camera based shuttlecock detection methods. On field trials involved two scanners to locate shuttlecock at discrete time interval and promising results are obtained indicating such detection system with suitable modifications can be employed in shuttlecock trajectory prediction.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116164648","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 : 1900-01-01DOI: 10.1109/CMI.2016.7413702
P. Biswas, S. Bhaumik, I. Patiyat
In this ongoing work, three non-linear Gaussian filters viz. the unscented Kalman filter (UKF), the cubature qudrature Kalman filter (CQKF) and the Gauss-Hermite filter (GHF) are designed to track blood glucose and insulin concentrations, as well as interstitial insulin level with the help of the `Bergman's minimal model of glucose-insulin homeostasis'. All the filters successfully track the plasma glucose and insulin level, even without the declaration of meal intake. We evaluate the filters' performances in terms of root mean square error (RMSE) which shows all the three filters are equally capable of tracking plasma glucose and insulin from noisy blood glucose measurements.
{"title":"Estimation of glucose and insulin concentration using nonlinear Gaussian filters","authors":"P. Biswas, S. Bhaumik, I. Patiyat","doi":"10.1109/CMI.2016.7413702","DOIUrl":"https://doi.org/10.1109/CMI.2016.7413702","url":null,"abstract":"In this ongoing work, three non-linear Gaussian filters viz. the unscented Kalman filter (UKF), the cubature qudrature Kalman filter (CQKF) and the Gauss-Hermite filter (GHF) are designed to track blood glucose and insulin concentrations, as well as interstitial insulin level with the help of the `Bergman's minimal model of glucose-insulin homeostasis'. All the filters successfully track the plasma glucose and insulin level, even without the declaration of meal intake. We evaluate the filters' performances in terms of root mean square error (RMSE) which shows all the three filters are equally capable of tracking plasma glucose and insulin from noisy blood glucose measurements.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131691907","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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