Pub Date : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.02050
E. Solingen, J. V. Wingerden, R. Breuker, M. Verhaegen
Abstract In this paper a novel approach for ℋ ∞ controller design for linear parameterizable controllers is presented. The approach uses the generalized Nyquist stability criterion to find the parameters of linear parameterized controllers for Multi-Input Multi-Output (MIMO) systems. The main advantage of the proposed approach is that the generalized plant does not have to be diagonally dominant and that there is no need for a desired open-loop response function. By constraining the Nyquist curve from certain parts in the frequency domain, controller parameters that guarantee stability and performance of the closed-loop system can be found. The method is successfully applied to two cases involving a double-mass-spring-damper system. In the first case only controller parameters are optimized and in the second case both structural and controller parameters are optimized.
{"title":"Optimization of Linear Parameterizable ℋ∞ Controllers in the Frequency Domain","authors":"E. Solingen, J. V. Wingerden, R. Breuker, M. Verhaegen","doi":"10.3182/20140824-6-ZA-1003.02050","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.02050","url":null,"abstract":"Abstract In this paper a novel approach for ℋ ∞ controller design for linear parameterizable controllers is presented. The approach uses the generalized Nyquist stability criterion to find the parameters of linear parameterized controllers for Multi-Input Multi-Output (MIMO) systems. The main advantage of the proposed approach is that the generalized plant does not have to be diagonally dominant and that there is no need for a desired open-loop response function. By constraining the Nyquist curve from certain parts in the frequency domain, controller parameters that guarantee stability and performance of the closed-loop system can be found. The method is successfully applied to two cases involving a double-mass-spring-damper system. In the first case only controller parameters are optimized and in the second case both structural and controller parameters are optimized.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"110 1","pages":"736-741"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81477932","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.00325
S. Aihara, A. Bagchi, E. Imreizeeq
Starting from the simple model for the spot price which is set as the jump augmented Vasicek model, we construct a factor model of the electricity futures as the stochastic hyperbolic systems with jumps. Representing the main spike phenomena of the electricity spot price from one observed futures data by proxy, the filtering of factor process and the related stochastic risk premium are formulated in a Gaussian frame work. After serving the likelihood functional, the systems parameter estimation problem is solved.
{"title":"Filtering and Identification of Stochastic Risk Premium for Electricity Spot Price Models","authors":"S. Aihara, A. Bagchi, E. Imreizeeq","doi":"10.3182/20140824-6-ZA-1003.00325","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.00325","url":null,"abstract":"Starting from the simple model for the spot price which is set as the jump augmented Vasicek model, we construct a factor model of the electricity futures as the stochastic hyperbolic systems with jumps. Representing the main spike phenomena of the electricity spot price from one observed futures data by proxy, the filtering of factor process and the related stochastic risk premium are formulated in a Gaussian frame work. After serving the likelihood functional, the systems parameter estimation problem is solved.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"47 1","pages":"9563-9568"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77668147","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.01191
Ziqi Yang, W. Naeem, G. Menary, Jing Deng, Kang Li
Abstract In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with particle swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.
{"title":"Advanced Modelling and Optimization of Infared Oven in Injection Stretch Blow-moulding for Energy Saving","authors":"Ziqi Yang, W. Naeem, G. Menary, Jing Deng, Kang Li","doi":"10.3182/20140824-6-ZA-1003.01191","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.01191","url":null,"abstract":"Abstract In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with particle swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"18 1","pages":"766-771"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87311048","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.01933
J. Jia, H. Yue
Under foggy viewing conditions, image contrast is often significantly degraded by atmospheric aerosols, which makes it difficult to quickly detect and track moving objects in intelligent transportation systems (ITS). A foggy image visibility enhancing algorithm based on an imaging model and wavelet transform technique is proposed in this paper. An optical imaging model in foggy weather conditions is established to determine the image degradation factors and compensation strategies. Based on this, the original image is firstly transferred into YUV color space of a luminance and two chrominance components. Then the luminance component is decomposed through wavelet transform into low- and high-frequency subbands. In the low-frequency subband, the medium scattered light component is estimated using Gaussian blur and removed from the image. Nonlinear transform for enhancement of foggy images is applied to high-frequency subbands. In the end, a new image is recovered by combining the chrominance components and the corrected luminance component altogether. Experimental results demonstrate that this algorithm can handle the problem of image blurring caused by atmospheric scattering effectively, and has a better real-time performance compared with a standard model-based procedure.
{"title":"A wavelet-based approach to improve foggy image clarity","authors":"J. Jia, H. Yue","doi":"10.3182/20140824-6-ZA-1003.01933","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.01933","url":null,"abstract":"Under foggy viewing conditions, image contrast is often significantly degraded by atmospheric aerosols, which makes it difficult to quickly detect and track moving objects in intelligent transportation systems (ITS). A foggy image visibility enhancing algorithm based on an imaging model and wavelet transform technique is proposed in this paper. An optical imaging model in foggy weather conditions is established to determine the image degradation factors and compensation strategies. Based on this, the original image is firstly transferred into YUV color space of a luminance and two chrominance components. Then the luminance component is decomposed through wavelet transform into low- and high-frequency subbands. In the low-frequency subband, the medium scattered light component is estimated using Gaussian blur and removed from the image. Nonlinear transform for enhancement of foggy images is applied to high-frequency subbands. In the end, a new image is recovered by combining the chrominance components and the corrected luminance component altogether. Experimental results demonstrate that this algorithm can handle the problem of image blurring caused by atmospheric scattering effectively, and has a better real-time performance compared with a standard model-based procedure.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"1 1","pages":"930-935"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89969929","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.00557
L. F. Recalde, R. Katebi, H. Yue
Abstract A sequential method for Control Performance Diagnosis using a classification tree to predict possible root-causes of poor performance is presented. The classification tree methodology is used to combine process pre-assessment (nonlinearities detection, delays estimation and controller assessment), control performance assessment (CPA) and analysis of variance (ANOVA) into an integrated framework. An initial process data set is analysed and the results are used as decision thresholds for the classification tree. The methodology is capable to identify root-causes such as poor tuning, inadequate control structure, nonlinearities, process mismatch and disturbance changes. The proposed methodology is applied to individual loops of a tandem cold rolling mill.
{"title":"Sequential Control Performance Diagnosis of Steel Processes","authors":"L. F. Recalde, R. Katebi, H. Yue","doi":"10.3182/20140824-6-ZA-1003.00557","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.00557","url":null,"abstract":"Abstract A sequential method for Control Performance Diagnosis using a classification tree to predict possible root-causes of poor performance is presented. The classification tree methodology is used to combine process pre-assessment (nonlinearities detection, delays estimation and controller assessment), control performance assessment (CPA) and analysis of variance (ANOVA) into an integrated framework. An initial process data set is analysed and the results are used as decision thresholds for the classification tree. The methodology is capable to identify root-causes such as poor tuning, inadequate control structure, nonlinearities, process mismatch and disturbance changes. The proposed methodology is applied to individual loops of a tandem cold rolling mill.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"22 1","pages":"2830-2835"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81877389","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.00104
B. Guo, Hua-cheng Zhou, Cui-Zhen Yao
Abstract We consider boundary stabilization for a multi-dimensional wave equation with boundary control matched disturbance that depends on both time and spatial variables. The active disturbance rejection control (ADRC) approach is adopted in investigation. An disturbance estimator is designed to estimate, in real time, the disturbance, and the disturbance is canceled in the feedback loop with its approximation. All subsystems in the closed-loop are shown to be asymptotically stable. The numerical experiments are carried out to illustrate the convergence and effect of peaking value reduction.
{"title":"The Stabilization of Multi-Dimensional Wave Equation with Boundary Control Matched Disturbance","authors":"B. Guo, Hua-cheng Zhou, Cui-Zhen Yao","doi":"10.3182/20140824-6-ZA-1003.00104","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.00104","url":null,"abstract":"Abstract We consider boundary stabilization for a multi-dimensional wave equation with boundary control matched disturbance that depends on both time and spatial variables. The active disturbance rejection control (ADRC) approach is adopted in investigation. An disturbance estimator is designed to estimate, in real time, the disturbance, and the disturbance is canceled in the feedback loop with its approximation. All subsystems in the closed-loop are shown to be asymptotically stable. The numerical experiments are carried out to illustrate the convergence and effect of peaking value reduction.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"2 1","pages":"11363-11368"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89053735","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.01200
Lei Chen, Y. Yan, Changyin Sun
Abstract This study investigates the sliding mode control (SMC) method based on the nonlinear characteristic model and its application to flexible satellites. A novel nonlinear dynamic sliding mode surface is designed depending on the nonlinear characteristic model. The expected advantage of the proposed SMC compared to the traditional SMC is to improve performances and robustness. The proposed results apply to a class of nonlinear systems and rely on the parameter estimation of the characteristic model. The theory is illustrated on the rapid maneuver and fast stability problem of the sun synchronous orbit satellite.
{"title":"Nonlinear Characteristic Model–Based SMC and Its Application to Flexible Satellites","authors":"Lei Chen, Y. Yan, Changyin Sun","doi":"10.3182/20140824-6-ZA-1003.01200","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.01200","url":null,"abstract":"Abstract This study investigates the sliding mode control (SMC) method based on the nonlinear characteristic model and its application to flexible satellites. A novel nonlinear dynamic sliding mode surface is designed depending on the nonlinear characteristic model. The expected advantage of the proposed SMC compared to the traditional SMC is to improve performances and robustness. The proposed results apply to a class of nonlinear systems and rely on the parameter estimation of the characteristic model. The theory is illustrated on the rapid maneuver and fast stability problem of the sun synchronous orbit satellite.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"61 1","pages":"4595-4600"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86788011","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}
The aim of this paper is to propose models to adapt and parameterize the Material Requirement Planning (MRP) approach under lead time uncertainty. Multi-level assembly systems with one type of finished products and several types of components aer studied. Each component has a fixed unit inventory cost and the finished product has a backlogging cost per unit of time. The lead times of components are discrete random variables, and the costumers demand of the finished product is known. A general mathematical model for supply planning of multi-level assembly systems is presented. A Genetic Algorithm (GA) method is proposed to minimize the sum of the average inventory holding cost for components and the average backlogging and inventory holding costs for the finished product.
Pub Date : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.00036
Aircraft in Cruising Phase, Jingjie Chen, Yong-Wang Yue
Abstract With the rapid development of civil aviation, the shortage of airspace resource is becoming one of the main limiting factors for air traffic transportation. Inspired by the ideas of reduced vertical separation minimum and reducing aircraft separation standard, this paper analyzes the distributing characteristics of civil aircraft tracks in cruising level space and presents a novel method for probability density estimation of civil aircraft tracks' relative altitudes in their cruising flight level spaces, and analyzes the distributing characteristics at their cruising altitude direction. The method is based on QAR data of enough random civil aircraft tracks from a domestic airline. First, we choose altitude data of each track's main cruise phase and calculate altitude values relative to the standard cruise altitude of respective cruising flight level, we call these processes as spatial alignment and the relative altitudes as relative-cruising altitudes or relative-cruise altitudes. Secondly, we do temporal alignment and figure out the relative altitude values of these tracks in panel data form. Then, we estimate the probability density of the relative altitude values using kernel density estimate method, with the least square cross-validation method choosing asymptotically optimal smoothing parameters. Finally, we figure out different confidence track bands, namely confidence interval limits, and do analysis. All the analysis results show that there is a great deal of airspace margin and space resource potential in each cruising levels. Hence there are a great possibility and expectation that the vertical separation minimum can be reduced again and add flight levels, which is beneficial to increase air traffic capacity and relieve traffic jams.
{"title":"A Novel Probability Density Estimating Method for Relative Altitudes of Civil","authors":"Aircraft in Cruising Phase, Jingjie Chen, Yong-Wang Yue","doi":"10.3182/20140824-6-ZA-1003.00036","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.00036","url":null,"abstract":"Abstract With the rapid development of civil aviation, the shortage of airspace resource is becoming one of the main limiting factors for air traffic transportation. Inspired by the ideas of reduced vertical separation minimum and reducing aircraft separation standard, this paper analyzes the distributing characteristics of civil aircraft tracks in cruising level space and presents a novel method for probability density estimation of civil aircraft tracks' relative altitudes in their cruising flight level spaces, and analyzes the distributing characteristics at their cruising altitude direction. The method is based on QAR data of enough random civil aircraft tracks from a domestic airline. First, we choose altitude data of each track's main cruise phase and calculate altitude values relative to the standard cruise altitude of respective cruising flight level, we call these processes as spatial alignment and the relative altitudes as relative-cruising altitudes or relative-cruise altitudes. Secondly, we do temporal alignment and figure out the relative altitude values of these tracks in panel data form. Then, we estimate the probability density of the relative altitude values using kernel density estimate method, with the least square cross-validation method choosing asymptotically optimal smoothing parameters. Finally, we figure out different confidence track bands, namely confidence interval limits, and do analysis. All the analysis results show that there is a great deal of airspace margin and space resource potential in each cruising levels. Hence there are a great possibility and expectation that the vertical separation minimum can be reduced again and add flight levels, which is beneficial to increase air traffic capacity and relieve traffic jams.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"25 1","pages":"4201-4208"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73923239","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 : 2014-08-24DOI: 10.3182/20140824-6-ZA-1003.02828
J. Richalet, T. Darure, J. Mallet
Abstract A full first principle model of counter current heat exchangers is used as the internal model of a classical PFC controller. With the use of a specific physical “convexity property” of this type of process, a full straightforward first-principle model is used as the internal model of the controller. The whole strategy is implemented in a classical industrial PLC, which controls this nonlinear process with a minimum effort.
{"title":"Predictive Functional Control of counter current heat exchangers","authors":"J. Richalet, T. Darure, J. Mallet","doi":"10.3182/20140824-6-ZA-1003.02828","DOIUrl":"https://doi.org/10.3182/20140824-6-ZA-1003.02828","url":null,"abstract":"Abstract A full first principle model of counter current heat exchangers is used as the internal model of a classical PFC controller. With the use of a specific physical “convexity property” of this type of process, a full straightforward first-principle model is used as the internal model of the controller. The whole strategy is implemented in a classical industrial PLC, which controls this nonlinear process with a minimum effort.","PeriodicalId":13260,"journal":{"name":"IFAC Proceedings Volumes","volume":"28 1","pages":"5345-5350"},"PeriodicalIF":0.0,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80963677","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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