Pub Date : 2013-12-01DOI: 10.1109/CDC.2013.6760411
Minyi Huang, J. Manton
This paper considers a social opinion model with noisy information when one agent obtains the opinion of another. Stochastic approximation with bounded confidence is introduced to update the opinions. The asymptotic behavior of the stochastic algorithm is intimately related to a deterministic vector field. We show that the presence of noise can cause a defragmentation of the state space. This in turn can generate more orderly collective behavior, which is very different from noiseless models which have the well known fragmentation property during the evolution of the individual opinions.
{"title":"Opinion dynamics with noisy information","authors":"Minyi Huang, J. Manton","doi":"10.1109/CDC.2013.6760411","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760411","url":null,"abstract":"This paper considers a social opinion model with noisy information when one agent obtains the opinion of another. Stochastic approximation with bounded confidence is introduced to update the opinions. The asymptotic behavior of the stochastic algorithm is intimately related to a deterministic vector field. We show that the presence of noise can cause a defragmentation of the state space. This in turn can generate more orderly collective behavior, which is very different from noiseless models which have the well known fragmentation property during the evolution of the individual opinions.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126730134","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 : 2013-12-01DOI: 10.1109/CDC.2013.6759965
N. Guglielmi, L. Laglia
We consider switched linear systems of odes, ẋ x(t)= A(u(t))x(t) where A(u(t)) ∈ A, a compact set of matrices. In this paper we propose a new method for the approximation of the upper Lyapunov exponent and lower Lyapunov exponent of the LSS when the matrices in A are Metzler matrices (or the generalization of them for arbitrary cone), arising in many interesting applications (see e.g. [9]). The method is based on the iterative construction of invariant positive polytopes for a sequence of discretized systems obtained by forcing the switching instants to be multiple of Δ(k)t where Δ(k)t → 0 as k → ∞. These polytopes are then used to generate a monotone piecewise-linear joint Lyapunov function on the positive orthant, which gives tight upper and lower bounds for the Lyapunov exponents. As a byproduct we detect whether the considered system is stabilizable or uniformly stable. The efficiency of this approach is demonstrated in numerical examples, including some of relatively large dimensions.
{"title":"Polytope joint Lyapunov functions for positive LSS","authors":"N. Guglielmi, L. Laglia","doi":"10.1109/CDC.2013.6759965","DOIUrl":"https://doi.org/10.1109/CDC.2013.6759965","url":null,"abstract":"We consider switched linear systems of odes, ẋ x(t)= A(u(t))x(t) where A(u(t)) ∈ A, a compact set of matrices. In this paper we propose a new method for the approximation of the upper Lyapunov exponent and lower Lyapunov exponent of the LSS when the matrices in A are Metzler matrices (or the generalization of them for arbitrary cone), arising in many interesting applications (see e.g. [9]). The method is based on the iterative construction of invariant positive polytopes for a sequence of discretized systems obtained by forcing the switching instants to be multiple of Δ(k)t where Δ(k)t → 0 as k → ∞. These polytopes are then used to generate a monotone piecewise-linear joint Lyapunov function on the positive orthant, which gives tight upper and lower bounds for the Lyapunov exponents. As a byproduct we detect whether the considered system is stabilizable or uniformly stable. The efficiency of this approach is demonstrated in numerical examples, including some of relatively large dimensions.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"1099 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116045502","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760673
F. Harrou, L. Fillatre, M. Bobbia, I. Nikiforov
Monitoring ozone concentrations is an essential requirement due to the adverse environmental and health effects of abnormal ozone pollution. The objective of this paper is twofold: first, to model ground level ozone concentrations, and second, to detect abnormal ozone measurements. Towards this end, a multidimensional Seasonal AutoRegressive Moving Average with eXogenous variable (SARMAX) model has been developed to describe ground level ozone concentrations. The database used to fit the models consists of two data sets collected from Upper Normandy region, France, via the network of air quality monitoring stations. A good description of the ambient ozone pollution may be a tool for facilitating detection of abnormalities in ozone measurements. The overarching goal of this paper is to detect abnormal pollution measurements caused by air pollution anomalies or malfunctioning sensors in the framework of regional ozone surveillance network. The proposed Constrained Generalized Likelihood Ratio (CGLR) anomaly detection scheme is successfully applied to collected data. The detection results of the proposed method are compared to that declared by Air Normand air monitoring association.
{"title":"Statistical detection of abnormal ozone measurements based on Constrained Generalized Likelihood Ratio test","authors":"F. Harrou, L. Fillatre, M. Bobbia, I. Nikiforov","doi":"10.1109/CDC.2013.6760673","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760673","url":null,"abstract":"Monitoring ozone concentrations is an essential requirement due to the adverse environmental and health effects of abnormal ozone pollution. The objective of this paper is twofold: first, to model ground level ozone concentrations, and second, to detect abnormal ozone measurements. Towards this end, a multidimensional Seasonal AutoRegressive Moving Average with eXogenous variable (SARMAX) model has been developed to describe ground level ozone concentrations. The database used to fit the models consists of two data sets collected from Upper Normandy region, France, via the network of air quality monitoring stations. A good description of the ambient ozone pollution may be a tool for facilitating detection of abnormalities in ozone measurements. The overarching goal of this paper is to detect abnormal pollution measurements caused by air pollution anomalies or malfunctioning sensors in the framework of regional ozone surveillance network. The proposed Constrained Generalized Likelihood Ratio (CGLR) anomaly detection scheme is successfully applied to collected data. The detection results of the proposed method are compared to that declared by Air Normand air monitoring association.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122321455","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760551
M. Pouliquen, F. Giri, O. Gehan, E. Pigeon, M. Frikel, B. Targui
In this paper, a subspace identification algorithm for a class of Hammerstein systems is developed. We consider dynamical systems subject to input backlash or switch nonlinearities. The idea is to use a specific input signal allowing the estimation of the nonlinear part and the estimation of a state space model for the linear part. The identification algorithm is a subspace type algorithm. A simulation example is given to illustrate the performances of the present method.
{"title":"Subspace identification of Hammerstein systems with nonparametric input backlash and switch nonlinearities","authors":"M. Pouliquen, F. Giri, O. Gehan, E. Pigeon, M. Frikel, B. Targui","doi":"10.1109/CDC.2013.6760551","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760551","url":null,"abstract":"In this paper, a subspace identification algorithm for a class of Hammerstein systems is developed. We consider dynamical systems subject to input backlash or switch nonlinearities. The idea is to use a specific input signal allowing the estimation of the nonlinear part and the estimation of a state space model for the linear part. The identification algorithm is a subspace type algorithm. A simulation example is given to illustrate the performances of the present method.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122710410","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 : 2013-12-01DOI: 10.1109/CDC.2013.6761022
Ylva Jung, M. Enqvist
This paper considers the problem of how to estimate a model of the inverse of a system. The use of inverse systems can be found in many applications, such as feedforward control and power amplifier predistortion. The inverse model is here estimated with the purpose of using it in cascade with the system itself, as an inverter. A good inverse model in this setting would be one that, when used in series with the original system, reconstructs the original input. The goal here is to select suitable inputs, experimental conditions and loss functions to obtain a good input estimate. Both linear and nonlinear systems will be discussed. For nonlinear systems, one way to obtain a linearizing prefilter is by Hirschorn's algorithm. It is here shown how to extend this to the postdistortion case, and some formulations of how the pre- or postinverter could be estimated are also presented.
{"title":"Estimating models of inverse systems","authors":"Ylva Jung, M. Enqvist","doi":"10.1109/CDC.2013.6761022","DOIUrl":"https://doi.org/10.1109/CDC.2013.6761022","url":null,"abstract":"This paper considers the problem of how to estimate a model of the inverse of a system. The use of inverse systems can be found in many applications, such as feedforward control and power amplifier predistortion. The inverse model is here estimated with the purpose of using it in cascade with the system itself, as an inverter. A good inverse model in this setting would be one that, when used in series with the original system, reconstructs the original input. The goal here is to select suitable inputs, experimental conditions and loss functions to obtain a good input estimate. Both linear and nonlinear systems will be discussed. For nonlinear systems, one way to obtain a linearizing prefilter is by Hirschorn's algorithm. It is here shown how to extend this to the postdistortion case, and some formulations of how the pre- or postinverter could be estimated are also presented.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122998835","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760172
A. Rikos, C. Hadjicostis
We address the integer weight-balancing problem for a distributed system whose components (nodes) can exchange information via interconnection links (edges) that form an arbitrary, possibly directed, communication topology (digraph). A weighted digraph is balanced if, for each of its nodes, the sum of the weights of the edges outgoing from the node is equal to the sum of the weights of the edges incoming to the node. Weight-balanced digraphs play a key role in a number of applications, including distributed optimization, cooperative control, and distributed averaging problems. In this paper, we develop a distributed iterative algorithm, which can be used to reach weight balance, by assigning a positive integer weight on each edge, as long as the underlying communication topology forms a strongly connected digraph (or is a collection of strongly connected digraphs).
{"title":"Distributed balancing of a digraph with integer weights","authors":"A. Rikos, C. Hadjicostis","doi":"10.1109/CDC.2013.6760172","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760172","url":null,"abstract":"We address the integer weight-balancing problem for a distributed system whose components (nodes) can exchange information via interconnection links (edges) that form an arbitrary, possibly directed, communication topology (digraph). A weighted digraph is balanced if, for each of its nodes, the sum of the weights of the edges outgoing from the node is equal to the sum of the weights of the edges incoming to the node. Weight-balanced digraphs play a key role in a number of applications, including distributed optimization, cooperative control, and distributed averaging problems. In this paper, we develop a distributed iterative algorithm, which can be used to reach weight balance, by assigning a positive integer weight on each edge, as long as the underlying communication topology forms a strongly connected digraph (or is a collection of strongly connected digraphs).","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613457","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 : 2013-12-01DOI: 10.1109/CDC.2013.6761130
Wenling Li, Y. Jia, Junping Du, Jun Zhang
In this paper, we address the problem of multi-target tracking with unknown measurement noise variance parameters by the probability hypothesis density (PHD) filter. Based on the concept of conjugate prior distributions for noise statistics, the inverse-Gamma distributions are employed to describe the dynamics of the noise variance parameters and a novel implementation to the PHD recursion is developed by representing the predicted and the posterior intensities as mixtures of Gaussian-inverse-Gamma terms. As the target state and the noise variance parameters are coupled in the likelihood functions, the variational Bayesian approximation approach is applied so that the posterior is derived in the same form as the prior and the resulting algorithm is recursive. A numerical example is provided to illustrate the effectiveness of the proposed filter.
{"title":"PHD filter for multi-target tracking by variational Bayesian approximation","authors":"Wenling Li, Y. Jia, Junping Du, Jun Zhang","doi":"10.1109/CDC.2013.6761130","DOIUrl":"https://doi.org/10.1109/CDC.2013.6761130","url":null,"abstract":"In this paper, we address the problem of multi-target tracking with unknown measurement noise variance parameters by the probability hypothesis density (PHD) filter. Based on the concept of conjugate prior distributions for noise statistics, the inverse-Gamma distributions are employed to describe the dynamics of the noise variance parameters and a novel implementation to the PHD recursion is developed by representing the predicted and the posterior intensities as mixtures of Gaussian-inverse-Gamma terms. As the target state and the noise variance parameters are coupled in the likelihood functions, the variational Bayesian approximation approach is applied so that the posterior is derived in the same form as the prior and the resulting algorithm is recursive. A numerical example is provided to illustrate the effectiveness of the proposed filter.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117090567","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760956
L. Buşoniu, I. Morǎrescu
An important challenge in multiagent systems is consensus, in which the agents must agree on certain controlled variables of interest. So far, most consensus algorithms for agents with nonlinear dynamics exploit the specific form of the nonlinearity. Here, we propose an approach that only requires a black-box simulation model of the dynamics, and is therefore applicable to a wide class of nonlinearities. This approach works for agents communicating on a fixed, connected network. It designs a reference behavior with a classical consensus protocol, and then finds control actions that drive the nonlinear agents towards the reference states, using a recent optimistic optimization algorithm. By exploiting the guarantees of optimistic optimization, we prove that the agents achieve practical consensus. A representative example is further analyzed, and simulation results on nonlinear robotic arms are provided.
{"title":"Consensus for agents with general dynamics using optimistic optimization","authors":"L. Buşoniu, I. Morǎrescu","doi":"10.1109/CDC.2013.6760956","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760956","url":null,"abstract":"An important challenge in multiagent systems is consensus, in which the agents must agree on certain controlled variables of interest. So far, most consensus algorithms for agents with nonlinear dynamics exploit the specific form of the nonlinearity. Here, we propose an approach that only requires a black-box simulation model of the dynamics, and is therefore applicable to a wide class of nonlinearities. This approach works for agents communicating on a fixed, connected network. It designs a reference behavior with a classical consensus protocol, and then finds control actions that drive the nonlinear agents towards the reference states, using a recent optimistic optimization algorithm. By exploiting the guarantees of optimistic optimization, we prove that the agents achieve practical consensus. A representative example is further analyzed, and simulation results on nonlinear robotic arms are provided.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129497671","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760355
Xiangyu Meng, Bingchang Wang, Tongwen Chen, M. Darouach
The problem of optimal control for first order stochastic systems with a quadratic performance index over a finite horizon is studied. The performance of three messaging policies for sensing combined with two hold circuits for actuation is compared based on optimization over the parameters of event detection and feedback control. The sampling rules include deterministic sampling (DS), level-crossing sampling (LCS) and optimal sampling (OS), and the hold circuits include zero order hold (ZOH) and generalized hold (GH). The general results are established that level-crossing sampling performs more effectively than deterministic sampling and generalized hold outperforms zero order hold.
{"title":"Sensing and actuation strategies for event triggered stochastic optimal control","authors":"Xiangyu Meng, Bingchang Wang, Tongwen Chen, M. Darouach","doi":"10.1109/CDC.2013.6760355","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760355","url":null,"abstract":"The problem of optimal control for first order stochastic systems with a quadratic performance index over a finite horizon is studied. The performance of three messaging policies for sensing combined with two hold circuits for actuation is compared based on optimization over the parameters of event detection and feedback control. The sampling rules include deterministic sampling (DS), level-crossing sampling (LCS) and optimal sampling (OS), and the hold circuits include zero order hold (ZOH) and generalized hold (GH). The general results are established that level-crossing sampling performs more effectively than deterministic sampling and generalized hold outperforms zero order hold.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129719272","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 : 2013-12-01DOI: 10.1109/CDC.2013.6760909
Shenpeng Li, Jingxin Zhang
Generalized inverse of non-square MIMO system arise from many application problems. This paper investigates some fundamental properties of the generalized inverse. These include the necessary and sufficient conditions for the minimum H2 norm inverse, the minimality of the H2 norms for the rows/columns of the inverse, and the redundancy and design freedom associated with the rows/columns of the generalized inverse. An application to MIMO communication system is presented to demonstrate the usefulness and potential of these properties.
{"title":"Some properties of generalized inverse of non-square systems","authors":"Shenpeng Li, Jingxin Zhang","doi":"10.1109/CDC.2013.6760909","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760909","url":null,"abstract":"Generalized inverse of non-square MIMO system arise from many application problems. This paper investigates some fundamental properties of the generalized inverse. These include the necessary and sufficient conditions for the minimum H2 norm inverse, the minimality of the H2 norms for the rows/columns of the inverse, and the redundancy and design freedom associated with the rows/columns of the generalized inverse. An application to MIMO communication system is presented to demonstrate the usefulness and potential of these properties.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129960973","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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