Pub Date : 2013-12-01DOI: 10.1109/CDC.2013.6760204
Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, K. Johansson
The coordinated output regulation problem for multiple heterogeneous linear systems is studied in this paper. Each agent is modeled as a linear multiple-input multiple-output (MIMO) system with an exogenous input which represents the individual tracking objective for the agent. The multi-agent system as a whole has a group exogenous input which represents the tracking objective for the whole group. Under the constraints that the group exogenous input is only locally available to each agent and that the agents have only access to their neighbors' information, we propose an observer-based feedback controller to solve the coordinated output regulation problem. A high-gain approach is introduced and the information interactions are allowed to be switching over a finite set of fixed networks containing both graphs having a spanning tree and graphs that do not. A lower bound of the high gain parameters is explicitly given. It describes a fundamental relationship between the information interactions, the dwell time, the non-identical dynamics of different agents, and the high gain parameters.
{"title":"Coordinated output regulation of multiple heterogeneous linear systems","authors":"Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, K. Johansson","doi":"10.1109/CDC.2013.6760204","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760204","url":null,"abstract":"The coordinated output regulation problem for multiple heterogeneous linear systems is studied in this paper. Each agent is modeled as a linear multiple-input multiple-output (MIMO) system with an exogenous input which represents the individual tracking objective for the agent. The multi-agent system as a whole has a group exogenous input which represents the tracking objective for the whole group. Under the constraints that the group exogenous input is only locally available to each agent and that the agents have only access to their neighbors' information, we propose an observer-based feedback controller to solve the coordinated output regulation problem. A high-gain approach is introduced and the information interactions are allowed to be switching over a finite set of fixed networks containing both graphs having a spanning tree and graphs that do not. A lower bound of the high gain parameters is explicitly given. It describes a fundamental relationship between the information interactions, the dwell time, the non-identical dynamics of different agents, and the high gain parameters.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"8 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":"121321890","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.2013.6760804
M. Abouheaf, F. Lewis
This paper studies a class of multi-agent graphical games denoted by differential graphical games, where interactions between agents are prescribed by a communication graph structure. Ideas from cooperative control are given to achieve synchronization among the agents to a leader dynamics. New coupled Bellman and Hamilton-Jacobi-Bellman equations are developed for this class of games using Integral Reinforcement Learning. Nash solutions are given in terms of solutions to a set of coupled continuous-time Hamilton-Jacobi-Bellman equations. A multi-agent policy iteration algorithm is given to learn the Nash solution in real time without knowing the complete dynamic models of the agents. A proof of convergence for this algorithm is given. An online multi-agent method based on policy iterations is developed using a critic network to solve all the Hamilton-Jacobi-Bellman equations simultaneously for the graphical game.
{"title":"Multi-agent differential graphical games: Nash online adaptive learning solutions","authors":"M. Abouheaf, F. Lewis","doi":"10.1109/CDC.2013.6760804","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760804","url":null,"abstract":"This paper studies a class of multi-agent graphical games denoted by differential graphical games, where interactions between agents are prescribed by a communication graph structure. Ideas from cooperative control are given to achieve synchronization among the agents to a leader dynamics. New coupled Bellman and Hamilton-Jacobi-Bellman equations are developed for this class of games using Integral Reinforcement Learning. Nash solutions are given in terms of solutions to a set of coupled continuous-time Hamilton-Jacobi-Bellman equations. A multi-agent policy iteration algorithm is given to learn the Nash solution in real time without knowing the complete dynamic models of the agents. A proof of convergence for this algorithm is given. An online multi-agent method based on policy iterations is developed using a critic network to solve all the Hamilton-Jacobi-Bellman equations simultaneously for the graphical game.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"73 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":"127073563","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.2013.6760577
Tao Yang, Ziyang Meng, Dimos V. Dimarogonas, K. Johansson
In this paper, we give conditions for the existence of periodic behaviors in a multi-agent system of identical discrete-time double integrators with input saturation constraints. If the feedback gain parameters of the controllers, which are based on relative state measurements of the agent itself and its neighboring agents, are bounded by a value depending on the largest eigenvalue of the Laplacian matrix, then the multi-agent system exhibits a periodic solution for certain initial conditions.
{"title":"Periodic behaviors in multi-agent systems with input saturation constraints","authors":"Tao Yang, Ziyang Meng, Dimos V. Dimarogonas, K. Johansson","doi":"10.1109/CDC.2013.6760577","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760577","url":null,"abstract":"In this paper, we give conditions for the existence of periodic behaviors in a multi-agent system of identical discrete-time double integrators with input saturation constraints. If the feedback gain parameters of the controllers, which are based on relative state measurements of the agent itself and its neighboring agents, are bounded by a value depending on the largest eigenvalue of the Laplacian matrix, then the multi-agent system exhibits a periodic solution for certain initial conditions.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"95 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":"127140156","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.2013.6760677
C. Manes, F. Martinelli
Sensors providing only quantized or binary measurements are present in several automation contexts. A remarkable example is the Radio Frequency IDentification technology when only the detection of the tags is used as information for robot localization. In this paper we propose an algorithm which merges some concepts of the Unscented Kalman Filter (UKF) with some aspects of the Particle Filter (PF). The prediction step of the proposed method is like the prediction step of a standard UKF. On the contrary, the correction step of the UKF can not be trivially implemented due to the presence of binary measurements. For this reason a different correction step is proposed here where the sigma-points weights are modified according to their agreement with the measurements, like it is done for particles of a PF. The main advantage of the proposed algorithm with respect to a PF is that much less particles are needed. Moreover, the way to generate particles in the proposed approach is not random but deterministic. A simulative comparison of the proposed approach with respect to a PF and with respect to a Quantized Kalman Filter is reported in the paper.
{"title":"State estimation under quantized measurements: A Sigma-Point Bayesian approach","authors":"C. Manes, F. Martinelli","doi":"10.1109/CDC.2013.6760677","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760677","url":null,"abstract":"Sensors providing only quantized or binary measurements are present in several automation contexts. A remarkable example is the Radio Frequency IDentification technology when only the detection of the tags is used as information for robot localization. In this paper we propose an algorithm which merges some concepts of the Unscented Kalman Filter (UKF) with some aspects of the Particle Filter (PF). The prediction step of the proposed method is like the prediction step of a standard UKF. On the contrary, the correction step of the UKF can not be trivially implemented due to the presence of binary measurements. For this reason a different correction step is proposed here where the sigma-points weights are modified according to their agreement with the measurements, like it is done for particles of a PF. The main advantage of the proposed algorithm with respect to a PF is that much less particles are needed. Moreover, the way to generate particles in the proposed approach is not random but deterministic. A simulative comparison of the proposed approach with respect to a PF and with respect to a Quantized Kalman Filter is reported in the paper.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"85 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":"124939520","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.2013.6760611
N. Amelina, O. Granichin, Aleksandra Kornivetc
In this paper the applicability of the local voting protocol with nonvanishing step-size for decentralized stochastic network load balancing is studied under nonstationary problem formulation. The network system was considered to have a switched topology, and the control strategy uses noisy and delayed measurements. Nonvanishing (for example, constant) step-size allows to achieve the better convergence rate and copes with time-varying loads and productivities of agents (nodes). Conditions for achieving a suboptimal level of loading agents are established, and an estimate of the appropriate level of suboptimality is given depending on the step-size of the control algorithm, the structure of the averaged network and the statistical properties of noise and delays in measurements. Obtained theoretical results are illustrated by simulations of simultaneously processing of 106 tasks by 1024 agents with 2048 links. It is examined that the performance of the adaptive multi-agent strategy with redistribution of tasks among “connected” neighbors is significantly better than the performance of the strategy without redistribution.
{"title":"Local voting protocol in decentralized load balancing problem with switched topology, noise, and delays","authors":"N. Amelina, O. Granichin, Aleksandra Kornivetc","doi":"10.1109/CDC.2013.6760611","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760611","url":null,"abstract":"In this paper the applicability of the local voting protocol with nonvanishing step-size for decentralized stochastic network load balancing is studied under nonstationary problem formulation. The network system was considered to have a switched topology, and the control strategy uses noisy and delayed measurements. Nonvanishing (for example, constant) step-size allows to achieve the better convergence rate and copes with time-varying loads and productivities of agents (nodes). Conditions for achieving a suboptimal level of loading agents are established, and an estimate of the appropriate level of suboptimality is given depending on the step-size of the control algorithm, the structure of the averaged network and the statistical properties of noise and delays in measurements. Obtained theoretical results are illustrated by simulations of simultaneously processing of 106 tasks by 1024 agents with 2048 links. It is examined that the performance of the adaptive multi-agent strategy with redistribution of tasks among “connected” neighbors is significantly better than the performance of the strategy without redistribution.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"3 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":"125056877","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.2013.6760556
D. Bienstock, M. Chertkov, S. Harnett
Future Grids will integrate time-intermittent renewables and demand response whose fluctuating outputs will create perturbations requiring probabilistic measures of resilience. When smart but uncontrollable resources fluctuate, Optimum Power Flow (OPF), routinely used by the electric power industry to dispatch controllable generation over control areas of transmission networks, can result in higher risks. Our Chance Constrained (CC) OPF corrects the problem and mitigates dangerous fluctuations with minimal changes in the current operational procedure. Assuming availability of a reliable forecast parameterizing the distribution function of the uncertain resources, our CC-OPF satisfies all the constraints with high probability while simultaneously minimizing the cost of economic dispatch. For linear (DC) modeling of power flows, and parametrization of the uncertainty through Gaussian distribution functions the CC-OPF turns into convex (conic) optimization, which allows efficient and scalable cutting-plane implementation. When estimates of the Gaussian parameters are imprecise we robustify CC-OPF deriving its data ambiguous and still scalable implementation.
{"title":"Robust modeling of probabilistic uncertainty in smart Grids: Data ambiguous Chance Constrained Optimum Power Flow","authors":"D. Bienstock, M. Chertkov, S. Harnett","doi":"10.1109/CDC.2013.6760556","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760556","url":null,"abstract":"Future Grids will integrate time-intermittent renewables and demand response whose fluctuating outputs will create perturbations requiring probabilistic measures of resilience. When smart but uncontrollable resources fluctuate, Optimum Power Flow (OPF), routinely used by the electric power industry to dispatch controllable generation over control areas of transmission networks, can result in higher risks. Our Chance Constrained (CC) OPF corrects the problem and mitigates dangerous fluctuations with minimal changes in the current operational procedure. Assuming availability of a reliable forecast parameterizing the distribution function of the uncertain resources, our CC-OPF satisfies all the constraints with high probability while simultaneously minimizing the cost of economic dispatch. For linear (DC) modeling of power flows, and parametrization of the uncertainty through Gaussian distribution functions the CC-OPF turns into convex (conic) optimization, which allows efficient and scalable cutting-plane implementation. When estimates of the Gaussian parameters are imprecise we robustify CC-OPF deriving its data ambiguous and still scalable implementation.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"173 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":"125794938","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.2013.6761039
H. Mangesius
Despite the importance of the linear consensus algorithm for networked systems, yet, there is no agreement on the intrinsic mathematical structure that supports the observed exponential averaging behavior among n agents for any initial condition. Here we add to this discussion in linear consensus theory by introducing relative entropy as a novel Lyapunov function. We show that the configuration space of consensus systems is isometrically embedded into a statistical manifold. On projective n-1-space relative entropy is a common time-invariant Lyapunov function along solutions of the time-varying algorithm. For cases of scaled symmetry of the update law, we expose a gradient flow structure underlying the dynamics that evolve relative entropy in a steepest descent gradient scheme. On that basis we provide exact performance rates and upper bounds based on spectral properties of the update law governing the behavior on the statistical manifold. The condition of scaled symmetry allows to exhibit gradient flow structures for cases where the original update law is neither doubly stochastic, nor self-adjoint. The results related to the gradient flow structure are obtained by exploiting lossless passivity properties.We show that lossless passivity of a dynamical system implies a gradient flow structure on a manifold and vice versa. Exploiting lossless passivity amounts to constructing the combination of dissipation (pseudo)metric with Lyapunov function.
{"title":"New convergence and exact performance results for linear consensus algorithms using relative entropy and lossless passivity properties","authors":"H. Mangesius","doi":"10.1109/CDC.2013.6761039","DOIUrl":"https://doi.org/10.1109/CDC.2013.6761039","url":null,"abstract":"Despite the importance of the linear consensus algorithm for networked systems, yet, there is no agreement on the intrinsic mathematical structure that supports the observed exponential averaging behavior among n agents for any initial condition. Here we add to this discussion in linear consensus theory by introducing relative entropy as a novel Lyapunov function. We show that the configuration space of consensus systems is isometrically embedded into a statistical manifold. On projective n-1-space relative entropy is a common time-invariant Lyapunov function along solutions of the time-varying algorithm. For cases of scaled symmetry of the update law, we expose a gradient flow structure underlying the dynamics that evolve relative entropy in a steepest descent gradient scheme. On that basis we provide exact performance rates and upper bounds based on spectral properties of the update law governing the behavior on the statistical manifold. The condition of scaled symmetry allows to exhibit gradient flow structures for cases where the original update law is neither doubly stochastic, nor self-adjoint. The results related to the gradient flow structure are obtained by exploiting lossless passivity properties.We show that lossless passivity of a dynamical system implies a gradient flow structure on a manifold and vice versa. Exploiting lossless passivity amounts to constructing the combination of dissipation (pseudo)metric with Lyapunov function.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"16 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":"123506284","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.2013.6760207
A. Farhadi, M. Cantoni, P. Dower
This paper considers the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the interior point method that does not exploit problem structure. The second is distributed and based on a consensus algorithm, not specifically tailored to account for system structure, but devised rather to facilitate the management of conflicting computational and communication overheads. It is shown that there is a significant advantage in terms of computation time in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation time of the centralized algorithm grows as O(n4) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that the computation time of the distributed algorithm grows as O(n) with the number n of sub-systems.
{"title":"Computation time analysis of a distributed optimization algorithm applied to automated irrigation networks","authors":"A. Farhadi, M. Cantoni, P. Dower","doi":"10.1109/CDC.2013.6760207","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760207","url":null,"abstract":"This paper considers the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the interior point method that does not exploit problem structure. The second is distributed and based on a consensus algorithm, not specifically tailored to account for system structure, but devised rather to facilitate the management of conflicting computational and communication overheads. It is shown that there is a significant advantage in terms of computation time in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation time of the centralized algorithm grows as O(n4) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that the computation time of the distributed algorithm grows as O(n) with the number n of sub-systems.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"122 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":"123768314","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.2013.6760528
W. Abbas, H. Jaleel, M. Egerstedt
In this paper, we address the issue of activity scheduling of sensors in heterogeneous wireless sensor and actor networks (WSANs), thereby proposing an energy-efficient data collection scheme in such networks. In order to extend the lifetime of heterogeneous WSANs, sensors are activated and deactivated under certain constraints throughout the network operations. Here, we propose a coordination framework in which actors exchange information with each other and decide about the availability of redundant sensors that are eventually deactivated to save energy. In particular, let there be r different types of sensors with each sensor observing a particular sensing parameter. Under the initial deployment of sensors and actors within some field of observation, if an actor v receives information regarding k different sensing parameters, either directly from sensors or through other actors, then our scheme determines a small subset of sensors that are sufficient to provide information regarding the same k sensing parameters to v.
{"title":"Energy-efficient data collection in heterogeneous wireless sensor and actor networks","authors":"W. Abbas, H. Jaleel, M. Egerstedt","doi":"10.1109/CDC.2013.6760528","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760528","url":null,"abstract":"In this paper, we address the issue of activity scheduling of sensors in heterogeneous wireless sensor and actor networks (WSANs), thereby proposing an energy-efficient data collection scheme in such networks. In order to extend the lifetime of heterogeneous WSANs, sensors are activated and deactivated under certain constraints throughout the network operations. Here, we propose a coordination framework in which actors exchange information with each other and decide about the availability of redundant sensors that are eventually deactivated to save energy. In particular, let there be r different types of sensors with each sensor observing a particular sensing parameter. Under the initial deployment of sensors and actors within some field of observation, if an actor v receives information regarding k different sensing parameters, either directly from sensors or through other actors, then our scheme determines a small subset of sensors that are sufficient to provide information regarding the same k sensing parameters to v.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"27 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":"125681873","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.2013.6760685
H. Katayama, Hirotaka Aoki
We design semiglobal and practical discrete-time reduced-order observers for the exact discrete-time model of nonlinear sampled-data strict-feedback systems. As an application of the proposed design method, we design reduced-order observers for sampled-data ships and show their efficiency by experimental and simulation results.
{"title":"Reduced-order observers for nonlinear sampled-data systems with application to marine systems","authors":"H. Katayama, Hirotaka Aoki","doi":"10.1109/CDC.2013.6760685","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760685","url":null,"abstract":"We design semiglobal and practical discrete-time reduced-order observers for the exact discrete-time model of nonlinear sampled-data strict-feedback systems. As an application of the proposed design method, we design reduced-order observers for sampled-data ships and show their efficiency by experimental and simulation results.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"14 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":"126602876","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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