In this paper, we propose a new method to the control of closed kinematic chains (CKC). This method is based on a recently developed singularly perturbed model for CKC. Conventionally, the dynamics of CKC are described by differential-algebraic equations (DAE). Our approach transfers the control of the original DAE system to the control of an artificially created singularly perturbed system in which the slow dynamics corresponds to the original DAE when the small perturbation parameter tends to zero. Compared to control schemes which rely on the solution of nonlinear algebraic constraint equations, the proposed method uses an ODE solver to obtain the dependent coordinates, hence eliminates the need for Newton type iterations and is amenable to real-time implementation. The composite Lyapunov function method is used to show that the closed loop system, when controlled by typical open kinematic chain schemes, achieves local asymptotic trajectory tracking. Simulations and experimental results on a parallel robot, the rice planar delta robot, are also presented to illustrate the efficacy of our method.
{"title":"Control of closed kinematic chains using a singularly perturbed dynamic model","authors":"Zhiyong Wang, F. Ghorbel","doi":"10.1115/1.2171440","DOIUrl":"https://doi.org/10.1115/1.2171440","url":null,"abstract":"In this paper, we propose a new method to the control of closed kinematic chains (CKC). This method is based on a recently developed singularly perturbed model for CKC. Conventionally, the dynamics of CKC are described by differential-algebraic equations (DAE). Our approach transfers the control of the original DAE system to the control of an artificially created singularly perturbed system in which the slow dynamics corresponds to the original DAE when the small perturbation parameter tends to zero. Compared to control schemes which rely on the solution of nonlinear algebraic constraint equations, the proposed method uses an ODE solver to obtain the dependent coordinates, hence eliminates the need for Newton type iterations and is amenable to real-time implementation. The composite Lyapunov function method is used to show that the closed loop system, when controlled by typical open kinematic chain schemes, achieves local asymptotic trajectory tracking. Simulations and experimental results on a parallel robot, the rice planar delta robot, are also presented to illustrate the efficacy of our method.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"46 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125399830","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 : 2006-02-21DOI: 10.1109/CDC.2004.1428828
Ji-hyun Ko, Wonhee Kim, C. Chung
This paper presents dynamic programming therapy to reduce medication and establish long-term immune response against HIV-infection. Understanding HIV-relaled immune system control enables better HIV therapy without using full-treatments. Discrete regimen and continuous regimen characteristics are compared. Controllability of HIV-related immune system is analyzed for better understanding of optimal control in HIV therapy. Using optimal control provides more effective therapy than the full treatment without interruption in terms of controllability analysis. Case studies indicated the proposed therapy induces long-term non-progression while preserving high CD4 T-helper cell count and low virus load in HIV-infected patients.
{"title":"Optimized structured treatment interruption for HIV therapy and its performance analysis on controllability","authors":"Ji-hyun Ko, Wonhee Kim, C. Chung","doi":"10.1109/CDC.2004.1428828","DOIUrl":"https://doi.org/10.1109/CDC.2004.1428828","url":null,"abstract":"This paper presents dynamic programming therapy to reduce medication and establish long-term immune response against HIV-infection. Understanding HIV-relaled immune system control enables better HIV therapy without using full-treatments. Discrete regimen and continuous regimen characteristics are compared. Controllability of HIV-related immune system is analyzed for better understanding of optimal control in HIV therapy. Using optimal control provides more effective therapy than the full treatment without interruption in terms of controllability analysis. Case studies indicated the proposed therapy induces long-term non-progression while preserving high CD4 T-helper cell count and low virus load in HIV-infected patients.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126186264","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 : 2005-09-01DOI: 10.1137/S0363012903436259
M. Fragoso, Nei C. S. Rocha
We derive a stationary filter for the best linear mean square filter (BLMSF) of continuous-time Markovian jump linear systems (MJLS). It amounts here to obtain the convergence of the error covariance matrix of the BLMSF to a stationary value under the assumption of mean square stability of the MJLS and ergodicity of the associated Markovian chain /spl theta//sub t/. It is shown that there exists a unique solution for the stationary Riccati filter equation and this solution is the limit of the error covariance matrix of the BLMSF. The advantage of this scheme is that it is easy to implement since the filter gain can be performed offline, leading to a linear time-invariant filter.
{"title":"Stationary filter for continuous-time Markovian jump linear systems","authors":"M. Fragoso, Nei C. S. Rocha","doi":"10.1137/S0363012903436259","DOIUrl":"https://doi.org/10.1137/S0363012903436259","url":null,"abstract":"We derive a stationary filter for the best linear mean square filter (BLMSF) of continuous-time Markovian jump linear systems (MJLS). It amounts here to obtain the convergence of the error covariance matrix of the BLMSF to a stationary value under the assumption of mean square stability of the MJLS and ergodicity of the associated Markovian chain /spl theta//sub t/. It is shown that there exists a unique solution for the stationary Riccati filter equation and this solution is the limit of the error covariance matrix of the BLMSF. The advantage of this scheme is that it is easy to implement since the filter gain can be performed offline, leading to a linear time-invariant filter.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"323 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122332744","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 : 2005-06-15DOI: 10.1080/00207170500105384
V. Ugrinovskii, H. Pota
This paper considers the problem of decentralized control of interconnected power systems under large changes in real and reactive loads that cause large structural changes in the system model. In addition to this, small changes in load are regulated by small disturbance controllers whose gains are adjusted for variations in power system model due to large changes in. loads. In this paper small disturbance perturbations are handled using decentralised control. The only feedback needed by subsystem controllers is the state of the subsystem itself. The design is carried out within a large-scale Markov jump parameter systems framework. Using an integral quadratic constraints description for system interconnections and disturbances, we obtain necessary and sufficient conditions for the existence of a decentralized controller which stabilizes the overall system and guarantees its optimal robust performance.
{"title":"Decentralized control of power systems via robust control of uncertain Markov jump parameter systems","authors":"V. Ugrinovskii, H. Pota","doi":"10.1080/00207170500105384","DOIUrl":"https://doi.org/10.1080/00207170500105384","url":null,"abstract":"This paper considers the problem of decentralized control of interconnected power systems under large changes in real and reactive loads that cause large structural changes in the system model. In addition to this, small changes in load are regulated by small disturbance controllers whose gains are adjusted for variations in power system model due to large changes in. loads. In this paper small disturbance perturbations are handled using decentralised control. The only feedback needed by subsystem controllers is the state of the subsystem itself. The design is carried out within a large-scale Markov jump parameter systems framework. Using an integral quadratic constraints description for system interconnections and disturbances, we obtain necessary and sufficient conditions for the existence of a decentralized controller which stabilizes the overall system and guarantees its optimal robust performance.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121076434","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 : 2004-12-17DOI: 10.1109/CDC.2004.1428662
D. Peaucelle, D. Arzelier, C. Farges
A new approach has been exposed recently for the synthesis of sets of controllers. Among other features, this approach handles the fragility problem. These promising results, developed for static-output feedback synthesis, suffer from being formulated as non convex optimisation problems. The aim of the article is to explore the distinctive case of state-feedback control. Convex LMI optimisation problems are derived for resilient (non-fragile) control with H/sub /spl infin// guaranteed performance. The essential contribution is that well-known LMI results for state-feedback design can be easily extended to the design of resilient control.
{"title":"LMI results for resilient state-feedback with H/sub /spl infin// performance","authors":"D. Peaucelle, D. Arzelier, C. Farges","doi":"10.1109/CDC.2004.1428662","DOIUrl":"https://doi.org/10.1109/CDC.2004.1428662","url":null,"abstract":"A new approach has been exposed recently for the synthesis of sets of controllers. Among other features, this approach handles the fragility problem. These promising results, developed for static-output feedback synthesis, suffer from being formulated as non convex optimisation problems. The aim of the article is to explore the distinctive case of state-feedback control. Convex LMI optimisation problems are derived for resilient (non-fragile) control with H/sub /spl infin// guaranteed performance. The essential contribution is that well-known LMI results for state-feedback design can be easily extended to the design of resilient control.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126480412","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 : 2004-12-17DOI: 10.1109/CDC.2004.1429596
Ioannis Lestas, G. Vinnicombe
We investigate the regime where instability in deterministic fluid flow models for congestion control analysis in data networks corresponds to a significant increase in the variance of the flow in stochastic networks. This is shown to be the case when there are large number of packets in flight with small queue thresholds. The analysis is carried out by modelling an M/M/1 queue with delayed feedback as a stochastic hybrid system and analyzing the transient probability distribution of the states with partial differential equations. We also introduce a deterministic nonlinear dynamic queue model that captures the dynamics of the stochastic feedback system. Most of the literature on congestion control analysis using deterministic models, is currently based on queueing models that are valid in one of the extreme cases of negligible queueing delays relative to propagation delays (these are modelled with static functions) or never emptying queues (modelled as integrators). The proposed model is shown to be valid both in these extreme conditions, as well as intermediate regimes of large delays, emptying queues and significant queue dynamics.
{"title":"How good are deterministic models for analyzing congestion control in delayed stochastic networks?","authors":"Ioannis Lestas, G. Vinnicombe","doi":"10.1109/CDC.2004.1429596","DOIUrl":"https://doi.org/10.1109/CDC.2004.1429596","url":null,"abstract":"We investigate the regime where instability in deterministic fluid flow models for congestion control analysis in data networks corresponds to a significant increase in the variance of the flow in stochastic networks. This is shown to be the case when there are large number of packets in flight with small queue thresholds. The analysis is carried out by modelling an M/M/1 queue with delayed feedback as a stochastic hybrid system and analyzing the transient probability distribution of the states with partial differential equations. We also introduce a deterministic nonlinear dynamic queue model that captures the dynamics of the stochastic feedback system. Most of the literature on congestion control analysis using deterministic models, is currently based on queueing models that are valid in one of the extreme cases of negligible queueing delays relative to propagation delays (these are modelled with static functions) or never emptying queues (modelled as integrators). The proposed model is shown to be valid both in these extreme conditions, as well as intermediate regimes of large delays, emptying queues and significant queue dynamics.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630160","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 : 2004-12-17DOI: 10.1109/CDC.2004.1428758
Ioannis Lestas, G. Vinnicombe
In this paper we propose an algorithm for combined control of routing and flow, which is based on fluid flow deterministic network models. This leads to globally optimal solutions, in the sense that it solves the problem of maximizing an aggregate utility when all possible paths from sources to destinations could be made available. Flow control is carried out in an and to end manner with the user deciding how to split the flow among the paths it is using and with new paths being added on a shortest path basis. The algorithm avoids the use of unnecessary paths and is always guaranteed to converge to the optimal solution in spite of the fact that routing decisions are based entirely on congestion. Despite the significant complexity, as a result of the source routing approach and the fact that globally optimal solutions could involve a large number of paths, this algorithm provides a direction in which to investigate means of guaranteeing to get the most out of a network by providing appropriate alternative routes for flow control.
{"title":"Combined control of routing and flow: a multipath routing approach","authors":"Ioannis Lestas, G. Vinnicombe","doi":"10.1109/CDC.2004.1428758","DOIUrl":"https://doi.org/10.1109/CDC.2004.1428758","url":null,"abstract":"In this paper we propose an algorithm for combined control of routing and flow, which is based on fluid flow deterministic network models. This leads to globally optimal solutions, in the sense that it solves the problem of maximizing an aggregate utility when all possible paths from sources to destinations could be made available. Flow control is carried out in an and to end manner with the user deciding how to split the flow among the paths it is using and with new paths being added on a shortest path basis. The algorithm avoids the use of unnecessary paths and is always guaranteed to converge to the optimal solution in spite of the fact that routing decisions are based entirely on congestion. Despite the significant complexity, as a result of the source routing approach and the fact that globally optimal solutions could involve a large number of paths, this algorithm provides a direction in which to investigate means of guaranteeing to get the most out of a network by providing appropriate alternative routes for flow control.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131641309","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 : 2004-12-17DOI: 10.1109/CDC.2004.1429001
J. Mitchell, S. Rasmussen, A. Sparks
We investigate the effects of target arrival rate on the communication and mission performance of cooperatively controlled uninhabited aerial vehicles with task allocation performed by iterative network flow. Specifically, we quantify the effect of arrival rate on observed statistics of communication and mission performance. The statistics of interest are peak communication data rate, execution defects. The effects are seen in a series of vehicle-target scenarios simulated in the US Air Force Research Laboratory's MultiUAV environment.
{"title":"Effects of target arrival rate on mission performance of cooperatively controlled UAVs with communication constraints","authors":"J. Mitchell, S. Rasmussen, A. Sparks","doi":"10.1109/CDC.2004.1429001","DOIUrl":"https://doi.org/10.1109/CDC.2004.1429001","url":null,"abstract":"We investigate the effects of target arrival rate on the communication and mission performance of cooperatively controlled uninhabited aerial vehicles with task allocation performed by iterative network flow. Specifically, we quantify the effect of arrival rate on observed statistics of communication and mission performance. The statistics of interest are peak communication data rate, execution defects. The effects are seen in a series of vehicle-target scenarios simulated in the US Air Force Research Laboratory's MultiUAV environment.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127976180","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 : 2004-12-17DOI: 10.1109/CDC.2004.1430332
J. Cortés, S. Martínez, F. Bullo
This paper presents coordination algorithms for groups of mobile agents performing deployment and coverage tasks. As an important modeling constraint, we assume that each mobile agent has a limited sensing or communication radius. We focus on (1) a comprehensive smoothness analysis of a class of locational optimization functions (including a generalized statement of the conservation-of-mass law), and (2) a discrete-time convergence result based on a recently-developed generalized statement of LaSalle invariance principle. Our coordination algorithms have convergence guarantees and are spatially distributed with respect to appropriate proximity graphs. Numerical simulations illustrate the results.
{"title":"Coordinated deployment of mobile sensing networks with limited-range interactions","authors":"J. Cortés, S. Martínez, F. Bullo","doi":"10.1109/CDC.2004.1430332","DOIUrl":"https://doi.org/10.1109/CDC.2004.1430332","url":null,"abstract":"This paper presents coordination algorithms for groups of mobile agents performing deployment and coverage tasks. As an important modeling constraint, we assume that each mobile agent has a limited sensing or communication radius. We focus on (1) a comprehensive smoothness analysis of a class of locational optimization functions (including a generalized statement of the conservation-of-mass law), and (2) a discrete-time convergence result based on a recently-developed generalized statement of LaSalle invariance principle. Our coordination algorithms have convergence guarantees and are spatially distributed with respect to appropriate proximity graphs. Numerical simulations illustrate the results.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130956680","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 : 2004-12-17DOI: 10.1109/CDC.2004.1429003
Y. Liu, J. B. Cruz, A. Sparks
This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.
{"title":"Coordinating networked uninhabited air vehicles for persistent area denial","authors":"Y. Liu, J. B. Cruz, A. Sparks","doi":"10.1109/CDC.2004.1429003","DOIUrl":"https://doi.org/10.1109/CDC.2004.1429003","url":null,"abstract":"This paper explores the problem of cooperative control among multiple networked unmanned air vehicles (UAVs) for persistent area denial (PAD) mission. An adaptive Markov chain model is used to predict the locations of pop-up threats. The mixed information of predicted pop-up threats and actual pop-up targets is utilized to develop cooperative strategies for networked UAVs. The approach is illustrated by use of a simulation test bed for multiple networked UAVs and Monte Carlo simulation runs to evaluate our cooperative strategy. Both theoretical analysis and simulation results are presented to demonstrate the effectiveness of using predicted pop-up information in improving the overall PAD mission performance.","PeriodicalId":254457,"journal":{"name":"2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131793528","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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