Pub Date : 2021-12-14DOI: 10.1109/CDC45484.2021.9683436
Jorge San Martín, Takéo Takahashi, M. Tucsnak
We are interested in a system nonlinearly coupling a transport equation and an ODE. This system, inspired by the classical Kermack-Mckendrick epidemic model with age of infection, describes the evolution of an epidemic in the presence of vaccination and of a flux of susceptible population. Our main result provides effective input to state stability (ISS) estimates, assuming the application of an appropriate vaccination policy. The nonlinear character of the system and the presence of state constraints require a detailed preliminary analysis of the system well-posedness.
{"title":"Input to state stability of the Kermack-Mckendrick age structured epidemic model*","authors":"Jorge San Martín, Takéo Takahashi, M. Tucsnak","doi":"10.1109/CDC45484.2021.9683436","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683436","url":null,"abstract":"We are interested in a system nonlinearly coupling a transport equation and an ODE. This system, inspired by the classical Kermack-Mckendrick epidemic model with age of infection, describes the evolution of an epidemic in the presence of vaccination and of a flux of susceptible population. Our main result provides effective input to state stability (ISS) estimates, assuming the application of an appropriate vaccination policy. The nonlinear character of the system and the presence of state constraints require a detailed preliminary analysis of the system well-posedness.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129660826","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683396
S. Battilotti
We propose a framework for designing global observers for nonlinear systems with disturbances under geometric conditions based on orbital symmetries. Under some additional restrictions these orbital symmetry-based conditions boil down to geometric homogeneity (at infinity) conditions. Our observers are the result of the combination of a first filter, a state norm estimator, with a second filter adaptively tuned by the first and when compared with the existing literature have a completely novel structure, inherited by the orbital symmetry-based conditions. The second filter adaptively exploits the properties of orbital symmetries of the system to achieve global convergence properties by steering, first, the state estimate close to the state trajectory and acting locally afterwards.
{"title":"An orbital symmetry-based approach to observer design for systems with disturbances","authors":"S. Battilotti","doi":"10.1109/CDC45484.2021.9683396","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683396","url":null,"abstract":"We propose a framework for designing global observers for nonlinear systems with disturbances under geometric conditions based on orbital symmetries. Under some additional restrictions these orbital symmetry-based conditions boil down to geometric homogeneity (at infinity) conditions. Our observers are the result of the combination of a first filter, a state norm estimator, with a second filter adaptively tuned by the first and when compared with the existing literature have a completely novel structure, inherited by the orbital symmetry-based conditions. The second filter adaptively exploits the properties of orbital symmetries of the system to achieve global convergence properties by steering, first, the state estimate close to the state trajectory and acting locally afterwards.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127539423","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683565
Jie Hu, P. Pagilla, S. Darbha
Workpiece localization is the process of obtaining the location of a workpiece in a robot workspace. The location (position and orientation) is represented by the transformation between the workpiece (local) coordinate frame and the reference (world) frame. In this work, we propose a workpiece localization strategy to automate the localization process by collecting data sequentially and efficiently without the two common restrictive assumptions: the data used to calculate the transformation is readily available and the correspondence between the features used for calculation is known. Correspondingly, two subproblems are involved: (1) determining the correspondence between the measured data and the CAD model data, and (2) determining the next-best-views (NBVs) in case of limited measurement data. We assume the workpiece is convex and has at least three flat surfaces. We use the extended Gaussian images (EGIs) from the Gauss map of both the CAD model point clouds and measured point clouds to find the flat surfaces on the workpiece. A mixed integer convex optimization problem is solved to estimate the correspondence and the rotation between the flat surfaces in the CAD model and the measured point clouds. The translation part of the homogeneous transformation is obtained by solving a least-squares problem using the estimated correspondence. Potential views for further measuring the workpiece are generated by evaluating a defined search region to find the NBVs based on a specified criterion. The workpiece is considered to be fully localized when the distances in the estimated homogeneous transformation matrices are within a predefined threshold. Simulation results are provided to show the effectiveness of the proposed localization method.
{"title":"A Novel Method for the Localization of Convex Workpieces in Robot Workspace Using Gauss Map","authors":"Jie Hu, P. Pagilla, S. Darbha","doi":"10.1109/CDC45484.2021.9683565","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683565","url":null,"abstract":"Workpiece localization is the process of obtaining the location of a workpiece in a robot workspace. The location (position and orientation) is represented by the transformation between the workpiece (local) coordinate frame and the reference (world) frame. In this work, we propose a workpiece localization strategy to automate the localization process by collecting data sequentially and efficiently without the two common restrictive assumptions: the data used to calculate the transformation is readily available and the correspondence between the features used for calculation is known. Correspondingly, two subproblems are involved: (1) determining the correspondence between the measured data and the CAD model data, and (2) determining the next-best-views (NBVs) in case of limited measurement data. We assume the workpiece is convex and has at least three flat surfaces. We use the extended Gaussian images (EGIs) from the Gauss map of both the CAD model point clouds and measured point clouds to find the flat surfaces on the workpiece. A mixed integer convex optimization problem is solved to estimate the correspondence and the rotation between the flat surfaces in the CAD model and the measured point clouds. The translation part of the homogeneous transformation is obtained by solving a least-squares problem using the estimated correspondence. Potential views for further measuring the workpiece are generated by evaluating a defined search region to find the NBVs based on a specified criterion. The workpiece is considered to be fully localized when the distances in the estimated homogeneous transformation matrices are within a predefined threshold. Simulation results are provided to show the effectiveness of the proposed localization method.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127338111","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683191
S. Ardizzoni, L. Consolini, M. Laurini, M. Locatelli
The purpose of this work is to introduce and characterize the Bounded Acceleration Shortest Path (BASP) problem, a generalization of the Shortest Path (SP) problem. This problem is associated to a graph: nodes represent positions of a mobile vehicle and arcs are associated to pre-assigned geometric paths that connect these positions. BASP consists in finding the minimum-time path between two nodes. Differently from SP, we require that the vehicle satisfy bounds on maximum and minimum acceleration and speed, that depend on the vehicle position on the currently traveled arc. We propose solution algorithms that achieves polynomial time-complexity under some additional hypotheses on problem data.
{"title":"Efficient solution algorithms for the Bounded Acceleration Shortest Path problem","authors":"S. Ardizzoni, L. Consolini, M. Laurini, M. Locatelli","doi":"10.1109/CDC45484.2021.9683191","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683191","url":null,"abstract":"The purpose of this work is to introduce and characterize the Bounded Acceleration Shortest Path (BASP) problem, a generalization of the Shortest Path (SP) problem. This problem is associated to a graph: nodes represent positions of a mobile vehicle and arcs are associated to pre-assigned geometric paths that connect these positions. BASP consists in finding the minimum-time path between two nodes. Differently from SP, we require that the vehicle satisfy bounds on maximum and minimum acceleration and speed, that depend on the vehicle position on the currently traveled arc. We propose solution algorithms that achieves polynomial time-complexity under some additional hypotheses on problem data.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127483967","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9682937
Shaopan Guo, Xiangyu Meng, Baozhu Du
In this paper, the consensus problem is studied for double-integrator multi-agent systems with edge-based event- triggered communication. More specifically, two agents connected by an edge mutually sample the relative state information when a designed triggering condition is satisfied. The triggering mechanism is introduced to reduce the communication frequency. To make the triggering mechanism implementable, a positive minimum inter-event time is guaranteed in all communication links in the network. All designs use only local neighborhood information. Based on Lyapunov analysis, the proposed algorithm makes all the agents converge to a consensus trajectory asymptotically.
{"title":"Fully Distributed Event-Triggered Consensus of Double-Integrator Multi-Agent Systems","authors":"Shaopan Guo, Xiangyu Meng, Baozhu Du","doi":"10.1109/CDC45484.2021.9682937","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9682937","url":null,"abstract":"In this paper, the consensus problem is studied for double-integrator multi-agent systems with edge-based event- triggered communication. More specifically, two agents connected by an edge mutually sample the relative state information when a designed triggering condition is satisfied. The triggering mechanism is introduced to reduce the communication frequency. To make the triggering mechanism implementable, a positive minimum inter-event time is guaranteed in all communication links in the network. All designs use only local neighborhood information. Based on Lyapunov analysis, the proposed algorithm makes all the agents converge to a consensus trajectory asymptotically.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130073492","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683058
H. Pinto, T. R. Oliveira, L. Hsu, M. Krstić
This paper provides a new stabilization control method for linear time-invariant systems subject to known time-varying measurement delays and matched unknown nonlinear disturbances that may represent actuator faults. Part of the state vector is assumed to be unmeasured in current time. Hence, the proposed method utilizes an open-loop predictor associated with a state observer based on the Super-Twisting Algorithm in order to compensate the delays and estimate the unmeasured state variables. In particular, this nonlinear observer-based structure allows for the reconstruction of the non-modeled fault signals which, unlike the existing literature, are not supposed to be generated by a known exogenous dynamic system, being also robust to parametric uncertainties, whereas the predictor advances in time the delayed output signal. Then, a sliding mode control law is developed to achieve an ideal sliding mode and guarantee global stabilization even in the presence of a more general class of perturbations, non-modeled disturbances, parametric uncertainties and delays due to the inclusion of the Super-Twisting observer. Numerical simulations illustrate the efficiency of the proposed approach.
{"title":"Sliding Mode Control for Stabilization and Disturbance Rejection of Uncertain Systems with Output Delays via Predictor and Super-Twisting Observer","authors":"H. Pinto, T. R. Oliveira, L. Hsu, M. Krstić","doi":"10.1109/CDC45484.2021.9683058","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683058","url":null,"abstract":"This paper provides a new stabilization control method for linear time-invariant systems subject to known time-varying measurement delays and matched unknown nonlinear disturbances that may represent actuator faults. Part of the state vector is assumed to be unmeasured in current time. Hence, the proposed method utilizes an open-loop predictor associated with a state observer based on the Super-Twisting Algorithm in order to compensate the delays and estimate the unmeasured state variables. In particular, this nonlinear observer-based structure allows for the reconstruction of the non-modeled fault signals which, unlike the existing literature, are not supposed to be generated by a known exogenous dynamic system, being also robust to parametric uncertainties, whereas the predictor advances in time the delayed output signal. Then, a sliding mode control law is developed to achieve an ideal sliding mode and guarantee global stabilization even in the presence of a more general class of perturbations, non-modeled disturbances, parametric uncertainties and delays due to the inclusion of the Super-Twisting observer. Numerical simulations illustrate the efficiency of the proposed approach.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130163595","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683000
K. Mishra, James Reed, Maxwell J. Wu, K. Barton, C. Vermillion
For many emerging repetitive control applications such as wind and marine energy generation systems, gait-cycle following in legged locomotion, remote sensing, surveillance, and reconnaissance, the primary objective for repetitive control (RC) is optimization of a cycle cost such as the lap-averaged power generated and metabolic cost of locomotion, as opposed to the classical requirement of tracking a known reference trajectory by the system output. For this newer class of applications, only a range of reference trajectories suitable for cyclic operation is known a priori, the range potentially encapsulating various operational constraints, and as part of repetitive control, it is desired that over a number of operation cycles, the cycle cost, or the economic metric, is optimized. With this underlying motivation, a hierarchical solution is presented, wherein the inner loop includes a classical repetitive controller that tracks a reference trajectory of known period, and the outer loop iteratively learns the desired reference trajectory using a combination of the system and cost function models and the measured cycle cost. This approach results in optimum steady-state cyclic operation. A steepest descent type algorithm is used in the outer loop, and via Lyapunov-like arguments, the existence of tuning parameters resulting in robust and optimal steady-state cyclic operation is discussed. Appropriate guidelines for parameter tuning are presented, and the proposed method is numerically validated using an example of an inverted pendulum.
{"title":"Hierarchical Structures for Economic Repetitive Control","authors":"K. Mishra, James Reed, Maxwell J. Wu, K. Barton, C. Vermillion","doi":"10.1109/CDC45484.2021.9683000","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683000","url":null,"abstract":"For many emerging repetitive control applications such as wind and marine energy generation systems, gait-cycle following in legged locomotion, remote sensing, surveillance, and reconnaissance, the primary objective for repetitive control (RC) is optimization of a cycle cost such as the lap-averaged power generated and metabolic cost of locomotion, as opposed to the classical requirement of tracking a known reference trajectory by the system output. For this newer class of applications, only a range of reference trajectories suitable for cyclic operation is known a priori, the range potentially encapsulating various operational constraints, and as part of repetitive control, it is desired that over a number of operation cycles, the cycle cost, or the economic metric, is optimized. With this underlying motivation, a hierarchical solution is presented, wherein the inner loop includes a classical repetitive controller that tracks a reference trajectory of known period, and the outer loop iteratively learns the desired reference trajectory using a combination of the system and cost function models and the measured cycle cost. This approach results in optimum steady-state cyclic operation. A steepest descent type algorithm is used in the outer loop, and via Lyapunov-like arguments, the existence of tuning parameters resulting in robust and optimal steady-state cyclic operation is discussed. Appropriate guidelines for parameter tuning are presented, and the proposed method is numerically validated using an example of an inverted pendulum.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130574375","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683226
Dina Mikhaylenko, Marcel Krames, Ping Zhang
Cyber security is nowadays an important research area in cyber-physical systems (CPS) to prevent possible disastrous physical consequences. In this paper, we consider stealthy targeted local covert attacks, which take into account the target of the adversary explicitly and need fewer disruption resources than standard covert attacks. We show conditions when the local attack can achieve its target and simultaneously remain stealthy. The provided conditions help to analyze the CPS on potential fraud and enhance the cyber security. Experimental results on the three-tank system are provided to illustrate the main results.
{"title":"Stealthy Targeted Local Covert Attacks on Cyber-Physical Systems","authors":"Dina Mikhaylenko, Marcel Krames, Ping Zhang","doi":"10.1109/CDC45484.2021.9683226","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683226","url":null,"abstract":"Cyber security is nowadays an important research area in cyber-physical systems (CPS) to prevent possible disastrous physical consequences. In this paper, we consider stealthy targeted local covert attacks, which take into account the target of the adversary explicitly and need fewer disruption resources than standard covert attacks. We show conditions when the local attack can achieve its target and simultaneously remain stealthy. The provided conditions help to analyze the CPS on potential fraud and enhance the cyber security. Experimental results on the three-tank system are provided to illustrate the main results.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130674397","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683784
Benjamin J. Gravell, T. Summers
Robust stability and stochastic stability have separately seen intense study in control theory since its inception. In this work we establish relations between these properties for discrete-time systems. Specifically, we examine a robustness framework which models the inherent uncertainty and variation in the system dynamics which arise in model-based learning control methods such as adaptive control and reinforcement learning. We provide results which guarantee mean-square stability margins in terms of multiplicative noises which affect the nominal dynamics, as well as connections to prior work which together imply that robust stability and mean-square stability are, in a certain sense, equivalent.
{"title":"Stochastic Stability via Robustness of Linear Systems","authors":"Benjamin J. Gravell, T. Summers","doi":"10.1109/CDC45484.2021.9683784","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683784","url":null,"abstract":"Robust stability and stochastic stability have separately seen intense study in control theory since its inception. In this work we establish relations between these properties for discrete-time systems. Specifically, we examine a robustness framework which models the inherent uncertainty and variation in the system dynamics which arise in model-based learning control methods such as adaptive control and reinforcement learning. We provide results which guarantee mean-square stability margins in terms of multiplicative noises which affect the nominal dynamics, as well as connections to prior work which together imply that robust stability and mean-square stability are, in a certain sense, equivalent.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132014721","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683053
A. Andriën, D. Antunes
This paper tackles the problem of identifying the parameters of a class of stochastic switched systems, where the active subsystem is determined by a Markov chain. This class includes autoregressive models with exogenous inputs (ARX) for which the parameters switch according to a Markov chain and general Markov Jump Linear Systems (MJLSs) with full-state information. The transition probabilities of the Markov chain are assumed to be known, but the active subsystem is unknown. A recursive identification method for the joint maximum a posteriori probability estimate of these parameters and of the unknown mode is proposed relying on relaxed dynamic programming. The method is guaranteed to provide an estimate whose joint posteriori probability is within a constant factor of that of the optimal estimate while reducing the computational complexity. The method is illustrated through a numerical example.
{"title":"Near-Optimal Recursive Identification for Markov Switched Systems","authors":"A. Andriën, D. Antunes","doi":"10.1109/CDC45484.2021.9683053","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683053","url":null,"abstract":"This paper tackles the problem of identifying the parameters of a class of stochastic switched systems, where the active subsystem is determined by a Markov chain. This class includes autoregressive models with exogenous inputs (ARX) for which the parameters switch according to a Markov chain and general Markov Jump Linear Systems (MJLSs) with full-state information. The transition probabilities of the Markov chain are assumed to be known, but the active subsystem is unknown. A recursive identification method for the joint maximum a posteriori probability estimate of these parameters and of the unknown mode is proposed relying on relaxed dynamic programming. The method is guaranteed to provide an estimate whose joint posteriori probability is within a constant factor of that of the optimal estimate while reducing the computational complexity. The method is illustrated through a numerical example.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"2016 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132030162","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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