Networked control systems are subject to adversary conditions that affect their network topologies.To ensure reliable system operations,network topologies need to be characterized and managed for their impact on the o...Networked control systems are subject to adversary conditions that affect their network topologies.To ensure reliable system operations,network topologies need to be characterized and managed for their impact on the overall system performance.This paper introduces the concept of network robustness depth for this pursuit.Discrete event systems are used as a foundation to model dynamic behavior of network topologies,support their analysis,and carry out their management.Stochastic analysis relates the link reliability probabilities to a probabilistic characterization of network robustness depth.Several topology management strategies are discussed,including passive methods,random strategies,and optimization methodologies.Their respective benefits and limitations are quantified.By using platoon control as a platform of hybrid(continuous and discrete event) systems and packet erasure channels as a communication protocol,the results are demonstrated with case studies.展开更多
This work is concerned with controlled stochastic Kolmogorov systems.Such systems have received much attention recently owing to the wide range of applications in biology and ecology.Starting with the basic premise th...This work is concerned with controlled stochastic Kolmogorov systems.Such systems have received much attention recently owing to the wide range of applications in biology and ecology.Starting with the basic premise that the underlying system has an optimal control,this paper is devoted to designing numerical methods for approximation.Different from the existing literature on numerical methods for stochastic controls,the Kolmogorov systems take values in the first quadrant.That is,each component of the state is nonnegative.The work is designing an appropriate discrete-time controlled Markov chain to be in line with(locally consistent)the controlled diffusion.The authors demonstrate that the Kushner and Dupuis Markov chain approximation method still works.Convergence of the numerical scheme is proved under suitable conditions.展开更多
基金supported in part by the National Science Foundation under Grant No.CPS-1136007
文摘Networked control systems are subject to adversary conditions that affect their network topologies.To ensure reliable system operations,network topologies need to be characterized and managed for their impact on the overall system performance.This paper introduces the concept of network robustness depth for this pursuit.Discrete event systems are used as a foundation to model dynamic behavior of network topologies,support their analysis,and carry out their management.Stochastic analysis relates the link reliability probabilities to a probabilistic characterization of network robustness depth.Several topology management strategies are discussed,including passive methods,random strategies,and optimization methodologies.Their respective benefits and limitations are quantified.By using platoon control as a platform of hybrid(continuous and discrete event) systems and packet erasure channels as a communication protocol,the results are demonstrated with case studies.
基金ARO W911NF1810334NSF under EPCN 1935389the National Renewable Energy Laboratory(NREL)。
文摘This work is concerned with controlled stochastic Kolmogorov systems.Such systems have received much attention recently owing to the wide range of applications in biology and ecology.Starting with the basic premise that the underlying system has an optimal control,this paper is devoted to designing numerical methods for approximation.Different from the existing literature on numerical methods for stochastic controls,the Kolmogorov systems take values in the first quadrant.That is,each component of the state is nonnegative.The work is designing an appropriate discrete-time controlled Markov chain to be in line with(locally consistent)the controlled diffusion.The authors demonstrate that the Kushner and Dupuis Markov chain approximation method still works.Convergence of the numerical scheme is proved under suitable conditions.
