List of Articles Networked Control System

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  1 - A Stochastic Lyapunov Theorem with Application to Stability Analysis of Networked Control Systems
  Babak Tavassoli Parviz Jabehdar Maralani
  10.7508/jist.2014.02.004
  The source of randomness in stochastic systems is an input with stochastic behavior as treated in the existing literature. Special types of stochastic processes such as the Wiener process or the Brownian motion have served as an adequate model of such an input for years More

  The source of randomness in stochastic systems is an input with stochastic behavior as treated in the existing literature. Special types of stochastic processes such as the Wiener process or the Brownian motion have served as an adequate model of such an input for years. The body of stochastic systems theory is elegantly shaped around such input models. An example is the Itô’s formula. With development of new applications, we are faced with various phenomena that are more demanding from a stochastic modeling approach. To cope with this problem we restate the stochastic Lyapunov theorem such that it can be applied to a wider class of stochastic systems. In this paper stochastic systems are considered without imposing assumptions on the nature of the stochastic input and the way it affects the sample trajectories. Lyapunov stability theorem is represented for this type of systems in terms of a stability notion that generalizes the notion of stability in moments. As a result, the new theorem finds a larger domain of applications while it can be reduced to some known versions of the stochastic Lyapunov theorem. As an application, an existing deterministic result for nonlinear networked control systems is extended to a more practical probabilistic setting which extends the available analysis tools for checking the stability of continuous-time nonlinear networked control systems in the stochastic setting. The results are applied to a two-channel magnetic levitation system which is controlled over a local communication network to obtain a bound on the rate of transmission failures due to the presence of noise in the industrial environment. Manuscript profile
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  2 - Stability Analysis of Networked Control Systems under Denial of Service Attacks using Switching System Theory
  Mohammad SayadHaghighi Faezeh Farivar
  With the development of computer networks, packet-based data transmission has found its way to Cyber-Physical Systems (CPS) and especially, networked control systems (NCS). NCSs are distributed industrial processes in which sensors and actuators exchange information bet More

  With the development of computer networks, packet-based data transmission has found its way to Cyber-Physical Systems (CPS) and especially, networked control systems (NCS). NCSs are distributed industrial processes in which sensors and actuators exchange information between the physical plant and the controller via a network. Any loss of data or packet in the network links affects the performance of the physical system and its stability. This loss could be due to natural congestions in network or a result of intentional Denial of Service (DoS) attacks. In this paper, we analytically study the stability of NCSs with the possibility of data loss in the feed-forward link by modelling the system as a switching one. When data are lost (or replaced with a jammed or bogus invalid signal/packet) in the forward link, the physical system will not receive the control input sent from the controller. In this study, NCS is regarded as a stochastic switching system by using a two-position Markov jump model. In State 1, the control signal/packet passes through and gets to the system, while in State 2, the signal or packet is lost. We analyze the stability of system in State 2 by considering the situation as an open-loop control scenario with zero input. The proposed stochastic switching system is studied in both continuous and discrete-time spaces to see under what conditions it satisfies Lyapunov stability. The stability conditions are obtained according to random dwell times of the system in each state. Finally, the model is simulated on a DC motor as the plant. The results confirm the correctness of the obtained stability conditions. Manuscript profile