جستجوی مقالات مرتبط با کلیدواژه "سیستم های پرش مارکوف" در نشریات گروه "فنی و مهندسی"

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.

This paper aims to present a novel and comprehensive model for actuator faults to address the problem of robust fault-tolerant controller design for networked control systems (NCSs) in the presence of phenomena such as random delays, model uncertainties, and actuator faults. For this purpose, firstly, the NCS has been appropriately modeled as discrete-time Markovian jump systems (MJSs) with partly-unknown transition probabilities. Then, the problem of mode-dependent static output feedback controller design has been studied not only as a convex optimization problem but also in the form of linear matrix inequalities (LMIs). Notably, the designed controller guaranteesthe stochastic stability of the closed-loop system in the presence of actuator faults and uncertainties. Finally, through numerical simulations, the theoretical results of this study are proved, and it has been shown that this method is more efficient and superior than other methods.

This paper deals with the problem of finite-time stochastic stability and stabilization of networked control systems in the presence of random delay. At first, the network random delay is modeled as a Markov chain, and the resulting closed-loop system is a Markovian jump linear system. Since, due to network complexities, the accurate access to transition probabilities are hard or even impossible, some of the elements in the transition probability matrix are considered as unknown. Then, according to the definition of finite-time stochastic stability for discrete-time Markovian jump systems, a sufficient condition is proposed to guaranty the boundedness of the system states in the sense of mean-square, in a determined time interval. In the next step, the results are extended for the finite-time stochastic stabilization problem of this specific class of systems and the output feedback controller is designed such that the closed-loop system is stochastically finite-time stable. All the results are presented in the form of new linear matrix inequalities (LMIs). The main contribution of this paper is utilizing the static output feedback controller for finite-time stochastic stabilization of the closed-loop system; besides, new LMIs are employed to calculate the output feedback control law. Also, in order to verify the theoretical results and show the applicability of the proposed controller, simulations are performed for two systems.

In this paper, a sliding mode controller for time-delay Markovian jump systems with partly unknown transition probability matrix in presence of disturbance is designed. The proposed method is quite general and includes both systems with completely known and completely unknown transition probability rates. At first, sufficient conditions for existence of linear switching surface are obtained in terms of linear matrix inequalities (LMIs) that guarantee the stochastic stability of sliding mode dynamics. Then, a sliding mode controller is designed such that the closed-loop system’s state trajectories reach the desired sliding surface in a finite time and maintain there for all subsequent times. As a result, the stochastic stability of closed-loop system is guaranteed by applying a specifically designed control law. All of the conditions are presented in terms of linear matrix inequalities and can be simply solved by means of numerical software tools. Finally, anumerical example is given to demonstrate the validity and effectiveness of the proposed method.