Stochastic Packet Research Articles

[formula omitted] control of uncertain T–S fuzzy networked control systems with actuator faults under stochastic packet loss-dependent event-triggered schemes

In this paper, the H∞ control problem of uncertain T–S fuzzy networked control systems (NCSs) with actuator faults under stochastic packet loss-dependent event-triggered schemes (SPDETS) is investigated. First, in order to improve the efficiency of communication networks, an innovative SPDETS is proposed, which relies on stochastic packet losses during data transmission and event-triggered conditions. Second, a packet loss-dependent switching-like controller is designed to maintain the control performance of the system. Third, some potential actuator faults are taken into account, besides considering system uncertainty and network-induced delay. Using the Lyapunov–Krasovskii theorem, sufficient conditions to guarantee the system stability for a specified performance index are presented, and design conditions are given for a switching-like fault-tolerant controller that compensates for the actuator efficiency loss. Finally, the effectiveness of the proposed control scheme is verified through the CSTR simulation example.

Reachable set performance and quantized sampled-data synchronization analysis of neural networks under random packet dropouts via enhanced looped functional

The study aims to present the synchronization concerns of neural networks with stochastic packet dropouts utilizing a quantized memory sampled-data control (QMSDC) scheme and the problem of reachable set analysis (RSA) for NNs under the influence of external disturbances are discussed. To do this, a novel free-weighting matrix integral inequality (FWMII) is proposed with an augmented Lyapunov-functional. Furthermore, at this time, we show that the proposed inequality is less conservative due to the delay information. In the meantime, a novel enhanced looped function is created that utilizes not only sampling information but also incorporates both transmission delay information and a quantized sampling pattern. Next, using the proposed FWMII technique, several sufficient conditions in terms of linear matrix inequalities (LMIs) are derived to suggest how an augmented closed-loop system can achieves stochastic mean-square exponential synchronization under random packet loss situations. Finally, the proposed approach demonstrates its usefulness and superiority by comparing it with existing methods through numerical simulation of the secure communications.

Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts

Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts

Adaptive Optimal Control of Networked Nonlinear Systems With Stochastic Sensor and Actuator Dropouts Based on Reinforcement Learning.

This article investigates the adaptive optimal control problem for networked discrete-time nonlinear systems with stochastic packet dropouts in both controller-to-actuator and sensor-to-controller channels. A Bernoulli model-based Hamilton-Jacobi-Bellman (BHJB) equation is first developed to deal with the corresponding nonadaptive optimal control problem with known system dynamics and probability models of packet dropouts. The solvability of the nonadaptive optimal control problem is analyzed, and the stability and optimality of the resulting closed-loop system are proven. Two reinforcement learning (RL)-based policy iteration (PI) and value iteration (VI) algorithms are further developed to obtain the solution to the BHJB equation, and their convergence analysis is also provided. Furthermore, in the absence of a priori knowledge of partial system dynamics and probabilities of packet dropouts, two more online RL-based PI and VI algorithms are developed by using critic-actor approximators and packet dropout probability estimator. It is shown that the concerned adaptive optimal control problem can be solved by the proposed online RL-based PI and VI algorithms. Finally, simulation studies of a single-link manipulator are provided to illustrate the effectiveness of the proposed approaches.

Investigation of stochastic models of packet generation in computer networks

Stochastic packet generation models are models that are used to generate traffic in computer networks with certain characteristics. These models can be used to simulate network activity and test network performance. Standard data transmission on the network is packet generation with delays, in which packets are sent at certain intervals. Various stochastic models can be used to generate delayed packets, including uniform distribution, exponential distribution, and Erlang distribution. In this work, an experimental setup was assembled and a client-server application was developed to conduct research and analyze the performance of the data transmission channel. An algorithm has been proposed that allows to restore the moment characteristics of a random value of the interval between packets for further use of queuing models. The analysis of the distribution laws on the performance of the experimental network sample was performed and estimates of the efficiency of channel use and the average packet generation time in network segments, as well as histograms of delays according to the distribution laws, were obtained. An experimental setup was created, and a client-server application was developed to analyze the performance of the data transmission channel. An algorithm for restoring the moment characteristics of the time intervals between packets is proposed. The analysis of the distribution laws on network performance was carried out, estimates of the efficiency of channel use and the average packet generation time in network segments were obtained, as well as histograms of delays according to the distribution laws. The generation of packets with delays according to stochastic distribution laws (uniform, exponential, Erlang) is of great importance in modeling and analyzing the operation of network systems. Also, the generation of packets with delays according to the above-mentioned distribution laws allows testing and debugging of network applications and devices in conditions close to real ones. This allows to identify possible problems and improve the operation of network systems. As a result of the experiment, an algorithm was proposed that allows to restore the moment characteristics of a random value of the interval between packets for further use of queuing models. Also, the analysis of the influence of distribution laws on the performance of the experimental network sample was performed and estimates of the efficiency of channel use and the average packet generation time in network segments, as well as histograms of delays according to distribution laws, were obtained.

Fuzzy Memory Sampled-Data Controller Design for PMSG-Based WECS With Stochastic Packet Dropouts

The fuzzy memory sampled-data control problem for permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS) with stochastic packet dropouts is discussed in this paper. To do this, the PMSG-based WECS dynamics are firstly modelled by a set of fuzzy IF-THEN rules of the Takagi–Sugeno (T–S) fuzzy model because of high nonlinearity. And then, to minimize design conservatism, a suitable augmented looped-type Lyapunov functional along with a novel integral inequality is established by using the sampling mode information with signal transmission delay. Further, a fuzzy memory-based sampled-data controller is designed to obtain the asymptotic stability condition under the circumstances of packet dropouts, and simultaneously, disturbance reduction is confirmed. Thereafter, the associated fuzzy controller gains can be computed by solving a number of linear matrix inequalities (LMIs). Finally, the application of the suggested method to a real-world system is proved using PMSG-based WECS, and the mathematical Rossler's system demonstrates the effectiveness and superiority of the proposed technique over the existing method.

Mixed [formula omitted] control for discrete-time periodic Markov jump systems with quantization effects and packet loss compensation

This article concentrates on the issue of the mixed H2/H∞ state feedback control for discrete-time periodic Markov jump systems with quantization effects and packet loss compensation. Considering that the communication channel is limited, the state signals need to be quantized by a logarithmic quantizer with mode-dependent property before communication. When the quantized state is passed to the controller, the stochastic packet loss phenomenon may occur, which follows Bernoulli stochastic distribution. Therefore, a new packet loss compensation strategy is put forward, which adopts the single exponential smoothing method to predict the lost data. Additionally, considering that the system modes are not always fully available, a periodic controller with partially mode-dependent property is devised to ensure that the system is stochastically stable with the predefined mixed H2/H∞ performance. Then, the sufficient conditions for the existence of periodic controller are established by constructing a periodic Lyapunov function, which is mode-dependent. Ultimately, a practical example of a boost converter is presented to verify the validity of the proposed approach.

Observer-based control for networked Takagi-Sugeno fuzzy systems with stochastic packet losses

This paper addressed the observer-based control problem for Takagi-Sugeno (T-S) fuzzy systems with stochastic packet losses. More specifically, an sampled-data (SD) control technique is introduced to reduce the burden of the limited bandwidth of the network, a general consecutive packet loss model is used to represent the stochastic packet loss behavior between sensor-to-controller and controller-to-actuator, and an observer scheme based on received SD output information is used to obtain the estimated system states. Based on the above scenarios, an exact discrete-time model approach is developed for stabilizing networked T-S fuzzy systems. First, the considered system with the observer-based control scheme is transformed into its discrete-time model such that subsequent analysis will be carried out in the discrete-time domain. On this basis, stability criteria are derived by fully considering the probability distribution of consecutive packet losses. Furthermore, an observer-based controller is designed by introducing some auxiliary matrices. Finally, the correctness and practicability of the designed controller is demonstrated by a mass-spring-damper system.

Consensus of discrete-time multi-agent systems with consecutive packet losses in directed communication topology

In this paper, consensus analysis and design are investigated for discrete-time multi-agent systems (MASs) with consecutive packet losses in communication links of directed communication topology. It is assumed that at each transmitted instant, the packet loss is stochastic and described by Bernoulli distribution, but during a given time window, the data could be successfully transmitted to the agent from each of its neighbors. First, we utilize the incidence matrix of a directed spanning tree of the communication topology to construct a linear transformation matrix so that the consensus problem is equivalently transformed into a mean square asymptotic stability problem of a reduced-order system. Second, by using Lyapunov–Krasovskii functional approach, we derive some sufficient conditions of consensus criterion in terms of linear matrix inequalities (LMIs). These conditions express the relationship among the control gain matrix, packet loss rate, and the number of consecutive packet losses. Based on the conditions, gain matrix in the consensus protocol is designed to guarantee the MAS with stochastic packet losses to achieve mean square asymptotic consensus. Moreover, for the special case of undirected communication topology, by using the matrix decomposition method, the variables of LMIs are transformed into the low-order conditions independent of the network size. Finally, some numerical examples are given to show the effectiveness of the proposed method.

Robust Performance Analysis for Time-Varying Multi-Agent Systems with Stochastic Packet Loss

Recently, a scalable approach to system analysis and controller synthesis for homogeneous multi-agent systems with Bernoulli distributed packet loss has been proposed. As a key result of that line of work, it was shown how to obtain upper bounds on the H2-norm that are robust with respect to uncertain interconnection topologies. The main contribution of the current paper is to show that the same upper bounds hold not only for uncertain but also time-varying topologies that are superimposed on the stochastic packet loss. Because the results are formulated in terms of linear matrix inequalities that are independent of the number of agents, multi-agent systems of any size can be analysed efficiently. The applicability of the approach is demonstrated on a numerical first-order consensus example, on which the obtained upper bounds are compared to estimates from Monte-Carlo simulations.

Parameter-space-based robust control of heterogeneous platoon with stochastic packet dropout

Parameter-space-based robust control of heterogeneous platoon with stochastic packet dropout

Parameter-space-based robust control of heterogeneous platoon with stochastic packet dropout

Parameter-space-based robust control of heterogeneous platoon with stochastic packet dropout

Practical Fixed-Time Consensus Tracking for Multiple Euler–Lagrange Systems With Stochastic Packet Losses and Input/Output Constraints

In this article we investigate the practical fixed-time consensus tracking problem for multiple Euler–Lagrange systems, which is subject to, concurrently, stochastic packet losses in directed communication networks (DCNs) and input/output constraints. In practice, the packet losses in the communication network may lead to communication failure and control accuracy degradation. To address this impact, a novel fully distributed observer is established to estimate the leader’s states within fixed time. Subsequently, the state constraint function is introduced so that the designed adaptive control protocol can be used in a uniform structure with unconstrained or asymmetric/symmetric output constraints without changing the adaptive structure. Combining the backstepping technique with fuzzy-logic systems, an adaptive fixed-time local control protocol is constructed to drive each agent to track the leader’s states estimated by the observer. Besides, a novel auxiliary system is introduced to solve the constraint problem of the control input. Furthermore, through rigorous theoretical analysis, it is verified that all signals converge to the compact set close to zero with guaranteed fixed-time convergence rate. At last, a representative simulation is carried out to demonstrate the practicability of the proposed method.

Перспективы использования машинного обучения для классификации сетевого трафика в технологиях доверенного взаимодействия

The current stage of development of the world community is characterized by an everincreasing role of the information sphere and is completely dependent on information resources and technologies, their quality and security. Computerization of all aspects of life has become the main reason that a significant part of the elements of social relations cannot be implemented without the use of new IT in various subject areas, and hence without the implementation of a reliable system of integrated security of the developed information automated systems. This article gives the concept of network traffic, considers the classification of network traffic, in which classification by port numbers, deep packet analysis, stochastic packet analysis, and the use of machine learning were identified. Methods for protecting information using trusted technologies were defined, where a general presentation of trust technologies was considered. The main conclusions are drawn on the prospects of using machine learning to classify network traffic in trusted technologies.

Robust Sliding Mode Control for Stochastic Uncertain Discrete Systems with Two-Channel Packet Dropouts and Time-Varying Delays.

In this paper, the control problem is investigated for discrete time-varying delayed systems with stochastic uncertainty, external disturbance, and two-channel packet dropouts. Sliding mode functions with packet loss probabilities are proposed for the packet loss problem in the sensor–controller channel and the controller–actuator channel. Furthermore, by employing the Lyapunov–Krasovskii functional, some new stability conditions are established in terms of solvable linear matrix inequalities (LMIs), and H∞ performance is analyzed for the sliding mode motion of the system. Meanwhile, a sliding mode controller is designed to drive the system state to the pre-designed sliding surface. Moreover, the designed controller can be robust for two-channel packet dropouts, time-varying delays, stochastic uncertainty and external disturbance. Finally, two numerical examples are given to demonstrate the feasibility of the proposed theoretical method.

Corrections to “Practical Fixed-Time Consensus Tracking for Multiple Euler–Lagrange Systems With Stochastic Packet Losses and Input/Output Constraints” [2021 DOI: 10.1109/JSYST.2021.3112720

In [1], several errors were introduced during the production process, which are corrected here.

Design of Prediction-Based Controller for Networked Control Systems with Packet Dropouts and Time-Delay

A novel prediction-based controller design is proposed for networked control systems (NCSs) with stochastic packet dropouts and time-delay in their control channel. The sequence of packet dropouts, which are modelled as a Bernoulli process, is compensated by a zero-order holder (ZOH)-based module, whereas a state predictor is utilized for obtaining the predicted states at the time delayed. In view of dropout compensator and state predictor, a novel modified model predictive controller (MPC) is designed and proposed in the following procedures. Compared to cost function of a general model predictive controller, variables of states are substituted by the predicted ones as obtained from state predictor preliminarily. Then, a logical programming approach is applied to include all the possible circumstances in the prediction horizon. Consequently, the cost function is reformed as simultaneous minimax linear matrix inequalities (LMI) with constraints. As a result, toolbox YALMIP is employed in order to solve such minimax programming problem eventually. Simulation results are presented to show the feasibility and performance of proposed method.

Dissipativity analysis for Takagi–Sugeno fuzzy system with time-varying delays and stochastic packet dropouts

The dissipative stability analysis of Takagi–Sugeno fuzzy system (TSFS) is the focus of this paper via taking the effects of both delays and packet dropouts. The novel augmented Lyapunov–Krasovskii functional (LKF) is proposed via utilizing the delay-dependent matrix, which provides the information of the delay derivative bounds. By applying the dynamic delay partition method, the delay interval is divided into several variable subintervals, which takes full advantage of time-varying delay information. In addition, the randomly occurring asynchronous or synchronous controllers are put forward to enhance the design flexibility and control performance. On the basis of the new augmented LKF and improved boundary techniques, the sufficient asymptotic stability condition is derived in the form of linear matrix inequalities (LMIs). Subsequently, numerical examples are addressed to certify the feasibility and advantage of the put forward methodology.

Communication Topology Assignment and Control Co-design for Vehicle Platoons in LTE-V2V Network

In this study, we investigate the problem of inter-vehicle communication topology (IVCT) assignment and control for vehicular platoons in LTE-V2V networks based on the cooperative awareness message dissemination mechanism. A sampled-data feedback controller is proposed for platoons to eliminate the effect of stochastic packet dropouts and external disturbance, where the controller gain depends on the IVCT. To guarantee the stability requirement of a platoon with the minimized cost function, a unified control framework is established to jointly determine the optimal IVCT from all the available ones and the associated feedback controller gain. This co-design procedure is based on the optimal control and dynamic programming technique, where both fixed and periodic switching IVCTs are available. A useful algorithm is proposed to implement the established co-design framework. Furthermore, we present numerical examples to demonstrate the effectiveness of the proposed method.

Feedback-Based Network Coding for Broadcast: Queueing Analysis

The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">randomized drop when seen</i> (rDWS) scheme is an online, feedback-based network coding technique proven to be an efficient, lightweight variant of the deterministic <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">drop when seen</i> (DWS) scheme. We have proposed a non-generation-based, generalized version of rDWS with stochastic packet arrival at the sender queue (SQ) in this letter. Next, a queueing analysis is performed to find the expected SQ length with respect to the load factor. Analysis shows that asymptotic SQ length in rDWS approaches the same of DWS as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">innovativeness factor</i> approaches unity, which establishes the effectiveness of rDWS in maintaining shorter expected SQ length.