Stochastic Communication Protocol Research Articles

Statistical-Based Optimal $\epsilon$-Stealthy Attack Under Stochastic Communication Protocol: An Application to Networked Permanent Magnet Synchronous Machine Systems

This article presents the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -stealthy attack against cyber-physical systems under the stochastic communication protocol (SCP), which is used to avoid data collisions. The aim is to develop an optimal attack strategy to degrade the estimation performance maximally, while remaining a certain level of stealthiness characterized by the Kullback–Leibler divergence. Taking the SCP-introduced effects into account, a novel attack model is proposed, where only a part of the transmitted data is utilized to construct the attack signal at each time instant. Subsequently, the optimization problem is formulated. Different from the existing results, where only the numerical solution is given, the analytical expression of the optimal attack parameters is presented, where the analytical solution has more advantage in analyzing how the parameters affect the attack performance. Finally, the numerical simulations on a three-tank system and the experiments performed on a networked permanent magnet synchronous machine prototype system are provided to validate our results.

Sliding mode control for multi‐agent systems under stochastic communication protocol

AbstractThis article investigates the consensus problem for the multi‐agent system (MAS) via a sliding mode control method. The stochastic communication protocol (SCP) obeying Markovian chain is adopted to schedule the information transmission among agents, by which only one state component of each agent is stochastically selected and transmitted to other agents at each transmission instant. Through the use of the merging technique, a joint Markovian chain is introduced to model the multi‐agent consensus error system. And then, a distributed sliding mode controller is designed to achieve the stochastic consensus of the MAS. Meanwhile, the desired controller gain matrix is obtained via solving a minimization problem. Finally, a numerical example has been provided to illustrate the proposed results.

Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems With the Denial-of-Service Attacks and Stochastic Communication Protocol

In this paper, a new filtering fusion problem is studied for nonlinear cyber-physical systems under error-variance constraints and denial-of-service attacks. To prevent data collision and reduce communication cost, the stochastic communication protocol is adopted in the sensor-to-filter channels to regulate the transmission order of sensors. Each sensor is allowed to enter the network according to the transmission priority decided by a set of independent and identically-distributed random variables. From the defenders&#x0027; view, the occurrence of the denial-of-service attack is governed by the randomly Bernoulli-distributed sequence. At the local filtering stage, a set of variance-constrained local filters are designed where the upper bounds (on the filtering error covariances) are first acquired and later minimized by appropriately designing filter parameters. At the fusion stage, all local estimates and error covariances are combined to develop a variance-constrained fusion estimator under the federated fusion rule. Furthermore, the performance of the fusion estimator is examined by studying the boundedness of the fused error covariance. A simulation example is finally presented to demonstrate the effectiveness of the proposed fusion estimator.

Communication-protocol-based distributed filtering for general systems over sensor networks: developments and challenges

During the past decades, the communication-protocol-based distributed filtering (DF) problems have received a great deal of research interest owing to their importance in networked systems. In this paper, we mainly present a timely review of DF problems under the influence of communication protocols (CPs). Firstly, we summarize the characteristics and advantages of the DF algorithm based on wireless sensor networks. According to the different types of noises or performance indices, the DF strategy can be generally categorized as the distributed recursive Kalman-type filtering, the distributed filtering, the distributed set-membership filtering and so on. Subsequently, the recent advances of various CPs including the event-based mechanism, the round-robin protocol, the weighted try-once-discard protocol, the stochastic CP and the redundant channel are discussed. After that, the DF schemes for complex dynamical systems under different CPs are reviewed in detail. In addition, several challenges faced in this survey are summarized and discussed. Finally, the conclusions are provided and several potential future research directions are mentioned.

Sliding Mode Control for Uncertain 2D Systems Under Stochastic Communication Protocol: The Roesser Model Case

This brief investigates the sliding mode control (SMC) problem of two-dimensional (2D) systems depicted by the Roesser model subject to limited communication channels. The stochastic communication protocol is employed to schedule the transmission from controller to actuators, under which only one controller node at each instant will be randomly selected to transmit its signal. To maintain the structural characteristics of 2D system, a sliding surface related to the horizontal and vertical states is constructed. By introducing the zero-input strategy to generate the information of unchosen nodes, a token-dependent SMC is designed, and both the reachability of the sliding surface and the asymptotic stability of the closed-loop system are analyzed. Moreover, the feasible SMC is obtained via solving a minimization problem. Finally, the proposed control scheme is applied in the metal rolling process.

Distributed cubature Kalman filtering for nonlinear systems with stochastic communication protocol

AbstractThis paper is concerned with the distributed cubature Kalman filtering (DCKF) for a class of discrete time‐varying nonlinear systems subject to stochastic communication protocol (SCP). In order to avoid the data collisions, the SCP is introduced to randomly schedule each sensor node information from one of the neighboring nodes to the filter which is presented via not only the information of itself sensor but also the information of neighboring sensors. The considered scheduling probability of the selected node is unknown. Therefore, the exact filtering error covariance is not available. The purpose of this paper is to design a DCKF under the spherical–radial cubature rule such that an upper bound of the filtering error covariance is guaranteed by utilizing fundamental inequality. Such an upper bound is dependent on known upper and lower bounds of the scheduling probabilities. Subsequently, the desired filter matrices are given by minimizing the upper bound of the filtering error. A sufficient condition is derived by using Riccati‐like difference equations method. Besides, a recursive form of filter algorithm is designed for online computation. Finally, the usefulness of the DCKF is verified by utilizing a simulation example on the induction machines.

Robust Fault Detection for Uncertain Delayed Systems With Measurement Outliers Under Stochastic Communication Protocol

In this paper, the robust fault detection (RFD) problem is studied for uncertain networked systems with time delay and measurement outliers under limited communication condition, where the time delay is presumed to occur randomly and the occurrence probability is considered to be uncertain. Specifically, in order to reduce the communication burden, the stochastic communication protocol (SCP) is introduced to adjust the transmission of measurement signals. Moreover, a fault detection filter (FDF) with saturation constraints is constructed to achieve the purpose of properly eliminating possible measurement outliers. Subsequently, a generalized sector condition is utilized to derive the stability criteria of the system on the basis of appropriate Lyapunov functional. In addition, a traditional FDF is also designed to compare with the saturation-constrained FDF. It is shown that the FDF with saturation constraints can properly avoid the influence of outliers on the detection effect. Finally, two simulations are presented to show the superiority and the practicality of the developed saturation-constrained fault detection (FD) filtering algorithm.

Finite-Horizon H-Infinity Control for Time-Varying State-Saturated Systems under Stochastic Communication Protocol

In this paper, the H∞ control problem is investigated for a class of time-varying state-saturated systems with both stochastic parameters and nonlinearities under the stochastic communication protocol (SCP). The sensor-to-controller network is considered where only one sensor can obtain access to the communication network at each transmission instant. The SCP is adopted to mitigate the undesirable data collision phenomenon. The model transformation technique is employed to simplify the addressed problem, and then, the completing squares method is carried out to obtain a sufficient condition for the existence of the finite-horizon H∞ controller. The controller parameters are characterized by solving two coupled backward recursive Riccati-like difference equations. A simulation example is finally utilized to illustrate the effectiveness of the proposed controller design scheme.

Nonlinear Filtering Under Stochastic Communication Protocol with Unknown Scheduling Probability

Nonlinear Filtering Under Stochastic Communication Protocol with Unknown Scheduling Probability

Outlier-resistant observer-based [formula omitted] PID control under stochastic communication protocol

This paper addresses the H∞ proportional-integral-derivative control problem based on the outlier-resistant observer for discrete-time systems under the schedule of stochastic communication protocol (SCP). A novel observer with saturation constraint is structured in order to reduce the negative influence of abnormal measurement outputs, where the saturation limit is dynamically adjusted in the light of the observation errors. For the sake of avoiding the phenomenon of data congestion, the SCP is deployed to orchestrate the order of data transmission in the sensor-to-observer channel. In view of the Lyapunov stability theory and the orthogonal decomposition method, sufficient conditions are obtained to make sure that the exponential mean-square stability is met and the H∞ performance index is satisfied. Eventually, a simulation example is provided to confirm the effectiveness and correctness of the presented controller design algorithm.

Non-fragile H∞ Fault Detection for Nonlinear Systems with Stochastic Communication Protocol and Channel Fadings

Non-fragile H∞ Fault Detection for Nonlinear Systems with Stochastic Communication Protocol and Channel Fadings

On ℓ2–ℓ∞ output-feedback control scheduled by stochastic communication protocol for two-dimensional switched systems

This paper is concerned with the – output-feedback control problem for a class of two-dimensional (2-D) switched systems described by the general Fornasini–Marchesini second model under the stochastic communication protocol (SCP). In a networked 2-D switched control system, the sensors and the controller are typically connected through a shared communication network of limited bandwidth, which is likely to result in data collision problem. To circumvent this network-induced problem, a new SCP is dedicatedly put forward for the 2-D switched system in order to orchestrate the transmission order of sensor nodes, under which only one sensor node obtains the privilege to access the network at each transmission instant. Then, based on the nominal system information compensation, a set of new mode-dependent output-feedback controllers is designed for 2-D switched systems subject to SCP and external disturbances. Moreover, using the average dwell-time approach, sufficient conditions are established to ensure the existence of the desired controllers that guarantee both the exponential mean-square stability and the – performance. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed controller design method.

Input-to-State Stabilization of Stochastic Markovian Jump Systems Under Communication Constraints: Genetic Algorithm-Based Performance Optimization.

This work investigates the stabilization problem of uncertain stochastic Markovian jump systems (MJSs) under communication constraints. To reduce the bandwidth usage, a discrete-time Markovian chain is employed to implement the stochastic communication protocol (SCP) scheduling of the sensor nodes, by which only one sensor node is chosen to access the network at each transmission instant. Moreover, due to the effect of amplitude attenuation, time delay, and random interference/noise, the transmission may be inevitably subject to the Rice fading phenomenon. All of these constraints make the controller only receive the fading signal from one activated sensor node at each instant. A merge approach is first used to deal with two Markovian chains; meanwhile, a compensator is designed to provide available information for the controller. By a compensator and mode-based sliding-mode controller, the resulting closed-loop system is ensured to be input-to-state stable in probability (ISSiP), and the quasisliding mode is attained. Moreover, an iteration optimizing algorithm is provided to reduce the convergence domain around the sliding surface via searching a desirable sliding gain, which constitutes an effective GA-based sliding-mode control strategy. Finally, the proposed control scheme is verified via the simulation results.

Neural-Network-Based Control for Discrete-Time Nonlinear Systems with Input Saturation Under Stochastic Communication Protocol

In this paper, an adaptive dynamic programming (ADP) strategy is investigated for discrete-time nonlinear systems with unknown nonlinear dynamics subject to input saturation. To save the communication resources between the controller and the actuators, stochastic communication protocols (SCPs) are adopted to schedule the control signal, and therefore the closed-loop system is essentially a protocol-induced switching system. A neural network (NN)-based identifier with a robust term is exploited for approximating the unknown nonlinear system, and a set of switch-based updating rules with an additional tunable parameter of NN weights are developed with the help of the gradient descent. By virtue of a novel Lyapunov function, a sufficient condition is proposed to achieve the stability of both system identification errors and the update dynamics of NN weights. Then, a value iterative ADP algorithm in an offline way is proposed to solve the optimal control of protocol-induced switching systems with saturation constraints, and the convergence is profoundly discussed in light of mathematical induction. Furthermore, an actor-critic NN scheme is developed to approximate the control law and the proposed performance index function in the framework of ADP, and the stability of the closed-loop system is analyzed in view of the Lyapunov theory. Finally, the numerical simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Fuzzy-Model-Based Control for Markov Switching Singularly Perturbed Systems with the Stochastic Communication Protocol

This work is concerned with the H ∞ control for Markov switching singularly perturbed systems with the stochastic communication protocol. To coordinate the data transmission and save the bandwidth usage, the stochastic communication protocol with a compensator is applied to schedule the information exchange. The goal of this work is to design a joint-Markov-process-based controller such that the resulting system is stochastically stable with prescribed performance. Based on the Lyapunov functional technique, a sufficient condition is derived to ensure the existence of the achieved controller. Finally, the effectiveness and correctness of the developed results are verified by the simulation example.

On finite-horizon [formula omitted] state estimation for discrete-time delayed memristive neural networks under stochastic communication protocol

This paper is concerned with the protocol-based finite-horizon H∞ estimation problem for discrete-time memristive neural networks (MNNs) subject to time-delays and energy-bounded disturbances. With the purpose of effectively alleviating data collisions and saving energy, the stochastic communication protocol (SCP) is adopted to regulate the data transmission procedure in the sensor-to-estimator communication channel, thereby avoiding unnecessary network congestion. It is our objective to construct an H∞ estimator ensuring a prescribed disturbance attenuation level over a finite time-horizon for the delayed MNNs under the SCP. By virtue of the Lyapunov–Krasovskii functional in combination with stochastic analysis methods, the delay-dependent criteria are established that guarantee the existence of the desired H∞ estimator. Subsequently, the estimator gains are computed by resorting to solve a bank of convex optimization problems. Finally, the validity of the designed H∞ estimator is demonstrated via a numerical example.

Robust H ∞ filtering for 2D systems with RON under the stochastic communication protocol

This study is concerned with the robust filtering problem for two-dimensional (2D) systems in Roesser model with randomly occurring non-linearity (RON) and stochastic communication protocol (SCP). The introduced non-linearity is sector-like and governed by a random variable obeying the Bernoulli distribution law. The SCP is depicted by an independent and identically distributed sequence to schedule the signal transmission. The phenomenon of time delay is also taken into consideration. The aim of this study is to design a filter such that the augmented filtering error system satisfies a predefined performance index. Sufficient condition is first given to ensure the robust stability of the augmented filtering error system via Lyapunov theory and stochastic analysis. Then, the result is extended to guarantee the performance of the augmented system under SCP, where sufficient criterion related to the transmission probability is given in terms of matrix inequality. Moreover, the filter gains are explicitly designed which enable the system to achieve the filtering performance. Finally, a numerical example is given to show the effectiveness of the proposed design method.

Finite-TimeH∞State Estimation for Two-Time-Scale Complex Networks Under Stochastic Communication Protocol

The issue of finite-time H∞ state estimation is studied for a class of discrete-time nonlinear two-time-scale complex networks (TTSCNs) whose measurement outputs are transmitted to a remote estimator via a bandwidth-limited communication network under the stochastic communication protocol (SCP). To reflect different time scales of state evolutions, a new discrete-time TTSCN model is devised by introducing a singular perturbation parameter (SPP). For the sake of avoiding/alleviating the undesirable data collisions, the SCP is adopted to schedule the data transmissions, where the transition probabilities involved are assumed to be partially unknown. By constructing a new Lyapunov function dependent on the information of the SCP and SPP, a sufficient condition is derived which ensures that the resulting error dynamics is stochastically finite-time bounded and satisfies a prescribed H∞ performance index. By resorting to the solutions of several matrix inequalities, the gain matrices of the state estimator are given and the admissible upper bound of the SPP can be evaluated simultaneously. The performance of the designed state estimator is demonstrated by two examples.

Nonfragile H∞ fault detection for fuzzy discrete systems under stochastic communication protocol

SummaryIn this article, considering one type of fuzzy discrete‐time networked control systems (NCSs) under stochastic communication protocol (SCP), a fuzzy‐based nonfragile H∞ filter is developed to detect the subsistent fault signal. The Takagi‐Sugeno (T‐S) mathematical model is employed to approximate the nonlinearities in the concerned fuzzy NCSs. The SCP is adopted to decide which sensor gets the access to the communication network at certain time instant, and the scheduling model of which is constructed as a Markov chain. Taking into account that the filter gain parameters in real practice may suffer fluctuations during the implementation, a modified nonfragile fuzzy filter is designed to detect the fault occurred in the signal transmission. By using the strong centralized stochastic analysis technique and the matrix calculation method, a Lyapunov function is adopted to derive sufficient conditions under which the filtering error dynamics is stochastically stable and the H∞ performance is satisfied. Then, the desired nonfragile fuzzy fault detection filter is realized by solving a certain linear matrix inequality. Finally, the effectiveness of the develop fault detection scheme is verified in the simulation example.

Dynamic output feedback sliding mode control for Markovian jump systems under stochastic communication protocol and its application

SummaryThis article investigates the dynamic output feedback control problem for a class of networked Markovian jump systems via sliding mode control method. The stochastic communication protocol schedules the communication between sensors and the controller, by which only one sensor node can access the network at one instant. First, a compensator at the controller side is utilized to yield the available measurement signals composed of the current measurement output transmitted by the selected sensor node and the past measurement output from other sensor nodes. A joint Markovian chain incorporating the Markovian chains of the system as well as the stochastic communication protocol is introduced to model the Markovian jump system subject to the stochastic communication protocol. And then, the dynamic output feedback sliding mode controller is designed and the stochastic stability is analyzed. Moreover, a feasible solving algorithm is provided via a projection technique. Finally, the proposed control scheme is verified via an electrical motor model.