Shared Communication Network Research Articles

Signed-network-based consensus control for nonlinear multi-agent systems: a dynamic encryption–decryption approach

Abstract This paper is concerned with the bipartite secure control issue for a class of discrete-time nonlinear multi-agent systems under a dynamic encryption–decryption approach. First, the coupling relationships between agents are portrayed through a signed graph topology containing the edges of positive and negative connection weights. Next, the information transmissions between agents and their neighbors are executed via a shared communication network. The dynamic encryption–decryption approach is implemented to transform original signals into ciphertexts. Under the assumption that the signed graph is structurally balanced, a signed-network-based bipartite secure controller is designed to achieve the desired state control for the nonlinear multi-agent system and sufficient conditions are obtained for the existence of the desired signed-network-based state controller. Furthermore, a precise definition of the minimum channel capacity is proposed to understand the factors affecting the minimum channel capacity. Finally, the effectiveness of the proposed approach is illustrated by two simulation examples.

Real-time multi-camera 3D human pose estimation at the edge for industrial applications

There is an increasing interest in exploiting human pose estimation (HPE) software in human–machine interaction systems. Nevertheless, adopting such a computer vision application in real industrial scenarios is challenging. To overcome occlusion limitations, it requires multiple cameras, which in turn require multiple, distributed, and synchronized HPE software nodes running on resource-constrained edge devices. We address this challenge by presenting a real-time distributed 3D HPE platform, which consists of a set of 3D HPE software nodes on edge devices (i.e., one per camera) to redundantly extrapolate the human pose from different points of view. A centralized aggregator collects the pose information through a shared communication network and merges them, in real time, through a pipeline of filtering, clustering and association algorithms. It addresses network communication issues (e.g., delay and bandwidth variability) through a two-levels synchronization, and supports both single and multi-person pose estimation. We present the evaluation results with a real case of study (i.e., HPE for human–machine interaction in an intelligent manufacturing line), in which the platform accuracy and scalability are compared with state-of-the-art approaches and with a marker-based infra-red motion capture system.

Dissipative PID control for uncertain positive Roesser system under the try-once-discard protocol

This paper addresses the problem of dissipative proportional–integral–derivative (PID) control for the delayed positive Roesser system with interval uncertainties under the try-once-discard (TOD) protocol. To alleviate the undesired data congestion phenomenon in the shared communication network, the TOD protocol is introduced to regulate which sensor node could release its measurement at each transmission instant. An output-feedback-based PID controller is designed for the two-dimensional (2-D) system with TOD protocol. Based on the co-positive Lyapunov–Krasovskii function method, sufficient criteria in the linear programming form are attained to ensure the positivity, 2-D (ζ,η)-γ-dissipativity and robust asymptotic stability of the closed-loop system. Finally, an illustrative example is given to show effectiveness of the PID control scheme designed.

Dissipative filtering for uncertain positive Roesser system under the try-once-discard protocol

This article addresses the problem of dissipative filtering for the delayed positive Roesser system with uncertainties under the try-once-discard communication protocol. To estimate the output of the addressed two-dimensional system, both positive lower- and upper-bounding filters are constructed, where the signals from the sensor nodes to the remote filters are transmitted through a shared communication network. To avoid the undesired data congestion phenomenon, the try-once-discard protocol is implemented to dynamically schedule the transmission sequence of the sensor nodes. Then, sufficient conditions are derived to design appropriate filters ensuring that the filtering error systems are positive, two-dimensional [Formula: see text]- γ-dissipative, and asymptotically stable. Finally, one numerical example is presented to demonstrate effectiveness of the designed filters.

Security control of Markovian jump neural networks with stochastic sampling subject to false data injection attacks★ ★This work was supported by the NNSF of China under Grants 61973199, 62003794, 62173214, the Shandong Provincial NSF ZR2020QF050, ZR2021MF003.

The security control of Markovian jumping neural networks (MJNNs) is investigated under false data injection attacks that take place in the shared communication network. Stochastic sampled-data control is employed to research the exponential synchronization of MJNNs under false data injection attacks (FDIAs) since it can alleviate the impact of the FDIAs on the performance of the system by adjusting the sampling periods. A multi-delay error system model is established through the input-delay approach. To reduce the conservatism of the results, a sampling-period-probability-dependent looped Lyapunov functional is constructed. In light of some less conservative integral inequalities, a synchronization criterion is derived, and an algorithm is provided that can be solved for determining the controller gain. Finally, a numerical simulation is presented to confirm the efficiency of the proposed method.

Factors affecting continued purchase intention in live streaming shopping: parasocial relationships and shared communication networks

ABSTRACT Live streaming shopping (LSS) has become a means of increasing sales and has become a crucial research topic. Drawing on uncertainty reduction theory, parasocial relationship theory, and social influence theory, this study develops a research model to investigate the factors affecting LSS viewers’ continued watching and purchase intentions. The results indicate that the real-time multiparty interactivity of LSS offers information from two sources that can satisfy the long-term viewers’ needs for information. The first is the viewer’s perceived affinity with the streamer based on the information shared by the streamer. These perceptions lead to the development of a parasocial relationship, promoting identification with the streamer. The second is the shared communication network (SCN) comprising the audience watching the LSS content. This SCN generates social influence; coviewers’ endorsements and trustworthiness are internalised and influence the perceived credibility of the streamer and can promote identification with the streamer. Parasocial relationships, credibility, and identification with the streamer increase viewers’ intention to continue to watch LSS content and to purchase the products sold by the streamer. This study contributes to the LSS literature by investigating the influence of viewer–viewer interactions and highlighting the importance of the SCN in maintaining streamer–viewer relationships.

Dynamic output feedback model predictive control for asynchronous Markovian jump systems under try‐once‐discard protocol

AbstractThis paper is concerned with the dynamic output feedback robust model predictive control (RMPC) problem for a class of discrete‐time asynchronous Markovian jump systems (MJSs) subject to polytopic parameter uncertainties and hard constraints on states and inputs. A hidden Markov model is employed to describe the asynchronous phenomenon between the detected modes and the system modes. For the purpose of improving the network utilization as well as reducing the transmission burden and avoiding data collisions, the try‐once‐discard (TOD) protocol is deployed in the shared communication network between sensor nodes and the controller node. Considering the difficulty of obtaining the system state in the practice, the dynamic output‐feedback control in the framework of RMPC is adopted, and the worst‐case optimization problem over the infinite moving horizon is formulated for the performance analysis and control synthesis. By means of the Lyapunov‐like function approach, free weighting matrices and inequality techniques such as the ‐procedure are introduced to deal with the non‐convexity caused by couplings between decisive variables and the negative influence resulting from the data orchestration is mitigated. Based on the delicate establishments, a certain upper bound of the objective function is employed to construct an auxiliary optimization problem with solvability to find the desired controllers, and sufficient conditions are obtained to guarantee that the MJSs under the proposed RMPC‐based controllers are mean‐square stable. Finally, an illustrative example is used to demonstrate the validity of the proposed methods.

Multi‐loop networked control system design subject to interchange attack

AbstractThis paper deals with the design problem of multiloop networked control system (NCS) under interchange attack. This is a new type of attack where the transmitted data are swapped between different control loops which can be more destructive than other types of attacks, such as denial‐of‐service (DoS) attack. In this context, multiple sampled‐data control loops are first considered that use a shared communication network for data transmission. Then, the overall closed‐loop systems with the proposed attack are formulated in a unified stochastic delay system. The proposed framework is also applicable to DoS attack. Based on Lyapunov–Krasovskii theory and stochastic analysis techniques, some conditions in terms of linear matrix inequalities (LMIs) are derived for the control design problem. Finally, two inverted pendula are utilized for simulation to show the effectiveness of the proposed method. Also, the effects of DoS attack and interchange attack are compared.

Security Investment in Cyber-Physical Systems: Stochastic Games With Asymmetric Information and Resource-Constrained Players

This article considers remote state estimation in cyber-physical systems (CPSs) with multiple sensors. Each plant is modeled by a discrete-time stochastic linear system with measurements of each sensor transmitted to the corresponding remote estimator over a shared communication network when their securities are interdependent due to network-induced risks. A dynamic nonzero-sum game with asymmetric information is formulated in which each sensor subject to a resource budget constraint needs to decide whether to invest in security for sending data packets, taking the behaviors of other sensors into account. To overcome the difficulty in characterizing or computing the Nash equilibria (NE), the game with asymmetric information is transformed into another game with symmetric information such that the equilibrium of the original game can be obtained by solving the equilibrium of the new game. Under certain conditions, we devise a backward induction algorithm to obtain a subclass of NE of the original game, known as common information-based Markov perfect equilibria (CIBMPE). Finally, a numerical example is provided to illustrate the results obtained.

"It made me feel like I wasn't alone in the darkness": exploring dementia care network communication and coordination through a digital health platform.

To explore the use of a shared communication and coordination platform-the CareVirtue journal feature-for care networks of people living with Alzheimer's disease and related dementias to inform the design of care network support technologies. In the primary study, care networks comprised the primary caregiver and other caregivers they invited to participate (eg, family members, in-home aides) used CareVirtue, for 60days followed by a semistructured interview to explore primary caregivers' perceptions of usefulness. This secondary analysis focused on use of the shared journal feature of CareVirtue, which allowed care networks to communicate through posts that were shared with the network and to which network members could respond. Journal posts were analyzed using a deductive/inductive content analysis to categorize information behavior. We also conducted a thematic analysis of the interviews to identify primary caregivers' perceptions of the journal's usefulness. Care networks used the journal for: (1) information acquisition, (2) information sharing, (3) strategy development, and (4) information feedback. Thematic analysis revealed that caregivers felt the journal was useful at the individual, care network, and relational levels and that journal integration was influenced by care network structure and relationships. Care networks used the journal to document, share, and acquire information; co-create strategies; and provide support. The usefulness of this shared communication and coordination platform included individual and care network level benefits. These findings point to the importance of caregiver-centered technologies that support both the individual primary caregiver and the care network.

Encoding-decoding-based finite-horizon recursive secure state estimation for dynamic coupled networks with random coupling strength☆

The recursive secure state estimator design issue is investigated in this article for a class of dynamic coupled networks (DCNs) through the encoding-decoding scheme. The random variables distributed over specified intervals are utilized to depict the stochastically varying coupling strengths. For the sake of facilitating the data transmission, saving network resources and cutting down security risks, the two-description coding scheme (TDCS) is employed in the communication channels. Based on the TDCS, the encoders are installed at two independent communication channels, and the packet loss phenomena are considered in two encoder-to-decoder channels. The random denial of service (DoS) attack is taken into account when the decoded data are transmitted to the estimator through the shared communication networks. By recursively dealing with two coupled backward Riccati difference equations (CBRDEs), the desired finite-horizon H∞ state estimator gain matrix (EGM) can be determined. Finally, a numerical example is exhibited to illustrate the efficiency of the designed finite-horizon secure state estimator.

Protocol-based variance-constrained distributed secure filtering with measurement censoring

In this article, the variance-constrained distributed secure filtering issue based on communication protocol is investigated for time-varying stochastic systems with measurement censoring and cyber attacks over wireless sensor networks. In order to accurately characterise the measurement censoring property of real instruments, a two-sided censoring model is introduced for each sensor node, where the actual measurement value can be obtained only when the pre-set condition is satisfied. The DoS attack, occurring in a random way, is considered on the sensor-to-filter channel. The try-once-discard (TOD) protocol is employed to reduce the transmitted data and alleviate the burdens of shared communication networks, such that only one sensor node is granted to transmit the measurement data at each time instant. By the aid of the Lyapunov stability theory and recursive linear matrix inequality (RLMI) method, the sufficient condition is acquired to guarantee that the desired secure filter under cyber attacks ensures certain performance index and the filtering error variance constraint over a finite horizon. Finally, an illustrative example is provided to exhibit the effectiveness of the designed filtering algorithm.

An Accurate Method for Computing the Delay Margin in Load Frequency Control System with Gain and Phase Margins

In traditional power systems, a dedicated communication channel is utilized to transfer the frequency measurements. With the deregulation and reconstruction of power systems, the information is sent through a shared communication network that makes time delays unavoidable in load frequency control (LFC) systems. With the existence of time delays, the LFC system becomes a standard time delay system that complicates the stability analysis and controller synthesis. In this paper, we present a new approach for analyzing the stability and determining the delay margin of the LFC system. By introducing a new variable, the transcendental equation is converted to nonlinear equations. To find the crossing frequencies, the nonlinear equations are solved, which is simpler than solving a set of linear matrix inequalities. A single-area and a multi-area LFC system are selected as case studies. The new method accurately determines the delay margin of the LFC system with phase and gain margin. The effect of the PI controller gains on the delay margin is also considered. A sensitivity analysis is conducted to discover the effects of the system parameters on the delay margin, and it is found that the primary loop parameters have a powerful influence on the delay margin. The stability region of the LFC system is also clearly identified through the proposed method. The influence of the system parameters on the stability region is studied. Compared to the published methods in the literature, the proposed method has a simpler structure while giving more accurate results.

Uncertain AoI in stochastic optimal control of constrained LTI systems

Abstract This paper addresses finite-time horizon optimal control of control structures with shared communication network. To cope with the uncertainties, induced by network imperfections and exogenous disturbances at the same time, an optimization-based control scheme is proposed. It uses a disturbance feedback and the Age of Information (AoI), a receiver-based measure of communication delays, as central aspects. The disturbance feedback is an extension of the control law used for balanced stochastic optimal control. Balanced optimality is understood as a compromise between minimizing expected deviations from the reference and the minimization of the uncertainty of future states. Time-varying state constraints as well as time-invariant input constraints are considered, and the controllers are synthesized by semi-definite programming.

Robust set-membership filtering for two-dimensional systems with sensor saturation under the Round-Robin protocol

In this paper, the set-membership filtering problem is investigated for a class of polytopic uncertain two-dimensional shift-varying systems with delays and sensor saturation. The measurement information is transmitted between the sensors and the filter through a shared communication network. To avoid data congestions, the Round-Robin (R-R) protocol is employed to regulate the data transmission order. This paper aims to design a robust set-membership filter such that the real system states are always contained in the state estimate ellipsoid in the presence of the state delays, the sensor saturation, the parameter uncertainties, the R-R protocol and the unknown-but-bounded external perturbations. By using the mathematical induction, sufficient condition for the existence of the desired robust set-membership filter is given in the form of recursive linear matrix inequalities, and a convex optimisation method is also proposed to determine the optimal state estimation ellipsoid in the trace sense. One numerical example is also given to illustrate effectiveness of the proposed filtering strategy.

Event-triggered neuro sliding mode control for an uncertain Euler–Lagrange system: An impulsive dynamical system approach

This paper investigates the design of a neural network-based sliding mode control (SMC) with event-based sampling for an uncertain Euler–Lagrange (EL) system. The EL system considered here is connected to the controller over a shared communication network. The event-based SMC is designed to ensure the reduced usage of the communication and computational resources with robust tracking performance. The controller is designed under the assumption that the EL system dynamics are unknown; thus, a radial basis function neural network (RBFNN) is used to estimate it. The discrete weight update dynamics of RBFNN is formulated for a continuous-time EL system which makes the closed-loop system hybrid. Hence, the stability of the closed-loop system is investigated using the theory of impulsive dynamical systems with the admissible inter sampling time. Finally, a numerical example of an EL system is simulated to establish the effectiveness of the proposed control strategy.

A machine-learning approach for identification and mitigation of cyberattacks in networked process control systems

The robustness of process control systems to cyberattacks has become an increasingly important topic, especially in light of the increased dependence of process operations on networked control system architectures wherein dedicated sensor-controller and controller-actuator links are replaced by real-time, wired or wireless, shared communication networks. To mitigate the risks of cyberattacks, we propose in this work an integrated model-based framework for the detection, estimation and mitigation of false data injection cyberattacks in nonlinear networked process systems. The framework leverages a classification-based neural network scheme for attack detection and estimation, coupled with a stability-based attack mitigation strategy based on a model-based controller design. An illustrative chemical process example is used to demonstrate the effectiveness of the proposed framework and assess its robustness with respect to possible attack detection and estimation errors.

Security investment of interdependent and identical CPSs: Stochastic games with asymmetric information

This paper considers remote state estimation in cyber-physical systems (CPSs) with multiple sensors, where measurements of each sensor are transmitted to the corresponding remote estimator over a shared communication network with interdependent security. A stochastic non-cooperative game framework with asymmetric information is provided, in which each sensor is in pursuit of minimizing the security investment cost on the first stage associated with the expected error covariance as small as possible at the corresponding remote estimator on the second stage. The asymmetry of information among sensors poses a challenge to characterize or compute the Nash equilibria (NE). To overcome the challenge, based on the common information among sensors, the game with asymmetric information is transformed into another game with symmetric information such that a subclass of NE refer to common information based Markov perfect equilibria of the original game can be achieved by using a backward induction algorithm. Finally, a numerical example is presented to verify the obtained results.

Distributed Event Triggering Algorithm for Multi-Agent System over a Packet Dropping Network.

The availability of wireless networked control systems (WNCSs) has increased the interest in controlling multi-agent systems. Multiple feedback loops are closed over a shared communication network in such systems. An event triggering algorithm can significantly reduce network usage compared to the time triggering algorithm in WNCSs, however, the control performance is insecure in an industrial environment with a high probability of the packet dropping. This paper presents the design of a distributed event triggering algorithm in the state feedback controller for multi-agent systems, whose dynamics are subjected to the external interaction of other agents and under a random single packet drop scenario. Distributed event-based state estimation methods were applied in this work for designing a new event triggering algorithm for multi-agent systems while retaining satisfactory control performance, even in a high probability of packet drop condition. Simulation results for a multi-agent application show the main benefits and suitability of the proposed event triggering algorithm for multi-agent feedback control in WNCSs with packet drop imperfection.

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.