Distributed Networked Control Systems Research Articles

MAD‐DDS: Memory‐efficient automatic discovery data distribution service for large‐scale distributed control network

AbstractThe rampant deployment of data distribution service (DDS) as middle‐ware service providers for industrial network platforms has been widely investigated. All DDS‐based node discovery protocols establish communication with its intended target systems by accessing matched endpoints/nodes information. These matched endpoints/nodes information is usually embedded with the system’s programmable control plane network which acts as the conveyor vehicle. The introduction of software defined networking (SDN) is to characterize the control plane from embedded data plane. The DDS implements the simple discovery protocol (SDP) as its inherent node discovery protocol. Deploying DDS for data packet exchange in server‐based collaborative distributed networked control (DNC) systems has gained traction. The current automatic discovery protocol (ADP) based on SDP is fraught with real‐time limitations such as high memory consumption and poor packet transmission. This work presents novel memory‐efficient automatic discovery data distribution service (MAD‐DDS) with enhanced threshold bloom filters (ETBF) where ETBF stores transmission packets at simulation end‐nodes. The packet is further adjusted using optimized binarization and decision thresholds inside ADP, hence guaranteeing memory reduction. The testbed computation recorded significantly improved quality of service (QoS) whereas numerical results depict significant decline in memory consumption with consistent packet transmission rates that produces increased computational capacity.

Reliability Assessment of Distributed Network Control System Based on Time Delay Evaluation

Reliability Assessment of Distributed Network Control System Based on Time Delay Evaluation

Event-triggered control of interconnected nonlinear systems subjected to cyber-attacks and time-varying coupling

This paper addresses the problem of efficient control of nonlinear distributed networked control systems in the presence of stochastic deception attacks and time-varying coupling strength. A strategy combining model-based and event-triggered control to reduce the number of transmissions over a network thereby, saving network resources is proposed. In this strategy, a plant model at the controller end is used to estimate the state of each subsystem. Further, the control law between the two adjacent triggering instants changes in accordance with dynamics of the plant model. The nonlinearities present in each subsystem are approximated via neural network. The neural network weights and feedback signal are updated only when the event-triggering condition at the sensor end is violated. Also, a lower bound on the inter-event time is computed to avoid the occurrence of Zeno phenomena. Finally, the efficacy of the proposed methodology are verified through simulation examples.

Guaranteed consensus performance in second-order networked multi-agent systems with induced delay

This work described the performance of consensus control of the second-order networked multi-agent system with CAN bus-induced delay. First, the characteristics of controller area networks (CAN) buses and the main causes of CAN bus induce a delay in distributed networked control systems (DNCS) were analysed. Secondly, DNCS is converted into a model of networked multi-agent systems in the frequency domain. Then based on the designed model of networked multi-agent systems, an analytical H2 controller is proposed for performance tracking. Moreover, a complementary sensitivity function is used to assess the robustness of the proposed controller. In the end, delay margin criteria are derived for the consensus of a networked multi-agent system in the presence of CAN bus-induced delay. The results obtained by simulating the second-order networked multi-agent system verified the usefulness of the proposed control protocol.

A CPN-Based Approach for Studying Impacts of Communication Delays on Safety and Availability of Safety-Critical Distributed Networked Control Systems

With the great advances in computer science and communication technology, more and more control systems are implemented as distributed networked control systems (DNCSs). Due to the nature of the time delay of communication networks, it is of importance to investigate how communication delays affect the systems from different perspectives. Most of the literature by far focus on analyzing the impacts of time delays on the system stability or safety control with mathematical models (i.e., differential equations), which are of interest in the early phases of the system development (e.g., the conceptual phase). However, in the later phases of the system development (e.g., architecture design or system implementation), qualitative as well as quantitative safety analysis based on system models that describe the concrete structures, interactions between components, and state transitions of the underlying systems is desirable. Additionally, the availability of a control system is of interest from the perspective of operation. This article studies the impacts of communication delays on the safety and availability of DNCSs by a colored-Petri-net-based approach. To exemplify the proposed approach, a simplified communication-based train control system is presented.

Distributed event‐triggered robust automatic generation control for networked power system with wind turbines

This paper proposes an event-triggered distributed networked control scheme and its robust stability analysis strategy for the automatic generation control of multi-area interconnected power system with wind turbines. First, for the large-scale distributed networked control systems, considering the networked control systems with parameters uncertainty, effective transmission bandwidth, and time-varying networked-induced delays, a new distributed networked control systems model is proposed. Then, by constructing Lyapunov–Krasovskii functional method, the sufficient conditions for asymptotical stability of the system are obtained, a design method of event-triggered distributed networked control law based on linear matrix inequality is proposed. In order to verify the effectiveness of the proposed scheme, a multi-area power system with wind turbines is considered, and the system performance under different load disturbances is simulated. The simulation results show that the scheme has reliable robust performance for multi-area distributed networked power system and improves the anti-interference ability of the power system.

Design and real-time implementation of a wireless autopilot using multivariable predictive generalized minimum variance control in the state-space

The contribution of this work is the numerical simulation and the experimental assessment of a network distributed control system using an unmanned aerial vehicle and a remote master controller connected by a wireless network. A novel multi-input multi-output long-range predictive horizon minimum variance control approach is developed and implemented in altitude, heading, lateral and longitudinal velocities control problems under the influence of process noise, measurement noise and time-delay. The proposed autopilots exhibited damped and fast response speeds with optimal control and output variance minimization, outperforming a classic model predictive control approach in convincing experimental field tests in real-world environments and scenarios.

A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks

Smart grids (SGs), which can be classified into a class of networked distributed control systems, are designed to deliver electricity from various plants through a communication network to serve individual consumers. Due to the complexity of environments, the distribution of the spatial locations and vulnerability of the communication networks, cyber security emerges to be a critical issue because millions of electronic devices are interconnected via communication networks throughout critical power facilities. This paper addresses a comprehensive security understanding of the SGs framework, attacks scenarios, detection/protection methods, estimation and control strategies from both communication and control viewpoints. Also, some potential challenges and solution approaches are discussed to deal with the threat issues of SGs. At last, some conclusions and highlight future research directions are presented.

Model Reference Adaptive Control for Networked Distributed Systems with Strong Interconnections and Communication Delays

In recent years, networked distributed control systems (NDCS) have received research attention. Two of the main challenges that such systems face are possible delays in the communication network and the effect of strong interconnections between agents. This paper considers an NDCS that has delays in the communication network, as well as strong interconnections between its agents. The control objective is to make each agent track efficiently a reference model by attenuating the effect of strong interconnections via feedback based on the delayed information. First, the authors assume that each agent knows its own dynamics, as well as the interconnection parameters, but receives information about the states of its neighbors with some communication delay. The authors propose a distributed control scheme and prove that if the interconnections can be weakened and if the communication delays are small enough, then the proposed scheme guarantees that the tracking error of each agent is bounded with a bound that depends on the size of the weakened interconnections and delays, and reduces to zero as these uncertainties reduce to zero. The authors then consider a more realistic situation where the interconnections between agents are unknown despite the cooperation and sharing of state information. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense with respect to the size of the weakened interconnections and delays, provided the weakened interconnections and time delays are small enough. The authors then consider the case that each agent knows neither its dynamics nor the interconnection matrices. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense provided the weakened interconnections and time delays are small enough. Finally, the authors present an illustrative example to present the applicability and effectiveness of the proposed schemes.

Traffic scheduling in distributed networked control systems with packet losses and delays for power systems voltage stabilization

In this paper, medium access control (MAC) sublayer data traffic scheduling in distributed networked control systems (DNCSs) with networked induced packet losses and delays is investigated for stabilization and control of system dynamics. An effective‐information‐directed distributed sensor selection algorithm is proposed to select sensors to participate in delay‐tolerant information filtering for state estimation. The distributed scheduling algorithm is based on the total amount of effective information for all measurements stored in the sensors. We consider packet loss in wireless networks as a special type of delay, so the impact of packet losses on effective information amount can also be studied for the formulation of distributed scheduling strategy in the presence of packet losses. The distributed data traffic scheduling considering packet losses and delays is carried out in a networked system with data packet dropout governed by a Markov process for voltage regulation and stabilization with distributed energy resources (DERs). Experimental results demonstrate that the scheduling algorithm with awareness of the system dynamic state can well control the power system dynamics. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Robust fault tolerant control of distributed networked control systems with variable structure

This paper studies the robust fault tolerant control problem of distributed network control systems (DNCSs). DNCSs are defined as the networked control systems (NCSs) consist of several sub-systems. Each sub-system contains its own sensor, controller and actuator. This kind of systems widely exist in the real world, such as the urban water supply network, smart grid and so on. Three main aspects of DNSCs are investigated in this paper. Firstly, we consider the variable structure problem of DNCSs. Meanwhile, the network problems including time delays, packet-dropouts and quantization errors are considered. Finally, the actuator fault tolerant control problem due to the possible poor working environment is also studied. A series of two-mode-dependent controllers are proposed to stabilize such DNCSs and meet the robust closed-loop performance. By using the Lyapunov–Krasovskii (L-K) function, sufficient conditions on the existence of such controllers are presented in terms of bilinear matrix inequalities (BMIs). A cone complementarity linearization (CCL) algorithm is given to solve proposed BMIs. Finally, a simulation example is exploited to show the effectiveness of the proposed method.

Stability analysis of large-scale distributed networked control systems with random communication delays: A switched system approach

In this paper, we consider the stability analysis of large-scale distributed networked control systems with random communication delays. The stability analysis is performed in the switched system framework, particularly as the Markov jump linear system. There have been considerable research on stability analysis of the Markov jump systems. However, these methods are not applicable to large-scale systems because large numbers of subsystems result in extremely large number of switching modes. To circumvent this scalability issue, we propose a new reduced mode model for stability analysis, which is computationally scalable. We also consider the case in which the transition probabilities for the Markov jump process contain uncertainties. We provide a new method that estimates bounds for uncertain Markov transition probability matrix to guarantee the system stability. Numerical example verifies the computational efficiency of the proposed methods.

A Reputation-Based Secure Distributed Control Methodology in D-NCS

Distributed networked control systems (D-NCSs) are more vulnerable to malicious attacks with the adoption of distributed control strategies. The misbehaving agents in the D-NCS can disrupt the distributed control algorithms and gradually compromise the entire system. In this paper, a multirobot system using the linear consensus algorithm for formation control is studied where parts of the robots are compromised. A reputation-based secure distributed control methodology with built-in defense is proposed to achieve accurate consensus computation in the presence of misbehaving robots. It embeds four phases (i.e., detection, mitigation, identification, and update) into the distributed control process. The effectiveness of the proposed method is illustrated through simulation analysis and experimental results.

An Asynchronous Differential Measurement Method for Time-Varying Network Induced Delay

This paper proposes a novel asynchronous differential measurement method to compute the time varying network induced delay which exists in each period of networked control systems. It is independent of the whole networked clock synchronization and can compute the real-time system delay during a single period. System structure is designed as a distributed network control system which consists of a network scheduling manager, many sensors nodes, and many controller/actuator nodes. Network model adopts Master/Slaver communication industrial Ethernet. Finally, a numerical experiment is given to demonstrate that, this method has strong potential to improve the performance of system with network induced delay and proves its validity and effectiveness.

Stability analysis of model-based networked distributed control systems

Networked distributed control systems (NDCSs) face serious challenges such as delays and packet dropouts induced by the communication network employed to connect local controllers of interacting subsystems. These two network-induced shortcomings may degrade the performance or even destabilize NDCSs. This paper is concerned with the problem of stability analysis and stabilization of the NDCSs, featuring both random delay and random packet loss in their communication networks. A model-based networked distributed control framework is proposed to stabilize the NDCS consisting of discrete-time subsystems interconnected through their states. In this control framework, to compensate for the adverse effects of these two network-induced shortcomings, an interaction estimator is provided in each local controller; in addition to a main control unit. This estimator uses the explicit model of the subsystems to estimate the evolution of the states of interacting subsystems, when information about their actual values is not available. A model for the NDCS subject to both random packet loss and random delay is developed. By providing a 3-step interaction estimating algorithm, the closed-loop model-based networked distributed control system (MB-NDCS) is formulated as a time-dependent impulsive system. Then, a quadratic Lyapunov function is constructed to derive a linear matrix inequality (LMI) based sufficient condition for stability analysis of the overall impulsive system. Finally, an illustrative example of a network of interconnected chemical reactors with recycle is presented to show the effectiveness of the proposed approach.

Modeling and Optimizing the Performance-Security Tradeoff on D-NCS Using the Coevolutionary Paradigm

Distributed networked control systems (D-NCS) are vulnerable to various network attacks when the network is not secured; thus, D-NCS must be well protected with security mechanisms (e.g., cryptography), which may adversely affect the dynamic performance of the D-NCS because of limited system resources. This paper addresses the tradeoff between D-NCS security and its real-time performance and uses the Intelligent Space (iSpace) for illustration. A tradeoff model for a system's dynamic performance and its security is presented. This model can be used to allocate system resources to provide sufficient protection and to satisfy the D-NCS's real-time dynamic performance requirements simultaneously. Then, the paper proposes a paradigm of the performance-security tradeoff optimization based on the coevolutionary genetic algorithm (CGA) for D-NCS. A Simulink-based test-bed is implemented to illustrate the effectiveness of this paradigm. The results of the simulation show that the CGA can efficiently find the optimal values in a performance-security tradeoff model for D-NCS.

Modelling and analysis of distributed networked control systems

This study reports the l2 stability problem for a class of distributed heterogeneous systems interconnected via communication channels. First, the model of distributed networked control system (DNCS) is given, taking into account both the heterogeneity of the subsystems and the non-idealisation of the communication network. The sufficient condition for the finite-gain l2 stability is then derived. A numerically solvable condition is further given based on the frequency domain result. Finally, a simulation example is provided to demonstrate the usefulness of the theoretical results obtained.

Sliding Mode Observer-Based Fault Detection of Distributed Networked Control Systems with Time Delay

This paper considers the fault detection problem of distributed networked control systems (DNCS) with time delay. A sliding mode observer-based fault detection method for a two-level DNCS is presented and two different situations are considered. When all the states of the system are available for measurement, we convert the fault detection problem to a sliding motion stable and reachable problem. When some states of system are not available for measurement, we design a transformation matrix to separate the measurable states and the unknown states, and then different sliding mode observers for those unknown states are developed to achieve fault detection. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method with simulation results.

An Implementation of Remote Monitor Master Station Based on CANopen Protocol

For the development trends and defects of the Water Electrolysis Hydrogen Generation Station (WEHGS), the design of CAN bus distributed network control system based on CANopen protocol is presented. CANopen master characteristics have been analyzed, then the communication implementation of CANopen monitor msater protocol stack, which includes the hardware interface and software design of CAN controller based on the LPC2292, is described. The tested results show that CANopen monitor master meets the requirements of WEHGS.

Multi-agent Platform and Toolbox for Fault Tolerant Networked Control Systems

Industrial distributed networked control systems use different communication networks to exchange different critical levels of information. Real-time control, fault diagnosis (FDI) and Fault Tolerant Networked Control (FTNC) systems demand one of the more stringent data exchange in the communication networks of these networked control systems (NCS). When dealing with large-scale complex NCS, designing FTNC systems is a very difficult task due to the large number of sensors and actuators spatially distributed and network connected. To solve this issue, a FTNC platform and toolbox are presented in this paper using simple and verifiable principles coming mainly from a decentralized design based on causal modelling partitioning of the NCS and distributed computing using multi-agent systems paradigm, allowing the use of agents with well established FTC methodologies or new ones developed taking into account the NCS specificities. The multi-agent platform and toolbox for FTNC systems have been built in Matlab/Simulink environment, which is in our days the scientific benchmark for this kind of research. Although the tests have been performed with a simple case, the results are promising and this approach is expected to succeed with more complex processes.