Distributed Control Architecture Research Articles

DOLPHIN: Dynamically Optimized and Load Balanced Path for Inter-Domain SDN Communication

Software-Defined Networking has become an integral technology for large scale networks that require dynamic flow management. It separates the control function from data plane devices and centralizes it in a domain controller. However, only a limited number of switches can be managed by a single and centralized controller which introduces challenges such as scalability, reliability, and availability. Distributed controller architecture resolves these issues but also introduces new challenges of uneven load and traffic management across domains. As real-world networks have redundant links, hence a significant challenge is to distribute traffic flows on multiple paths, within a domain, and across multiple independent domains. The selection of ingress and egress switches becomes even more problematic if the intermediate domain is non-cooperative. In this work, we propose a Dynamically Optimized and Load-balanced Path for Inter-domain (DOLPHIN) communication system, a customized solution for different SDN controllers. It provides control beyond the virtual switch elements in intra and inter-domain communication and extends the range of programmability to wireless devices, such as the Internet of Things or vehicular networks. Extensive simulation results show that the traffic load is distributed evenly on multiple links connecting different domains. We model data center communication and 5G vehicular network communication to show that, by load balancing the flow completion times of the different types of network traffic can be significantly improved.

Distributed Reactive Power Control Scheme for the Voltage Regulation of Unbalanced LV Grids

This article proposes a new control strategy for the voltage regulation of unbalanced low-voltage (LV) distribution grids with high penetration of distributed renewable energy sources (DRESs). The proposed method uses the available reactive power of DRESs as the primary means for voltage regulation. Furthermore, its distinct feature is the use of a distributed control architecture prioritizing the response of DRESs to maintain the network voltages within permissible limits and minimize the network losses. The prioritization process is locally implemented by each DRES combining two types of information: (a) the sensitivity matrix that quantifies the impact of reactive power variations on the network voltages and (b) voltage measurements along the network. Time-domain and time-series simulations on the IEEE European LV test feeder are performed to evaluate the performance of the proposed method against existing decentralized, distributed and centralized, optimization-based methods.

Hierarchical Two-Layer Distributed Control Architecture for Voltage Regulation in Multiple Microgrids in the Presence of Time-Varying Delays

The Multiple Microgrids (MMGs) concept has been identified as a promising solution for the management of large-scale power grids in order to maximize the use of widespread renewable energies sources. However, its deployment in realistic operation scenarios is still an open issue due to the presence of non-ideal and unreliable communication systems that allow each component within the power network to share information about its state. Indeed, due to technological constraints, multiple time-varying communication delays consistently appear during data acquisition and the transmission process and their effects must be considered in the control design phase. To this aim, this paper addresses the voltage regulation control problem for MMGs systems in the presence of time-varying communication delays. To solve this problem, we propose a novel hierarchical two-layer distributed control architecture that accounts for the presence of communication latencies in the information exchange. More specifically, the upper control layer aims at guaranteeing a proper and economical reactive power dispatch among MMGs, while the lower control layer aims at ensuring voltage regulation of all electrical buses within each MG to the desired voltage set-point. By leveraging a proper Driver Generator Nodes Selection Algorithm, we first provide the best choice of generator nodes which, considering the upper layer control goal, speeds up the voltage synchronization process of all the buses within each MG to the voltage set-point computed by the upper-control layer. Then, the lower control layer, on the basis of this desired voltage value, drives the reactive power capability of each smart device within each MG and compensates for possible voltage deviations. Simulation analysis is carried out on the realistic case study of an MMGs system consisting of two identical IEEE 14-bus test systems and the numerical results disclose the effectiveness of the proposed control strategy, as well as its robustness with respect to load fluctuations.

A Distributed Control Architecture for Cascaded H-Bridge Converter With Integrated Battery Energy Storage

Cascaded H-bridge topology has been used in grid-tied converters for battery energy storage system due to its modular structure. To fully utilize the converter's modularity, this article proposes a hierarchical distributed control architecture that consists of primary control, secondary control, and battery state-of-charge (SOC) balancing control. Primary control ensures accurate current tracking, whereas a distributed secondary control based on consensus algorithm is presented to regulate power sharing among modules and is proved to be stable theoretically. A distributed SOC balancing control is further introduced to improve energy efficiency of battery energy storage system. Finally, the hierarchical distributed control strategy is implemented using hardware controllers and a software platform. Besides, a carrier phase shift control is also implemented to achieve multilevel output voltage and harmonic reduction. The experimental results demonstrate the performance of the proposed control scheme effectively.

Distributed MPC of Residential Energy Storage for Voltage Regulation and Peak Shaving Along Radial Distribution Feeders

This article presents two low bandwidth distributed model predictive control (MPC) based algorithms for the coordinated control of residential energy storage (ES) to mitigate overvoltage and reduce peak demand along LV radial distribution feeders. Each ES unit consists of a low level controller (LLC) that utilises MPC with three distinct objective functions that can optimise for financial benefit, voltage regulation and peak shaving. These modes are activated via binary signals sent by the high level controller (HLC). The HLC, operating at the feeder level, determines if any network violations such as overvoltage or overloading are predicted to occur. Using inter-bus <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{P}$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{|V|}$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\Delta P}$</tex-math></inline-formula> data, the HLC determines the minimum ES units to dispatch to mitigate these issues. The result is a very low bandwidth distributed control architecture with low computational complexity, that can achieve acceptable network operating conditions while dispatching the minimum number of ES units. The proposed distributed MPC algorithms were shown to outperform decentralised control strategies for voltage regulation and peak shaving from the Australian Standards and also had significantly less computational requirements than a centralised MPC controller to achieve the same network overvoltage and peak load objectives.

Distributed MPC for Large Freeway Networks Using Alternating Optimization

The Model Predictive Control (MPC) framework has shown great potential for the control of Variable Speed Limits (VSLs) and Ramp Metering (RM) installations. However, the implementation to large freeway networks remains challenging. One major reason is that, by considering the VSLs to be discrete decision variables, an extremely difficult Mixed Integer Nonlinear Programming (MINLP) optimization problem has to be solved within every controller sampling interval. Consequently, many related papers relax the MINLP problems by considering the VSLs to be continuous variables. This paper proposes two novel MPC algorithms for coordinated control of discrete VSLs and continuous RM rates that do not make this relaxation. The proposed algorithms use a distributed control architecture and an alternating optimization scheme to relax the MINLP optimization problems but still consider the VSLs as discrete variables and, hence, offer a trade-off between computational complexity and system performance. The performance of the proposed algorithms is evaluated in a case study. The case study shows that relaxing the VSLs to be continuous variables with a distributed architecture results in a significant performance loss. Furthermore, both proposed algorithms have a lower computational complexity than the more conventional centralized approach and, as a result, they do manage to solve all optimization problems within the sampling intervals. Moreover, one of the proposed algorithms has a system performance that is remarkably similar to the optimal performance of the centralized approach.

Wheel Modules With Distributed Controllers: A Multi-Agent Approach to Vehicular Control

Modular vehicles have great potential to solve future mobility challenges in an efficient, reliable, and flexible way. Various designs have been proposed for compact, and multi-functional wheel modules. However, the architecture of vehicular active safety systems, by adopting such a modular approach, has not yet been well studied in the literature. Conventional stability control systems are developed in a centralized manner to seek the optimal distribution of control efforts, and the resultant controllers are highly dependent on the vehicle platform. Any changes to the actuators as well as modelling complexity will lead to a system redesign. This paper proposes a distributed control architecture as inspired by the modular chassis design for great re-usability. Each wheel module is treated as an agent in a cooperative game to determine their share in the overall control efforts, while encapsulating their configuration as well as modelling details within each module. Re-configurable agent models are also derived in a weak-coupled fashion to enhance modularity of the control system. The resultant distributed model predictive controller demonstrates greater flexibility in adaption to various configurations as well as enhanced robustness against computational units failure in the system. The proposed architecture also offers a new perspective for the controller design of conventional vehicles.

A Cyber-Secure Distributed Control Architecture for Autonomous AC Microgrid

Security of various cyber-physical systems is a major concern for researchers worldwide. Nowadays, microgrids also form such cyber-physical system to achieve a number of objectives such as enhanced frequency regulation, economic active power sharing, proper reactive power sharing, etc. Communication links are essential in such microgrids to ensure bilateral flow of data to be fed to the secondary controllers of the distributed generators integrated to the power network. This article, therefore, studies the impact of various kinds of cyberattacks viz., false data injection, denial-of-service, and replay attack on the performance of these communication enabled secondary controllers having potential vulnerabilities. Additionally, it presents a unique framework to ensure system stability when communication links are subjected to such attacks. The analysis has been carried out in a microgrid operating in islanded mode where the controller area network (CAN) bus communication network is utilized to form the cyber-physical system. Simulations are performed in MATLAB/Simulink platform and real-time evaluation of the proposed framework has been carried out in a test bed having OPAL-RT (OP5600) simulator and physical CAN devices to form the communication links.

Localisation-based distributed control of timed discrete-event systems with communication delay

We study localisation-based distributed control of timed multi-component discrete-event systems with communication delay in the Brandin–Wonham framework. First, we propose channel models for inter-component event communication with bounded and unbounded delays; the channel models are treated as plant components. In this formulation, there exist multiple distinct observable event sets; thus we employ timed relative coobservability to synthesise partial-observation decentralised supervisors. Then, we localise these supervisors into local controllers and preemptors, which provably tolerate the specified bounded and unbounded communication delays. Finally, the derived local controllers and preemptors are allocated to each plant component, thereby building a purely distributed control architecture of TDES with communication delay. The above results are illustrated by a timed workcell example.

Setpoint Attack Detection in Cyber-Physical Systems

In this article, we face the problem of detecting setpoint attacks in networked control systems. We consider a setup where the reference signal (also known as setpoint) is generated by a control center remotely located with respect to a standard feedback controller. In this scenario, an attacker with sufficient resources can exploit the communication channel to alter the setpoint signal and ultimately affect the tracking performance of the control system. With respect to this problem, we propose a novel distributed control architecture that, taking advantage of peculiar capabilities of the command governor control paradigm, enables the detection of reference attacks. We formally prove that for constrained linear systems such detector exists. Moreover, by limiting the attacker's disclosure resources with superimposed cryptographically secure pseudorandom signals, we show that the absence of advanced stealthy attacks is also ensured. Finally, a solid numerical simulation investigating setpoint attacks on the flight control system of a single-engine fighter is presented to provide tangible evidence of the features of the presented methodology.

Synchronization for an MMC Distributed Control System Considering Disturbances Introduced by Submodule Asynchrony

The modular multilevel converter (MMC) is a promising topology for HVdc applications, which typically adopts a distributed control architecture to manage considerable submodules (SMs) in the system. SM synchronization is necessary for an MMC distributed control system to cope with the local controller clock discrepancy and asynchrony due to the manufacturing tolerance. This article proposes a synchronization scheme for the MMC distributed control system taking the disturbances introduced by the SM asynchrony into account. The MMC models considering SM asynchrony reveal that the asynchrony introduces harmonics around the carrier frequency in MMC output and the circulating current. The interaction between the SM switching harmonics and arm current harmonics leads to divergence of the capacitor voltages. The MMC distributed control system cannot entirely restrain the voltage divergence and maintain the system stability owing to the control capability saturation of the balancing controller. According to the theoretical analysis, the synchronization interval is properly selected considering the harmonic contents in the MMC output, the capacitor voltage deviation, and the distributed control system stability. The theoretical models and the proposed synchronization scheme are validated experimentally on an MMC prototype.

An enhanced AHP–TOPSIS-based load balancing algorithm for switch migration in software-defined networks

Considering a software defined network, distributed controller architecture uses multiple controllers in which each controller manages a part of the network. The load imbalance problem in this architecture causes a large number of switch migrations resulting in a significant increase in switch migration cost and average network response time along with a decrease in throughput. Although recent studies have addressed these issues, access to optimal response time had been achieved with high cost of switch migration and sometimes with reduction of throughput using their methods. Therefore, the load balance in the present study is managed by a variable threshold based on the controllers’ workload. In other words, migration is done by selecting optimal switch and controller so that the switch will be selected with the lowest traffic generation rate which could return the source controller to its steady state. Using the suggested method, a destination controller is selected based on some important parameters such as CPU utilization, rate of incoming packets and the number of hops between switch and controller. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) algorithm is used to select the best controller based on the above-mentioned criteria and the AHP (analytic hierarchy process) algorithm is employed for determining the ratio of each criterion. The proposed method considerably outperforms other methods by achieving about 6 and 78% improvement in throughput and the number of switch migration in our implementation, respectively.

Modular Field Robots for Extraterrestrial Exploration

Modular design methodology enables rapid reconfigurability for functional changes, robustness to failures and space utilisation for transportation. In the case of planetary exploration robots, there is promise in modular robots that are able to reconfigure themselves for exploration of unknown terrains. This paper presents a design and controller architecture for modular field robots that can be rapidly assembled in a variety of functional configurations. A key challenge of building a functional robot out of modular units is the ability to seamlessly add, remove and replace individual units to enable functional improvements as well as adapt to terrain requirements. We present a representative modular wheel design and a distributed controller architecture able to create a range of bespoke multi-wheeled configurations capable of traversal on a variety of terrains during simulated failure scenarios. The self-contained wheeled unit has energy, computation communication, and actuation modules and does not require any modification or physical customization in the field during deployment enabling a seamless plug and play behaviour. The hierarchical control structure runs a body controller node that decomposes a whole body motion requested from a higher level planner to generate a sequence of actuation goals for each of the modules, while a local controller node running on each of the modules ensures that the desired actuation is adapted to the configuration, load and terrain characteristics.

Formation Control With Multiplex Information Networks

Current distributed control methods have a lack of information exchange infrastructure to enable spatially evolving multiagent formations. Specifically, these methods are designed based on information exchange rules represented by a network having a single layer, where they lead to multiagent formations with fixed, nonevolving spatial properties. For situations where capable agents have to control the resulting formation through these methods, they can often do so if such agents have global information exchange ability. Yet, global information exchange is not practical for cases that have large numbers of agents and low-bandwidth peer-to-peer communications. Motivated from this standpoint, the contribution of this paper is to show how information exchange rules, which are represented by a network having multiple layers (multiplex information networks), can be designed for enabling spatially evolving multiagent formations. In particular, we first consider the formation assignment problem and then the formation tracking problem and introduce new distributed control architectures that allow capable agents to spatially alter the size and the orientation of the resulting formation without requiring global information exchange ability. In addition, tools and methods from differential potential fields are further utilized in order to generalize the proposed distribute control architecture for the formation tracking problem to allow for connectivity maintenance and collision avoidance needed in real-world applications. Stability of the proposed architectures is theoretically analyzed and their efficacy is illustrated on numerical examples and on multiagent formation experiments.

A Review on Software-Defined Networking Distributed Controllers

A computer network is a critical issue in our day to day activity; however, today it works under various problems. Since in the current network architecture the control plane and data plane are vertically bundled on the same device. To solve this problem programmable Software-Defined Network is released. OpenFlow is a protocol that vertically separates control plane and data plane of the network devices. In SDN the controllers are the brains of the network that controls the network devices. Today’s network required successful integration of distributed controllers to make the network more consistent. SDN distributed controller is a controller that we can add or remove the controllers according to the number of devices change. Distributed controller architecture has investigated and compared the 6 recent distributed controllers by using 26 criteria. Orion is the first best controller and ONOS is the second best controller.

On detectability of cyber-attacks for large-scale interconnected systems

The paper deals with the key problem of detecting cyber-attacks in the context of large-scale systems (LSS). As these systems grow in size and complexity, cyber-attacks may target limited parts of the LSS, leading to tackling the problem in a decentralized way. We analyze the properties of distributed detection schemes under both local and interconnection attacks, and show that they are vulnerable to attacks that exploit the structure of the interconnections between subsystems. We also provide conditions and strategies that may be adopted to make the distributed control architecture regulating the LSS robust to this class of cyber-attacks.

On the Use of LoRaWAN for the Monitoring and Control of Distributed Energy Resources in a Smart Campus

The application of the most recent advances of the Internet-of-Things (IoT) technology to the automation of buildings is emerging as a promising solution to achieve greater efficiencies in energy consumption, and to allow the realization of sustainable models. The application of IoT has been demonstrated as effective in many fields, such as confirmed, for instance, by the Industry 4.0 concepts, which are revolutionizing modern production chains. By following this approach, the use of distributed control architectures and of IoT technologies (both wired and wireless) would result in effective solutions for the management of smart environments composed of groups of buildings, such as campuses. In this case, heterogeneous IoT solutions are typically adopted to satisfy the requirements of the very diverse possible scenarios (e.g., indoor versus outdoor coverage, mobile versus fixed nodes, just to mention a few), making their large-scale integration cumbersome. To cope with this issue, this paper presents an IoT architecture able to transparently manage different communication protocols in smart environments, and investigates its possible application for the monitoring and control of distributed energy resources in a smart campus. In particular, a use–case focused on the integration of the Long Range Wide Area Network (LoRaWAN) technology is considered to cope with heterogeneous indoor and outdoor communication scenarios. The feasibility analysis of the proposed solution is carried out by computing the scalability limits of the approach, based on the proposed smart campus data model. The results of the study showed that the proposed solution would be able to manage more than 10,000 nodes. An experimental validation of the LoRaWAN technology confirms its suitability in terms of coverage and latency, with a minimum LoRaWAN cell coverage range of 250 m, and a communication latency of about 400 ms. Finally, the advantages of the proposed solution in the supervision and management of a PV system are highlighted in a real-world scenario.

Multi-robot Target Encirclement Control with Collision Avoidance via Deep Reinforcement Learning

The target encirclement control of multi-robot systems via deep reinforcement learning has been investigated in this paper. Inspired by the encirclement behavior of dolphins to entrap the fishes, the encirclement control is mainly to enforce the robots to achieve a capturing formation pattern around a target, and can be widely applied in many areas such as coverage, patrolling, escorting, etc. Different from traditional methods, we propose a deep reinforcement learning framework for multi-robot target encirclement formation control, combining the advantages of the deep neural network and deterministic policy gradient algorithm, which is free from the complicated work of building the control model and designing the control law. Our method provides a distributed control architecture for each robot in continuous action space, relying only on local teammate information. Besides, the behavioral output at each time step is determined by its own independent network. In addition, both the robots and the moving target can be trained simultaneously. In that way, both cooperation and competition can be contained, and the results validate the effectiveness of the proposed algorithm.

A distributed model predictive control strategy for finite-time synchronization problems in multi-agent double-integrator systems

In this paper, a synchronization problem for a group of agents described by double-integrator dynamics and time-varying communication network is formally addressed. Specifically, the main aim consists in ensuring that the agents, organized as a swarm, are capable to synchronize in finite-time the swarm centroid to a given reference trajectory and to keep this property for all future time instants. To this end, an ad-hoc distributed control architecture is developed by taking advantage from two key ingredients: a novel swarm formation modelling that guarantees finite-time convergence properties of the agent kinematics and a hybrid model predictive control scheme in charge to adequately exploit such a kinematics description. One of the relevant features of the resulting distributed algorithm relies on the fact that both parallel and sequential paradigms are used with the aim to ensure collision avoidance requirements amongst the involved agents.

Solar sail cooperative formation flying around [formula omitted]-type artificial equilibrium points

The aim of this paper is to propose a distributed control architecture for a solar sail-based formation, flying around an L2-type artificial equilibrium point in the Sun-[Earth + Moon] circular restricted three-body problem. Two typical cases, depending on whether the formation structure is leaderless or includes a virtual leader, are investigated. In particular, the virtual leader case is further analyzed according to whether the state information of the virtual leader is available to all of the sails or to a part of the formation structure only. The protocols of the consensus-based algorithms are formulated on a general directed (unidirectional) communication topology, by exploring each available local neighbor-to-neighbor information interaction in a cooperative manner. In that case, a synchronized formation tracking may be achieved while increasing the reliability of the formation system. Illustrative examples show the effectiveness of the proposed approach in a typical mission scenario.