Distributed Control Methodology Research Articles

Bounded Voltage Regulation in a Direct Current Microgrid Using Barrier Lyapunov Function With Uncertain Load Current

A distributed control methodology for steady-state voltage regulation, along with a bounded transient response in a Direct Current (DC) microgrid, is proposed in this letter. The idea of asymmetric barrier Lyapunov function (ABLF) is used in realizing the prescribed constraints on the voltage magnitudes while considering the uncertain nature of the load current. By proposing a suitable load current estimator, we show that the voltage regulation is achieved within prescribed limits, and the closed-loop system remains stable under the proposed controller. We also obtain explicit bounds on the voltage and current errors, virtual controller, and estimated load current in the post-design analysis. Simulations illustrate the theoretical findings and the robustness of the proposed scheme to load perturbations.

Any-Time Feasible Coordination for Multivehicle Systems

This article proposes a distributed control methodology for the coordination of multiple connected and automated vehicles (CAVs). Each vehicle computes its local trajectory based on a model predictive control (MPC) law and communicates the result with other relevant vehicles. In an iterative negotiation process, planned trajectories are optimized within a sampling time step. Inspired by the Jacobi over-relaxation (JOR) algorithm, we develop a distributed Jacobi over-relaxation algorithm (DJOR) for vehicle coordination. The modified algorithm exploits the structure of the distributed problem setting in which coupling occurs only in a bilateral way. Besides being able to guarantee any-time feasibility that implies collision-freeness, the algorithm scales well, unlike the standard JOR algorithm. The DJOR algorithm allows for significantly less conservatism in the choice of the update weightings. As a result, much faster convergence rates can be expected. Furthermore, the collision avoidance guarantee is extended for unforeseen scenarios such as emergency braking. Using an exact penalty function formulation ensures that the distributed optimization problem remains feasible even in previously unforeseen cases. Numerical simulations of an intersection crossing scenario illustrate the presented approach and show its benefits in comparison with standard traffic rules and a centralized computation.

Mitigation of Voltage Unbalance in Distribution Feeders Using Phase Switching Devices: A Decentralized Control Approach Based on Local Measurements

High penetration level of single-phase solar PVs in low voltage distribution systems has raised concern about the Voltage Unbalance (VU) level. Real-time phase reconfiguration using Dynamic Switching Devices (DSD) has been proposed as a cost-effective solution to mitigate the excessive level of Voltage Unbalance. DSDs are fast power electronics devices that could change the phase connection of a solar PV with minimum disturbances. Most of the proposed methodologies for controlling DSDs are based on a central controller and the assumption of availability of Advanced Metering Infrastructure (AMI) and a communication system. In this paper, we propose a distributed control methodology to control DSDs based on the measurement from the local node only and using the sensitivity of nodal voltage to power injection. Each DSD decides on phase swapping if it rectifies the unbalance index of the local node. We show that decreasing the Voltage Unbalance Factor (VUF) of individual nodes will improve the unbalance situation of the whole feeder. The proposed scheme does not require a communication system nor a central controller. The result of simulations confirms the efficacy of the proposed methodology.

Relation of spatial grasp paradigm to philosophical and psychological concepts

The paper follows practical works on the creation of the first citywide computer networks in Kyiv (Ukraine) which have been integrating different institutes of the National Academy of Sciences and other organizations from the end of the sixties, well before the internet. These works resulted in a new management concept and distributed control methodology and technology, originally called WAVE, which were further developed and demonstrated in different countries in the areas like network management, industry, social systems, collective robotics, military command and control, crisis management, national and international security, defense, distributed simulation, space-based systems, and many others. The current paper analyses the relation of the developed Spatial Grasp Model, resultant Spatial Grasp Language (SGL), and Spatial Grasp Technology (SGT) to some higher-level psychological and philosophical concepts. By providing the basics of SGL and SGT and details of their implementation, it discusses the possible relation of these concepts to some gestalt theory laws like the Law of Proximity, Law of Good Gestalt, and Law of Figure and Ground. The paper also shows how to organize a sort of distributed and global awareness under SGT on an example of a dynamic swarm of chasing units, which can provide the increased operational capability of the swarm and be practically used for the organization of collective behaviour of multiple robot units exploring unknown and harsh environments. The paper mentions how SGT may relate to higher mental concepts like perception, consciousness, and even soul. It also shows relations of SG concept and its implementation to the pattern theory, with pattern considered as a fundamental and universal concept in many areas of human activity, which actually stands in opposition to the terms of logic.

Edge-Assisted Democratized Learning Toward Federated Analytics

A recent take toward federated analytics (FA), which allows analytical insights of distributed data sets, reuses the federated learning (FL) infrastructure to evaluate the summary of model performances across the training devices. However, the current realization of FL adopts single server-multiple client architecture with limited scope for FA, which often results in learning models with poor generalization, i.e., an ability to handle new/unseen data, for real-world applications. Moreover, a hierarchical FL structure with distributed computing platforms demonstrates incoherent model performances at different aggregation levels. Therefore, we need to design a robust learning mechanism than the FL that 1) unleashes a viable infrastructure for FA and 2) trains learning models with better generalization capability. In this work, we adopt the novel democratized learning (Dem-AI) principles and designs to meet these objectives. First, we show the hierarchical learning structure of the proposed edge-assisted Dem-AI mechanism, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Edge-DemLearn</i> , as a practical framework to empower generalization capability in support of FA. Second, we validate Edge-DemLearn as a flexible model training mechanism to build a distributed control and aggregation methodology in regions by leveraging the distributed computing infrastructure. The distributed edge computing servers construct regional models, minimize the communication loads, and ensure distributed data analytic application’s scalability. To that end, we adhere to a near-optimal two-sided many-to-one matching approach to handle the combinatorial constraints in Edge-DemLearn and solve it for fast knowledge acquisition with optimization of resource allocation and associations between multiple servers and devices. Extensive simulation results on real data sets demonstrate the effectiveness of the proposed methods.

Distributed Torque Control of Deloaded Wind DFIGs for Wind Farm Power Output Regulation

In this work, we propose a distributed control methodology that solves the problem of dispatching and regulating the power outputs of a group of deloaded wind double-fed induction generators (DFIGs) to attain fast, dynamic, and efficient wind farm power output regulation, with fair load-sharing among the DFIGs. In this context, fair load-sharing means that the ratio defined by the mechanical power over the maximum power from the wind, i.e., the utilization level, of all DFIGs, is the same in the steady state. Dynamic distributed dispatch and control of the power outputs of DFIGs refers to their ability to self-dispatch and regulate their power outputs under dynamical conditions and through peer-to-peer information exchange. Initially, we propose a leader-follower consensus protocol that DFIGs can adopt into their control system to attain: 1) asymptotic consensus on their utilization levels (i.e., fair load-sharing), and 2) total power output regulation. Then, we perform compositional stability analysis and prove that the protocol asymptotically converges under sufficient conditions. Finally, we design a distributed control-Lyapunov-function-based torque controller for the rotor-side converter that realizes the protocol in practice. The performance of the distributed control methodology is evaluated through numerical simulations on the modified IEEE 24-bus RT system.

Nonlinear Control of a DC MicroGrid for the Integration of Photovoltaic Panels

New connection constraints for the power network (grid codes) require more flexible and reliable systems, with robust solutions to cope with uncertainties and intermittence from renewable energy sources (renewables), such as photovoltaic (PV) arrays. The interconnection of such renewables with storage systems through a direct current (DC) MicroGrid can fulfill these requirements. A “Plug and Play” approach based on the “System of Systems” philosophy using distributed control methodologies is developed in this paper. This approach allows to interconnect a number of elements to a DC MicroGrid as power sources, such as PV arrays, storage systems in different time scales, such as batteries and supercapacitors, and loads, such as electric vehicles and the main ac grid. The proposed scheme can easily be scalable to a much larger number of elements.

A Multi-Functional Fully Distributed Control Framework for AC Microgrids

This paper proposes a fully distributed control methodology for secondary control of ac microgrids. The control framework includes three modules: 1) voltage regulator; 2) reactive power regulator; and 3) active power/frequency regulator. The voltage regulator module maintains the average voltage of the microgrid distribution line at the rated value. The reactive power regulator compares the local normalized reactive power of an inverter with its neighbors’ powers on a communication graph and, accordingly, fine-tunes Q-V droop coefficients to mitigate any reactive power mismatch. Collectively, these two modules account for the effect of the distribution line impedance on the reactive power flow. The third module regulates all inverter frequencies at the nominal value while sharing the active power demand among them. Unlike most conventional methods, this controller does not utilize any explicit frequency measurement. The proposed controller is fully distributed; i.e., each controller requires information exchange with only its neighbors linked directly on the communication graph. Steady-state performance analysis assures the global voltage regulation, frequency synchronization, and proportional active/reactive power sharing. An ac microgrid is prototyped to experimentally validate the proposed control methodology against the load change, plug-and-play operation, and communication constraints such as delay, packet loss, and limited bandwidth.

Guaranteed performance design for distributed bounded containment control of networked uncertain underactuated surface vessels

This paper presents a predefined performance design approach for distributed containment control of networked heterogeneous underactuated surface vessels (USVs) under a directed graph topology. It is assumed that the position information of multiple dynamic leaders is informed to only a subset of the followers consisting of USVs and all nonlinearities and external forces in each USV follower are unknown. The local control law for each USV follower is recursively designed using the predefined performance design technique where auxiliary variables are presented to deal with underactuated constraints in the predefined performance design framework and the approach angles capable of the tracking of both straight and curved line are employed. Compared with the existing literature on the control of multiple ocean vehicles with uncertainties, the proposed distributed control methodology is simply designed without using any function approximators and adaptive techniques to estimate uncertainties or their bounds. It is shown that the distributed containment errors are preserved within the predefined bounds of transient and steady-state performance in the Lyapunov sense.

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.

A Partitioning Method for Distributed Capacitor Control of Electric Power Distribution Systems

In order to implement distributed control of an electric power distribution system, typically a feeder is first partitioned into control areas. In this work, an analytical partitioning method based on capacitor reactive power domains is presented. Once partitioned, a distributed control algorithm is employed to support distribution operation applications with a focus on voltage spread reduction. The partitioning method is also applied to the commonly studied capacitor control objective of loss minimization. Simulation results applying the method to a real-world distribution feeder are presented and compared with an alternate geographically-based partitioning method. Results show the analytical partitioning and distributed control methodology is capable of producing high quality solutions to the capacitor control problem.

On the Coordination of Constrained Fixed-Wing Unmanned Aerial Vehicles

A formal distributed control methodology to coordinate a team of fixed-wing UAVs (Unmanned Aerial Vehicles) in a three-dimensional workspace is addressed. The complete task to be accomplished is divided in three stages: (i) each UAV tracks a circle parallel to the \(xy\) plane in a given altitude (different altitudes for different UAVs); (ii) the UAVs distribute themselves in such a way that their projection onto the \(xy\) plane are evenly spaced around a circle; (iii) each UAV converges to the same altitude to track the same circle. The main contribution of this work lies in the mathematical proofs of the proposed strategy for a given UAV model. We consider minimum and maximum limits in the forward speed command, maximum limit in the absolute value of the yaw rate, maximum limit in the absolute value of the altitude speed, second-order dynamics, and a non-holonomic constraint. Stability and collision avoidance are guaranteed during the whole task including the stage transitions and without violating the constraints. Simulation results are given to illustrate the proposed approach.

An Integrated Scheme for Cyber-physical Building Energy Management System

Building energy management systems (BEMS) are gaining momentum as an alternative means to implement energy efficiency applications in large public buildings. A integration of Cyber-physical system and building energy management manifests an effective avenue for the pursuit of high energy efficiency. This paper presents a building energy management system with wireless sensor networks using multi-agent distributed control methodology that concentrates on optimized target of air-conditioning, lighting and official electrical devices. A tiered integrated approach provides multiple levels of sensing, processing, communication and management functionality. The paper also introduces a detail study of physical and cyber aspects of the system. The performance of the system and its application in a large campus building are shown finally.

Emerging Control Technologies: What Does the Future Hold?

There is increasing emphasis today on higher autonomy and intelligence in control systems that is driven by ever more demanding control requirements and fueled primarily by recent significant advances in sensor, actuator, computer and computer network technologies. Distributed control methodologies and coordination of interacting intelligent systems over networks will bring sophisticated control and decision methodologies where the needs are. We are at the dawn of a new era in control and decision systems which has the potential to significantly benefit agriculture. Highly demanding control requirements in production and processing of agricultural products coupled with the complexity and uncertainty of the models require the use of sophisticated control methods. Areas that stand to benefit from the use of advanced methods include the control and management of greenhouses, water resources, energy etc as well as all areas of processing and distributing agriCUltural products.

An experiment in distributed manufacturing control

Local area networks are used in industrial control applications that require the digital interconnection of low-level devices such as transducers, actuators and simple controllers. It is possible to use such interconnections solely as a wiring alternative to the traditional star-connected computer controllers and to leave the control of the application with one ‘central’ computer. However, using a local area network to connect intelligent low-level devices opens up the possibility of applying a distributed control methodology to the application. This paper describes the application of a distributed control approach to a work cell previously based around a single, large programmable logic controller. Comparisons of the two approaches are made in an attempt to quantify the effect of this new approach on the metrics of the work cell.