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This study was carried out to determine inhibitory effect of crude extracts and essential oils of aromatic plants against Sclerotinia sclerotiorum in potato fields in Bahar and Lalehjin, Iran during cropping seasons of 2015 and 2016. The results showed that crude extracts of cinnamon and ginger at concentrations 5 g/l as well as essential oils of coriander, lavender thyme, savory and eucalyptus at concentration 50 μl EO/ml had potential to significantly reduce incidence of potato white mold. This is the first study about inhibitory effect of crude extracts and essential oils of aromatic plants against potato white mold under field condition. [ABSTRACT FROM AUTHOR]

A distributed control method is proposed to simultaneously optimize the power sharing among sources of islanded dc microgrids, while regulating the distribution bus voltage. During the optimization process, an economic dispatch problem is solved to minimize the total generation cost by setting the output powers of the dispatchable sources. To this end, the voltage set points of individual dc–dc converters are adjusted using a voltage regulator and an optimizer, which regulates the average voltage of the sources to establish the generation–consumption equality constraint and matches the incremental costs, respectively. Afterward, the proposed optimizer is modified to exclude the sources from the incremental cost consensus protocol upon reaching their generation limits, enforcing inequality constraints. This coregulation and cooptimization paradigm is developed in a fully distributed fashion. The dynamical model of the proposed controller is established. The steady-state analysis verifies the fulfillment of the control objectives, i.e., voltage regulation and cost minimization. Experimental results verify the controller performance and validate its resiliency against cyber and physical faults. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed finite-time restoration of inverter voltage and frequency terms in an islanded ac microgrid. Formulating networked inverters of ac microgrids as a cooperative multiagent system, the voltage and frequency restoration can be cast as synchronization problems, while the active power sharing can be viewed as a consensus problem. One popular distributed control approach is the neighbor-based linear consensus protocol, where the consensus at the frequency and voltage set points is achieved over an infinite-time horizon with an exponential convergence. To achieve accelerated convergence and better disturbance rejection properties, a distributed finite-time control protocol, based on feedback linearization approach, is proposed for voltage restoration, which synchronizes the voltage term at each inverter to the reference value in finite time period. Then, a finite-time control protocol for both frequency restoration and active power sharing problems is proposed to synchronize the microgrid frequency to the nominal value, and share the active power among inverters based on their ratings in a finite time. Rigorous Lyapunov proofs are provided to establish the upper bounds on the convergence times. Numerical simulation studies verify the effectiveness of the proposed control protocols. [ABSTRACT FROM PUBLISHER]

A distributed control method is proposed to handle power sharing among a cluster of dc microgrids. The hierarchical control structure of microgrids includes primary, secondary, and tertiary levels. While the load sharing among the sources within a dc microgrid is managed through primary and secondary controllers, a tertiary control level is required to provide the higher level load sharing among microgrids within a cluster. Power transfer between microgrids enables maximum utilization of renewable sources and suppresses stress and aging of the components, which improves its reliability and availability, reduces the maintenance costs, and expands the overall lifespan of the network. The proposed control mechanism uses a cooperative approach to adjust voltage set points for individual microgrids and, accordingly, navigate the power flow among them. Loading mismatch among neighbor microgrids is used in an updating policy to adjust voltage set point and mitigate such mismatches. While the voltage adjustment policy handles the load sharing among the microgrids within each cluster, at a lower level, each microgrid carries a communication network that is in contact with the secondary control system. It is this lower level network that propagates voltage set points across all sources within a microgrid. Load sharing and set point propagation are analytically studied for the higher and lower level controllers, respectively. Experimental studies on two cluster setups demonstrate excellent controller performance and validate its resiliency against converter failures and communication losses. [ABSTRACT FROM PUBLISHER]

An introduction is presented in which the editor discusses various reports within the special section " Advanced Distributed Control of Energy Conversion Devices and Systems" of the issue on topics including energy storage systems, photovoltaics and renewable energy sources.

This paper proposes an adaptive and distributed secondary voltage control for microgrids with inverter-based distributed generators (DG). The proposed control is fully adaptive and does not require the information of DG parameters. Neural networks are used to compensate for the uncertainties caused by the unknown dynamics of DGs. The controller structure is fully distributed such that each DG only requires its own information and the information of its neighbors on the communication network. Therefore, this secondary control is associated with a sparse communication network. The effectiveness of the proposed methodology is verified for different loading, outage, and islanding scenarios, as well as variable communication structures in a microgrid setup. [ABSTRACT FROM AUTHOR]

A distributed-adaptive droop mechanism is proposed for secondary/primary control of dc microgrids. The conventional secondary control that adjusts the voltage set point for the local droop mechanism is replaced by a voltage regulator. A current regulator is also added to fine-tune the droop coefficient for different loading conditions. The voltage regulator uses an observer that processes neighbors’ data to estimate the average voltage across the microgrid. This estimation is further used to generate a voltage correction term to adjust the local voltage set point. The current regulator compares the local per-unit current of each converter with the neighbors’ on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load sharing. The proposed controller precisely accounts for the transmission/distribution line impedances. The controller on each converter exchanges data with only its neighbor converters on a sparse communication graph spanned across the microgrid. Global dynamic model of the microgrid is derived with the proposed controller engaged. A low-voltage dc microgrid prototype is used to verify the controller performance, link-failure resiliency, and the plug-and-play capability. [ABSTRACT FROM AUTHOR]

Modular dc-dc converters are popular in dc-power systems due to their advantageous characteristics such as fault tolerance, ease of thermal management, reducing voltage/current stress of the components, and modularity. In this paper, the concept of cooperative control in multiagent systems is introduced for modular dc-dc converters. Each constituent converter is represented by a node in a directed communication graph that models the information flow among converters. The proposed cooperative control scheme enjoys structural modularity, plug-and-play capability, fault tolerance against random failures in the converters and/or communication links, and satisfactory dynamic performance. This paper provides a general analytical framework to study modular dc-dc converters with an arbitrary communication graph. Hence, the designer has the freedom to choose among the various types of graphs based on the available communication resources and the desired level of reliability and fault tolerance. The dynamic model of the cooperative multiconverter system is developed and analyzed. Hardware measurements are presented to verify the plug-and-play capability, fault tolerance in both cyber and physical domains, and dynamic performance of the proposed cooperative control scheme. [ABSTRACT FROM AUTHOR]

Transport and deposition of nanoparticles (NPs) have drawn great attention in different fields of engineering in recent years because of their potential risk to the environment. In this study, mobility of aluminum oxide NP, one of the most popular metal oxide NPs, was studied in synthetic saturated porous media. The impacts of ionic strength using monovalent (NaCl) and divalent (MgCl2) salt solution, pH, and NPs concentrations on nano-alumina mobility were investigated. The experimental results showed that the transport of nano-alumina was influenced by ionic strength; the highest mobility was observed at the 0.01 M solution and decreased by increasing ionic strength. Moreover, the suspension containing alumina NPs presented the best mobility behavior in the acidic solution (pH = 2) in comparison with neutral and basic solutions. Consequently, transport of NPs with particle size distribution lower than 100 nm through porous media was facilitated at the acidic, low ionic strength condition. In addition, faster elution occurred when the influent concentration was increased from 0.1 wt% to 0.3 wt%. Finally, it is expected that ionic strength, pH of solution, and NPs concentration will be key parameters to control the nano-alumina mobility. [ABSTRACT FROM AUTHOR]

A distributed algorithm is presented to solve the economic power dispatch with transmission line losses and generator constraints. The proposed approach is based on two consensus algorithms running in parallel. The first algorithm is a first-order consensus protocol modified by a correction term which uses a local estimation of the system power mismatch to ensure the generation-demand equality. The second algorithm performs the estimation of the power mismatch in the system using a consensus strategy called consensus on the most up-to-date information. The proposed approach can handle networks of different size and topology using the information about the number of nodes which is also evaluated in a distributed fashion. Simulations performed on standard test cases demonstrate the effectiveness of the proposed approach for both small and large systems. [ABSTRACT FROM PUBLISHER]

The article introduces various reports published within the issue, including one about fuel cells, one about energy management and another on hybrid electric vehicles.

In this paper, we propose a topology-cognizant optimal power flow (OPF) paradigm with additional safety constraints for multi-terminal direct current (MTDC) grids. The resulting formulation is concerned with the optimization of controller set-points, i.e., voltage and power levels at each bus, and the switching status of transmission lines that collectively referred to as grid topology. A pair of additional safety constraints are integrated into the problem formulation to prevent voltage violations caused by power fluctuations in between two controller set-point updates. Searching for a grid topology that offers more efficient operation leads to a mixed-integer nonlinear program (MINLP) which is computationally challenging due to: i) Non-convex power flow equations, (ii) Non-convex converter loss equations, and iii) Binary variables accounting for the operational status of transmission lines. Non-convexities of power flows and converter loss equations are tackled by means of a mixed-integer second-order cone programming (MISOCP) relaxation, while the optimal switching status of transmission lines are determined via a branch-and-bound search. Numerical results for the modified IEEE 14, 30, and 57-bus systems are used to verify the merits of the proposed method. Furthermore, this method is experimentally validated using the CIGRE B4 DC grid benchmark in a real-time hardware-in-the-loop platform. [ABSTRACT FROM AUTHOR]

This paper copes with the state estimation and topology identification problems in direct current (DC) networks. This problem is challenging due to binary decisions and nonlinear relations between sensor measurements and state variables. We introduce a non-convex nuclear norm estimator whose non-convexity is addressed by incorporating two inertia terms. In the presence of noise, penalty terms are integrated into the objective function to estimate unknown noise values. Numerical results for the modified IEEE 9-bus, 14-bus, and 30-bus systems corroborate the merits of the proposed technique. Furthermore, this technique is experimentally validated for a converter-augmented 14-bus system in a real-time hardware-in-the-loop platform. [ABSTRACT FROM AUTHOR]

Power buffers can help improve the inertia in DC microgrids and supply the additional power demand during short load transients. This article investigates distributed event‐triggered control of power buffers over an unreliable network, subject to packet losses and transmission delays. For each power buffer, a distributed event‐triggered control law regulates the input impedance while altering its stored energy. Moreover, a dynamic event‐triggered communication mechanism determines the time sequence of control updates and data transmissions among power buffers. An appealing feature of this mechanism is a designable positive minimum inter‐event time despite packet losses and transmission delays. The closed‐loop system is shown to be exponentially stable. Controller/hardware‐in‐the‐loop studies validate the theoretical findings. [ABSTRACT FROM AUTHOR]

This article investigates distributed event-triggered control (ETC) of power buffers in a direct current (DC) microgrid. In order to facilitate the control design, a linear interconnected system model is derived that captures the physical coupling among power buffers. Then, a distributed ETC law regulates the stored energy and input impedance of each power buffer, and a decentralized dynamic event-triggering mechanism determines when each power buffer communicates with its neighboring buffers. This strategy eliminates the need for both continuous controller updates and continuous communication among the power buffers. The resulting closed-loop system is shown to be exponentially stable under a mild assumption on the communication network. The proposed event-triggering mechanism guarantees not only the exclusion of the Zeno behavior but also the existence of a positive minimum interevent time that can be adjusted by the control design parameters. Simulation studies validate the effectiveness of the proposed theoretical results for a multibuffer DC microgrid. [ABSTRACT FROM AUTHOR]

Emerging distributed control paradigms rely on communication among converters of a microgrid. We investigate the secondary control of dc microgrids with a distributed dynamic event-triggering mechanism. The physical and cyber layers are represented by different graph topologies. To reduce the communication burden, a distributed dynamic event-triggering mechanism is designed. Therein, the Zeno behavior is excluded and in addition, a positive minimum interevent time (MIET) is determined. Asymptotic stability of the closed-loop system dynamics is proven, and the adjustment of the positive MIET is discussed. Compared to the existing static event-triggering mechanisms, the proposed dynamic one guarantees the existence of a positive MIET, whose value can be tuned by the design parameters. Controller/hardware-in-the-loop implementation results validate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

This article details and solves a small-signal stability-constrained optimal power flow (SSSC-OPF) for inverter-based ac microgrids. To ensure a sufficient stability margin during optimal generation, a small-signal stability constraint is embedded into the conventional OPF formulation. This condition is enforced using a Lyapunov stability equation. A reduced-order model of the microgrid is adopted to alleviate the computational burden involved in solving the resulting SSSC-OPF. Even then, the resulting stability conditions are highly nonlinear and cannot be handled using the existing methods. To tackle the nonconvexity in the SSSC-OPF due to the presence of the nonlinear stability constraint, two distinct convex relaxation approaches, namely semidefinite programming and parabolic relaxations, are developed. A heuristic penalty function is added to the objective function of the relaxed SSSC-OPF, which is solved sequentially to obtain a feasible point. While off-the-shelf tools fail to produce any feasible point within hours, the proposed approach enables us to solve the SSSC-OPF in near real time. The efficacy of the proposed SSSC-OPF is evaluated by performing numerical studies on multiple benchmarks as well as real-time studies on a microgrid system built in a controller/hardware-in-the-loop setup. [ABSTRACT FROM AUTHOR]

A cooperative control paradigm is used to establish a distributed secondary/primary control framework for dc microgrids. The conventional secondary control, that adjusts the voltage set point for the local droop mechanism, is replaced by a voltage regulator and a current regulator. A noise-resilient voltage observer is introduced that uses neighbors' data to estimate the average voltage across the microgrid. The voltage regulator processes this estimation and generates a voltage correction term to adjust the local voltage set point. This adjustment maintains the microgrid voltage level as desired by the tertiary control. The current regulator compares the local per-unit current of each converter with the neighbors' and, accordingly, provides a second voltage correction term to synchronize per-unit currents and, thus, provide proportional load sharing. The proposed controller precisely handles the transmission line impedances. The controller on each converter communicates with only its neighbor converters on a communication graph. The graph is a sparse network of communication links spanned across the microgrid to facilitate data exchange. The global dynamic model of the microgrid is derived, and design guidelines are provided to tune the system's dynamic response. A low-voltage dc microgrid prototype is set up, where the controller performance, noise resiliency, link-failure resiliency, and the plug-and-play capability features are successfully verified. [ABSTRACT FROM AUTHOR]

In this paper, input–output feedback linearization is used to design distributed controls for multi-agent systems with nonlinear and heterogeneous non-identical dynamics. Using feedback linearization, the nonlinear and heterogeneous dynamics of agents are transformed to identical linear dynamics and non-identical internal dynamics. Based on the dependence of agent outputs on agent inputs, feedback linearization may lead to a first-order or high-order tracking synchronization problem. The controller for each agent is designed to be fully distributed such that each agent only requires its own information and the information of its neighbors. The effectiveness of the proposed control protocols are verified by simulation on a microgrid test system. [ABSTRACT FROM AUTHOR]

This article identifies the parameters of an induction machine using limited and nonintrusive observations of available input voltages, stator currents, and the rotor speed. Parameter extraction is formulated as a nonconvex estimation problem, which is then relaxed to a convex conic optimization problem. While the resulting relaxation could exhibit a satisfactory performance, there might be cases where the solution of convex relaxation fails to satisfy the dynamic equations of the machine. This is remedied through a local search approach initiated using the solution obtained from the relaxed problem. The proposed method is experimentally verified on a squirrel-cage induction machine with missing measured data. Using the measured signals as the benchmark, time-domain transients produced by the parameters estimated using the proposed method show almost 20% better match compared to time-domain transients produced by the parameters obtained via conventional testing. [ABSTRACT FROM AUTHOR]

A power buffer is a power electronics converter with a large capacitor that shields a weak DC grid from abrupt load changes. Distributed control solutions have been shown to be superior to the decentralized ones; however, the effects of the communication network topology on the control performance of these buffers have not yet been studied. This article offers a data-driven optimal solution to reduce the interactions between different control loops of power buffers while minimizing a closed-loop performance function. Reinforcement learning methods deal with the optimal control of nonlinear systems, and a Tabu Search method addresses the resulting combinatorial problem. The proposed solutions are validated for a DC microgrid in a controller/hardware-in-the-loop environment. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of optimizing voltage set points and switching status of components in direct current power networks subject to physical and security constraints. The problem is cast as a mixed-integer nonlinear programming with two sources of computational complexity: i) Non-convex power flow equations, and ii) The presence of binary variables accounting for the on/off status of network components. A strengthened second-order cone programming (SOCP) relaxation is developed to tackle the non-convexity of power flow equations, and a branch-and-bound search is employed for determining optimal network configurations. The efficacy of the proposed method in optimizing the operation while mitigating contingencies is experimentally validated in a real-time hardware-in-the-loop environment using IEEE benchmark data. [ABSTRACT FROM AUTHOR]

Power buffers are power electronic converters, with large capacitors, that decouple volatile loads and a low-inertia distribution network in a DC microgrid. In this work, a set of distributed optimal control policies enable power buffers to reciprocally assist each other during abrupt load changes. While the majority of existing control paradigms are localized, enabling communication among buffers extends their effective range of assistance and helps them minimize a shared objective in a cooperative fashion. The control law's weights surfaces are learned for a mesh of reference loads of each power buffer. Hamilton-Jacobi-Bellman equation is solved by a continuous-time adaptive dynamic programming (ADP) approach with off-policy learning to directly provide a feedback controller, instead of existing approaches that obtain open-loop policies via Pontryagin's minimum principle. This paper presents the first attempt in using ADP techniques for the control of power buffers that respects their original nonlinear dynamics, overcoming the limitations of previous approaches based on small-signal analysis. Compared to the current literature, the proposed approach provides trained controllers that are known a priori, avoiding player-by-player solutions or real-time optimization procedures that could degrade performances or become computationally intensive. Hardware-in-the-loop emulations of a low-voltage DC microgrid validates the proposed approach. [ABSTRACT FROM AUTHOR]

This paper studies the acceleration of numerical simulations executed on Field-Programmable Gate Arrays (FPGAs) for electric machines presented by voltage-behind-reactance (VBR) models. In VBR models, the stator dynamics are modeled in abc coordinates, while the rotor dynamics are formulated in qd reference frame. Both induction motors and synchronous generators, operating without and with magnetic saturation, are considered. Once VBR models of these machine types are reviewed, their dynamic models are discretized using Runge-Kutta numerical routines. The detailed mapping of such discrete models to FPGA is provided using High-Level Synthesis, which directly converts untimed descriptions into VHDL or Verilog. An automated method finds the fastest FPGA architecture by finding the best set of synthesis options. Experimental results show that our FPGA-based acceleration flow leads to about 92-168 times average simulation speed-up for various machine types compared to the MATLAB simulation. [ABSTRACT FROM AUTHOR]

We extract the lumped-parameter model of a wound-rotor synchronous machine from its physics-based magnetic-equivalent circuit model. Model extraction is formulated as a weighted least square optimization with nonlinear constraints in which time-domain trajectories of flux linkages, currents, and the electromagnetic torque are used as input data to obtain the parameters of the $qd0$ model of the machine. The resulting problem is non-convex and cannot be solved using standard methods. The optimization problem is, therefore, convexified using a cone programming relaxation. The solution to the relaxed problem is used as an initial point for the interior-point method, leading to a reliable framework. Accurate estimations on stator resistance, leakage and mutual inductances in stator and rotor, rotor speed, effective turns-ratio between the field and stator windings, and the number of poles are obtained. Estimated parameters are validated against measured and estimated values reported in literature, and are used to develop a behavioral $qd0$ macromodel of the machine. [ABSTRACT FROM AUTHOR]

This paper presents an approach to obtain reduced-order models for power networks involving power electronic converters (PEC) via the frequency-domain balanced realizations (FDBR) technique. PECs play an essential role in power processing and energy conversion in modern electrical networks, such as the interconnection of renewable generators, HVDC links, and active filters. Integration of PECs into dynamic equivalents needs model-order reduction (MOR) in both low- and high-frequency ranges to account for both slow and fast dynamics due to the network and switching natures. The objective of the FDBR technique is to obtain an internally balanced system, i.e., an equally controllable/observable system, that can be reduced according to its dominant dynamics within the limited frequency bandwidths. This allows accounting for specific band-limited phenomena, such as those generated within a power network caused by PECs, which is the focus of this paper. The results show that faster yet accurate simulations are achieved by reduced-order models through FDBR compared to their full-order counterparts. [ABSTRACT FROM AUTHOR]

This paper proposes a data-driven model-free inverse reinforcement learning (RL) algorithm to reconstruct the unknown cost function of the demonstrated discrete-time (DT) dynamical systems with antagonistic disturbances. We propose an inverse RL policy iteration scheme that uses system dynamics and the input policies, for deriving our main result of a data-driven off-policy inverse Q-learning algorithm using only demonstrated trajectories of the antagonistic system without knowing system dynamics and the control policy gain. This data-driven algorithm consists of Q -function evaluation, state-penalty weight improvement, and action policies update. We guarantee unbiased estimates in the data-driven algorithm when exploration noises exist for the persistence of the excitation. An example verifies the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract Resilience of multi-agent systems (MAS) reflects their capability to maintain normal operation, at a prescribed level in the presence of unintended faults. In this paper, we investigate resilient control of MAS under faults on sensors and actuators. We propose four resilient state feedback based leader–follower tracking protocols. For the case of sensor faults, we develop an adaptive compensation protocol and an H ∞ control protocol. For the case of simultaneous sensor and actuator faults, we further propose an enhanced adaptive compensation protocol and an enhanced H ∞ control protocol. We show the duality between the adaptive compensation protocols and the H ∞ control protocols. For adaptive compensation protocols, faults on sensors and actuators are rejected by using local adaptive sensor and actuator compensators, respectively. Moreover, by employing a static output-feedback design technique, we propose H ∞ control protocols that guarantee bounded L 2 gains of certain errors in terms of the L 2 norms of fault signals. This further allows us to prove resilience even if sensor faults are unbounded. Finally, simulation studies validate the effectiveness of the proposed protocols. [ABSTRACT FROM AUTHOR]

Chondroitin sulphate is a sulphated glycosaminoglycan biopolymer composed over 100 individual sugars. Chondroitin sulphate nanoparticles (NPs) loaded with catechin were prepared by an ionic gelation method using AlCl3 and optimised for polymer and cross‐linking agent concentration, curing time and stirring speed. Zeta potential, particle size, loading efficiency, and release efficiency over 24 h (RE24 %) were evaluated. The surface morphology of NPs was investigated by scanning electron microscopy and their thermal behaviour by differential scanning calorimetric. Antioxidant effect of NPs was determined by chelating activity of iron ions. The cell viability of mesenchymal stem cells was determined by 3‐[4, 5‐dimethylthiazol‐2‐yl]‐2, 5‐diphenyl tetrazolium bromide assay and the calcification of osteoblasts was studied by Alizarin red staining. The optimised NPs showed particle size of 176 nm, zeta potential of −20.8 mV, loading efficiency of 93.3% and RE24 % of 80.6%. The chatechin loaded chondroitin sulphate NPs showed 70‐fold more antioxidant activity, 3‐fold proliferation effect and higher calcium precipitation in osteoblasts than free catechin. [ABSTRACT FROM AUTHOR]

The Phase II upgrade of the Large Hadron Collider (LHC) will raise the luminosity of the LHC by at least five times. Due to the aging of the current electronics in the detectors and increased expected radiation from higher luminosity, all electronics of the ATLAS central hadronic calorimeter will be upgraded. Improved prototypes of all the front-end detector electronics have been designed, manufactured and tested for the Phase II upgrade. The results of the design and upgrade process of the Low Voltage Power Supply (LVPS) of TileCal are reported. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive output containment control of general linear heterogeneous multi-agent systems with multiple unknown leaders whose dynamics are only known to the neighboring followers. The output containment control objective is to assure the convergence of each follower’s output to the dynamic convex hull spanned by the leaders’ outputs. Compared with the situation where the leaders’ dynamics are known to each follower exactly, local adaptive observers are presented at each follower to estimate the leaders’ dynamics. Then, an adaptive tuning law is proposed to solve the associated output regulator equations without knowing leaders’ dynamics. Two distributed control protocols, using state-feedback and dynamic output-feedback are locally designed, using the estimated leaders’ dynamics and adaptive solutions to the output regulator equations. Both proposed control protocols are verified using numerical simulations. [ABSTRACT FROM AUTHOR]

This study investigates the bipartite output containment control of general linear heterogeneous multi‐agent systems on signed communication networks with antagonistic interactions, modelled as negative weights on the digraph. The authors first formulate a new control problem referred to as the bipartite output containment. This control paradigm aims to make each follower's output converge to a dynamic convex hull spanned by the outputs and the sign‐inverted outputs of multiple leaders. Second, the authors prove that the bipartite output containment problem can be solved by making some suitably defined signed output containment errors go to zero asymptotically. Then, the authors construct three different control protocols, using full‐state feedback, static output‐feedback, and dynamic output‐feedback designs. These control protocols are based on a distributed feed‐forward approach, which requires a feedback gain to make the closed‐loop system matrix stable, and a feed‐forward gain to drive trajectories of the closed‐loop system toward a subspace that renders the regulated signed output containment errors zero. Numerical simulations are performed to validate the proposed control protocols. [ABSTRACT FROM AUTHOR]

In this study, a unified distributed static output-feedback (OPFB) control protocol is presented for multi-agent systems. The proposed approach is unified in the sense that it is applicable to both homogeneous and heterogeneous multi-agent systems. Despite its importance, distributed OPFB control design is not considered for heterogeneous systems in the literature. Moreover, as will be shown, existing static OPFB controllers for homogeneous systems are vulnerable to attacks on sensors and actuators. More precisely, it is shown that a compromised agent can make an intact agent turn away from the leader if there is a directed path of any length from the compromised agent to the intact agent. To overcome these shortcomings, a distributed OPFB controller is presented which is (i) applicable to both homogeneous and heterogeneous systems, and (ii) is resilient against attacks on sensors and actuators. The proposed framework prevents attacks on sensors and actuators from propagating across the network and, thus, guarantees synchronisation of intact agents to the leader. To further improve the resiliency and guarantee synchronisation of even compromised agents, a disturbance compensator is designed. A significant advantage of this approach is that no assumption on topological connectivity and the number of agents under attack is required. [ABSTRACT FROM AUTHOR]

In this study, a unified distributed static output‐feedback (OPFB) control protocol is presented for multi‐agent systems. The proposed approach is unified in the sense that it is applicable to both homogeneous and heterogeneous multi‐agent systems. Despite its importance, distributed OPFB control design is not considered for heterogeneous systems in the literature. Moreover, as will be shown, existing static OPFB controllers for homogeneous systems are vulnerable to attacks on sensors and actuators. More precisely, it is shown that a compromised agent can make an intact agent turn away from the leader if there is a directed path of any length from the compromised agent to the intact agent. To overcome these shortcomings, a distributed OPFB controller is presented which is (i) applicable to both homogeneous and heterogeneous systems, and (ii) is resilient against attacks on sensors and actuators. The proposed framework prevents attacks on sensors and actuators from propagating across the network and, thus, guarantees synchronisation of intact agents to the leader. To further improve the resiliency and guarantee synchronisation of even compromised agents, a disturbance compensator is designed. A significant advantage of this approach is that no assumption on topological connectivity and the number of agents under attack is required. [ABSTRACT FROM AUTHOR]

Low generational inertia and lack of damping elements cause stability concerns in dc microgrids. Power buffers have been introduced to damp volatile load demands and improve microgrid's stability. Power buffer is a power electronics converter with large storage components (e.g., capacitors), which can decouple dynamics of a power distribution network and electronic loads by adjusting its input impedance and stored energy. Typically, power buffers are controlled individually to serve local loads. Alternatively, collective operation of power buffers is considered here to extend their damping effect to neighboring loads. Additionally, the group operation allows buffer designs with smaller storage components. A supervisory control to manage energy-impedance profiles of power buffers across a grid would require a complex communication network. Alternatively, distributed control lays a reliable ground to link power buffers with a minimal communication. This work offers a fully distributed feedback control algorithm to collectively manage the power buffers, using a sparse communication network. The controller enables the buffers to collectively respond to any load transient. Hardware-in-the-Loop simulation of a dc microgrid is used to show the controller's efficacy; it successfully groups power buffers in the neighborhood of the affected load and manages their energy reservoirs to shape the power supplied by the grid. [ABSTRACT FROM AUTHOR]

This paper presents hybrid automaton modeling, comparative model validation, and formal verification of stability through reachability analysis of pulse width modulation (PWM) dc–dc converters. Conformance degree provides a measure of closeness between the proposed hybrid automata models and experimental data. Nondeterminism due to variations in circuit parameters is modeled using interval matrices. In direct contrast to the unsound and computationally-intensive Monte Carlo simulation, reachability analysis is introduced to overapproximate the set of reachable states and ensure stable operation of PWM dc–dc converters. Using a 200 W experimental prototype of a buck converter, hybrid automata models of open-loop, and hysteresis-controlled converters are first validated against experimental data using their conformance degrees. Next, converter stability is formally verified through reachability analysis and informally validated using Monte Carlo simulations and experimental results. [ABSTRACT FROM PUBLISHER]

This paper reviews and applies the balanced realization (BR) theory to obtain reduced-order models from dynamic system equivalents of electric power networks. BR allows obtaining reduced-order models via a process in which the original asymptotic stable system is internally balanced. The balanced system is truncated according to its dominant dynamics. It can be proven that the truncated, that is, reduced-order, system is also stable. This paper applies the BR method to dynamic system equivalents represented as frequency-dependent network equivalents (FDNEs). Furthermore, it shows that an assumed reduced-order FDNE can be further reduced via the BR process. Four case studies, involving one transmission network and three wind power plants, are presented. [ABSTRACT FROM PUBLISHER]

Low-inertia dc microgrids often rely on storage devices to buffer energy and handle abrupt load changes. An alternative approach involves the concept of power buffers, power electronics converters with bulky storage components that precede the final point-of-load converters, and decouple the grid and load dynamics. Proper adjustment of the input impedances of power buffers helps to shape the trajectory of the transient imposed on a dc microgrid. A communication network facilitates information exchange among active loads (loads augmented with power buffers). Such group information helps to collectively respond to any load change; an optimal response with the least energy extract from individual buffers. A game-theoretic performance function is defined for active loads. Then, a distributed control policy simultaneously minimizes all performance functions. A low-voltage dc microgrid, simulated in MATLAB/Simulink environment, is used to study the effectiveness of the proposed methodology. [ABSTRACT FROM PUBLISHER]

A cooperative distributed secondary/primary control paradigm for AC microgrids is proposed. This solution replaces the centralized secondary control and the primary-level droop mechanism of each inverter with three separate regulators: voltage, reactive power, and active power regulators. A sparse communication network is spanned across the microgrid to facilitate limited data exchange among inverter controllers. Each controller processes its local and neighbors' information to update its voltage magnitude and frequency (or, equivalently, phase angle) set points. A voltage estimator finds the average voltage across the microgrid, which is then compared to the rated voltage to produce the first-voltage correction term. The reactive power regulator at each inverter compares its normalized reactive power with those of its neighbors, and the difference is fed to a subsequent PI controller that generates the second-voltage correction term. The controller adds the voltage correction terms to the microgrid rated voltage (provided by the tertiary control) to generate the local voltage magnitude set point. The voltage regulators collectively adjust the average voltage of the microgrid at the rated voltage. The voltage regulators allow different set points for different bus voltages and, thus, account for the line impedance effects. Moreover, the reactive power regulators adjust the voltage to achieve proportional reactive load sharing. The third module, the active power regulator, compares the local normalized active power of each inverter with its neighbors' and uses the difference to update the frequency and, accordingly, the phase angle of that inverter. The global dynamic model of the microgrid, including distribution grid, regulator modules, and the communication network, is derived, and controller design guidelines are provided. Steady-state performance analysis shows that the proposed controller can accurately handle the global voltage regulation and proportional load sharing. An AC microgrid prototype is set up, where the controller performance, plug-and-play capability, and resiliency to the failure in the communication links are successfully verified. [ABSTRACT FROM AUTHOR]

A distributed networked method for load sharing of parallel converters is proposed. Using consensus-voting protocols, the need for a master converter or a central controller is eliminated. The proposed modular structure does not require a priori knowledge of the number of active converters, which makes it a viable option for a plug-and-play operation. The voltage regulation at the desired set point and the consensus of the per-unit currents are analytically proven for the steady-state conditions. Moreover, in the absence of a centralized controller, measuring output voltages of each converter individually can lead to a measurement mismatch. The effect of this voltage mismatch on the controller performance is analyzed, and a solution is provided. Experimental results verify the proposed distributed control method using a parallel four-converter system and show its efficacy in response to changes in operational conditions and its resiliency against the loss of converters or communication links. [ABSTRACT FROM AUTHOR]