Showing papers on "Control reconfiguration published in 2015"

Dynamic reconfiguration of frontal brain networks during executive cognition in humans.

Abstract: The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia.

Reconfigurable Antennas: Design and Applications

Abstract: The advancement in wireless communications requires the integration of multiple radios into a single platform to maximize connectivity. In this paper, the design process of reconfigurable antennas is discussed. Reconfigurable antennas are proposed to cover different wireless services that operate over a wide frequency range. They show significant promise in addressing new system requirements. They exhibit the ability to modify their geometries and behavior to adapt to changes in surrounding conditions. Reconfigurable antennas can deliver the same throughput as a multiantenna system. They use dynamically variable and adaptable single-antenna geometry without increasing the real estate required to accommodate multiple antennas. The optimization of reconfigurable antenna design and operation by removing unnecessary redundant switches to alleviate biasing issues and improve the system's performance is discussed. Controlling the antenna reconfiguration by software, using Field Programmable Gate Arrays (FPGAs) or microcontrollers is introduced herein. The use of Neural Networks and its integration with graph models on programmable platforms and its effect on the operation of reconfigurable antennas is presented. Finally, the applications of reconfigurable antennas for cognitive radio, Multiple Input Multiple Output (MIMO) channels, and space applications are highlighted.

Assessing the Potential of Network Reconfiguration to Improve Distributed Generation Hosting Capacity in Active Distribution Systems

Abstract: As the amount of distributed generation (DG) is growing worldwide, the need to increase the hosting capacity of distribution systems without reinforcements is becoming nowadays a major concern. This paper explores how the DG hosting capacity of active distribution systems can be increased by means of network reconfiguration, both static, i.e., grid reconfiguration at planning stage, and dynamic, i.e., grid reconfiguration using remotely controlled switches as an active network management (ANM) scheme. The problem is formulated as a mixed-integer, nonlinear, multi-period optimal power flow (MP-OPF) which aims to maximize the DG hosting capacity under thermal and voltage constraints. This work further proposes an algorithm to break-down the large problem size when many periods have to be considered. The effectiveness of the approach and the significant benefits obtained by static and dynamic reconfiguration options in terms of DG hosting capacity are demonstrated using a modified benchmark distribution system.

Adaptive Fault-Tolerant Tracking Control for Linear and Lipschitz Nonlinear Multi-Agent Systems

Abstract: This paper considers the problem of fault-tolerant tracking control for linear and Lipschitz nonlinear multi-agent systems subject to actuator faults and the leader's bounded unknown input. The communication topology is the undirected subgraph with directed connections between the leader and the followers. Based on the relative states of neighbors and a general actuator fault model, an adaptive fault-tolerant control protocol is proposed to compensate for the failure effects on consensus tracking where the feedback matrices update the parameters by the online estimation of actuator faults. The criteria of reaching consensus tracking despite the actuator faults for both linear and Lipschitz nonlinear agents are derived, respectively. Finally, two examples are included to illustrate the theoretical results.

Software-Defined Networking for RSU Clouds in Support of the Internet of Vehicles

Abstract: We propose a novel roadside unit (RSU) cloud, a vehicular cloud, as the operational backbone of the vehicle grid in the Internet of Vehicles (IoV). The architecture of the proposed RSU cloud consists of traditional and specialized RSUs employing software-defined networking (SDN) to dynamically instantiate, replicate, and/or migrate services. We leverage the deep programmability of SDN to dynamically reconfigure the services hosted in the network and their data forwarding information to efficiently serve the underlying demand from the vehicle grid. We then present a detailed reconfiguration overhead analysis to reduce reconfigurations, which are costly for service providers. We use the reconfiguration cost analysis to design and formulate an integer linear programming (ILP) problem to model our novel RSU cloud resource management (CRM). We begin by solving for the Pareto optimal frontier (POF) of nondominated solutions, such that each solution is a configuration that minimizes either the number of service instances or the RSU cloud infrastructure delay, for a given average demand. Then, we design an efficient heuristic to minimize the reconfiguration costs. A fundamental contribution of our heuristic approach is the use of reinforcement learning to select configurations that minimize reconfiguration costs in the network over the long term. We perform reconfiguration cost analysis and compare the results of our CRM formulation and heuristic. We also show the reduction in reconfiguration costs when using reinforcement learning in comparison to a myopic approach. We show significant improvement in the reconfigurations costs and infrastructure delay when compared to purist service installations.

Multi-agent plan reconfiguration under local LTL specifications

Abstract: We propose a cooperative motion and task planning scheme for multi-agent systems where the agents have independently assigned local tasks, specified as linear temporal logic formulas. These tasks contain hard and soft sub-specifications. A least-violating initial plan is synthesized first for the potentially infeasible task and the partially-known workspace. This discrete plan is then implemented by the potential-field-based navigation controllers. While the system runs, each agent updates its knowledge about the workspace via its sensing capability and shares this knowledge with its neighbouring agents. Based on the knowledge update, each agent verifies and revises its motion plan in real time. It is ensured that the hard specification is always fulfilled for safety and the satisfaction for the soft specification is improved gradually. The design is distributed as only local interactions are assumed. The overall framework is demonstrated by a case study and an experiment.

Simultaneous Reconfiguration, Optimal Placement of DSTATCOM, and Photovoltaic Array in a Distribution System Based on Fuzzy-ACO Approach

Abstract: In this paper, a combination of a fuzzy multiobjective approach and ant colony optimization (ACO) as a metaheuristic algorithm is used to solve the simultaneous reconfiguration and optimal allocation (size and location) of photovoltaic (PV) arrays as a distributed generation (DG) and distribution static compensator (DSTATCOM) as a distribution flexible ac transmission system (DFACT) device in a distribution system. The purpose of this research includes loss reduction, voltage profile (VP) improvement, and increase in the feeder load balancing (LB). The proposed method is validated using the IEEE 33-bus test system and a Tai-Power 11.4-kV distribution system as a real distribution network. The results proved that simultaneous reconfiguration and optimal allocation of PV array and DSTATCOM unit leads to significantly reduced losses, improved VP, and increased LB. Obtained results have been compared with the base value and found that simultaneous placement of PV and DSTATCOM along with reconfiguration is more beneficial than separate single-objective optimization. Also, the proposed fuzzy-ACO approach is more accurate as compared to ACO and other intelligent techniques like fuzzy-genetic algorithm (GA) and fuzzy-particle swarm optimization (PSO).

Integral-Type Sliding Mode Fault-Tolerant Control for Attitude Stabilization of Spacecraft

Abstract: Two fault-tolerant control (FTC) schemes for spacecraft attitude stabilization with external disturbances are proposed in this brief. The approach is based on integral-type sliding mode control strategy to compensate for actuator faults without controller reconfiguration. First, a basic integral-type sliding mode FTC scheme is designed so that sliding manifold can be maintained from the very beginning. Once the system enters the sliding mode, the dynamics of the closed-loop system with actuator fault is identical to that of the nominal healthy system. Second, the integral-type sliding mode fault-tolerant controller is incorporated with adaptive technique to accommodate actuator faults so that the required boundary information can be relaxed. The effectiveness of the proposed schemes against actuator faults is demonstrated in simulation.

Reconfigurable Computing Architectures

Abstract: Reconfigurable architectures can bring unique capabilities to computational tasks. They offer the performance and energy efficiency of hardware with the flexibility of software. In some domains, they are the only way to achieve the required, real-time performance without fabricating custom integrated circuits. Their functionality can be upgraded and repaired during their operational lifecycle and specialized to the particular instance of a task. We survey the field of reconfigurable computing, providing a guide to the body-of-knowledge accumulated in architecture, compute models, tools, run-time reconfiguration, and applications.

Finite-time fault-tolerant attitude stabilization for spacecraft with actuator saturation

Abstract: This paper addresses the finite-time fault-tolerant attitude stabilization control problem for a rigid spacecraft in the presence of actuator faults or failures, external disturbances, and modeling uncertainties. First, a basic fault-tolerant controller is proposed to accommodate actuator faults or failures and guarantee local finite-time stability. When there is no a priori knowledge of actuator faults, disturbances, and inertia uncertainties, an online adaptive law is proposed to estimate the bounds of these uncertainties, and local finite-time convergence is achieved by an adaptive fault-tolerant controller. In addition, another adaptive fault-tolerant control scheme is derived that explicitly takes into account the actuator saturation. The proposed attitude controller provides fault-tolerant capability despite control input saturation and ensures that attitude and angular velocity converge to a neighborhood of the origin in finite time. Finally, simulation studies are presented to demonstrate the effectiveness of the proposed method.

Xhaul: toward an integrated fronthaul/backhaul architecture in 5G networks

Abstract: The Xhaul architecture presented in this article is aimed at developing a 5G integrated backhaul and fronthaul transport network enabling flexible and software-defined reconfiguration of all networking elements in a multi-tenant and service-oriented unified management environment. The Xhaul transport network vision consists of high-capacity switches and heterogeneous transmission links (e.g., fiber or wireless optics, high-capacity copper, mmWave) interconnecting remote radio heads, 5G points of attachment (5GPoAs, e.g., macro- and small cells), centralized- processing units (mini data centers), and points of presence of the core networks of one or multiple service provider(s). This transport network shall flexibly interconnect distributed 5G radio access and core network functions, hosted on network centralized nodes, through the implementation of a control infrastructure using a unified, abstract network model for control plane integration (Xhaul Control Infrastructure, XCI); and a unified data plane encompassing innovative high-capacity transmission technologies and novel deterministic-latency switch architectures (Xhaul packet Forwarding Element, XFE). Standardization is expected to play a major role in a future 5G integrated front haul/backhaul architecture for multi-vendor interoperability reasons. To this end, we review the major relevant activities in the current standardization landscape and the potential impact on the Xhaul architecture.

Photovoltaic Systems Reliability Improvement by Real-Time FPGA-Based Switch Failure Diagnosis and Fault-Tolerant DC–DC Converter

Abstract: The increased penetration of photovoltaic (PV) systems in different applications with critical loads such as in medical applications, industrial control systems, and telecommunications has highlighted pressing needs to address reliability and service continuity. Recently, distributed maximum power point tracking architectures, based on dc–dc converters, are being used increasingly in PV systems. Nevertheless, dc–dc converters are one of the important failure sources in a PV system. Since the semiconductor switches are one of the most critical elements in these converters, a fast switch fault detection method (FDM) is a mandatory step to guarantee the service continuity of these systems. This paper proposes a very fast FDM based on the shape of the inductor current associated to fault-tolerant (FT) operation for boost converter used in PV systems. By implementing fault diagnosis and reconfiguration strategies on a single field-programmable gate array target, both types of switch failure (open- and short-circuit faults) can be detected, identified and handled in real time. The FDM uses the signal provided by the current sensor dedicated to the control of the system. Consequently, no additional sensor is required. The proposed FT topology is based on a redundant switch. The results of hardware-in-the-loop and experimental tests, which all confirm the excellent performances of the proposed approach, are presented and discussed. The obtained results show that a switch fault can be detected in less than one switching period, typically around 100 ms in medium power applications, by the proposed FDM.

Robust Distribution Network Reconfiguration

Abstract: We propose a two-stage robust optimization model for the distribution network reconfiguration problem with load uncertainty. The first-stage decision is to configure the radial distribution network and the second-stage decision is to find the optimal a/c power flow of the reconfigured network for given demand realization. We solve the two-stage robust model by using a column-and-constraint generation algorithm, where the master problem and subproblem are formulated as mixed-integer second-order cone programs. Computational results for 16, 33, 70, and 94-bus test cases are reported. We find that the configuration from the robust model does not compromise much the power loss under the nominal load scenario compared to the configuration from the deterministic model, yet it provides the reliability of the distribution system for all scenarios in the uncertainty set.

Fault Estimation and Fault-Tolerant Control for Discrete-Time Dynamic Systems

Abstract: In this paper, a novel discrete-time estimator is proposed, which is employed for simultaneous estimation of system states, and actuator/sensor faults in a discrete-time dynamic system. The existence of the discrete-time simultaneous estimator is proven mathematically. The systematic design procedure for the derivative and proportional observer gains is addressed, enabling the estimation error dynamics to be internally proper and stable, and robust against the effects from the process disturbances, measurement noise, and faults. Based on the estimated fault signals and system states, a discrete-time fault-tolerant design approach is addressed, by which the system may recover the system performance when actuator/sensor faults occur. Finally, the proposed integrated discrete-time fault estimation and fault-tolerant control technique is applied to the vehicle lateral dynamics, which demonstrates the effectiveness of the developed techniques.

Expected Cost Minimization of Smart Grids With Plug-In Hybrid Electric Vehicles Using Optimal Distribution Feeder Reconfiguration

Abstract: Stochastic charging behavior of plug-in hybrid electric vehicles (PHEVs) under different charging strategies brings new challenges for distribution networks such as feeder overloading and loss increase. In this way, the augmented penetration of these vehicles mandates employing new operative tools to inspect their impacts on electrical grids. Therefore, this paper proposes a novel optimal stochastic reconfiguration methodology to moderate the charging effect of PHEVs by changing the topology of grid using some remote controlled switches. Uncertainties associated with network demand, energy price, and PHEV charging behavior in different charging frameworks are handled with Monte Carlo simulation and the proposed stochastic problem is solved with krill herd optimization algorithm. Numerical studies on Tai-power distribution system verify the efficacy of proposed reconfiguration to improve the system performance considering PHEV charging loads.

Frequency Selective Surfaces

Abstract: A switchable Frequency Selective Surface (FSS) in which the switchable elements are Plasma-shells. Plasma-shells as described herein allow for control or ‘reconfiguration’ of the FSS electromagnetic (EM) properties.

An on-demand reconfigurable control plane architecture (orca) integrating millimeter-wave small cell and microwave macro cell

Abstract: Millimeter-wave (mmWave) band communication is a very promising technology for 5G small cells. In practice, such a new system will coexist with legacy or evolved microwave band systems, such as E-UTRAN LTE macro-cell cellular systems, for a long time to come. Considering the typical scenarios where a macro cell offers umbrella coverage for clusters of small cells, several control plane (C-plane) architectural choices of macro-assisted 5G mmWave systems from both UE and network's perspectives are evaluated. The proposed On-demand Reconfiguration C-Plane Architecture (ORCA) for Macro-assisted Millimeter Wave (mmWave) small cells is designed to meet 5G expectations of dense deployment of small cells and UEs and beamformed intermittent Gbps links.

Reconfigurable Coordination of Distributed Discrete Event Control Systems

Abstract: Dynamic reconfigurability is receiving more and more attention from both academy and industry, which means the ability to flexibly modify system functions by adding/removing hardware/software components, modifying logic relation between components, or updating particular system data at runtime without sacrificing the system performance. A distributed reconfigurable discrete event control system (DRDECS) is composed of several networked reconfigurable subsystems. In order to realize system functions, these reconfigurable subsystems communicate and coordinate with each other, since any casually reconfiguration applied to a subsystem may cause risks to others, or even to the safety of the whole system. This brief proposes a new coordination method for a DRDECS, where each subsystem is modeled by a reconfigurable timed net condition/event system. A virtual coordinator together with a communication protocol between it and subsystems is developed in order to achieve two aims: 1) to coordinate subsystems with an optimal coordination solution using judgement matrices while multiple subsystems require global reconfigurations and 2) to reduce exchanged messages between the coordinator and these subsystems. Furthermore, for the purpose of checking functional and temporal properties of a DRDECS with this virtual coordinator, a computation tree logic-based model checking method is applied. Finally, a hypothetic manufacturing plant is used as a running example to illustrate this brief.

Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation

Abstract: Different types of distributed generation (DG) are broadly used and optimally placed in a distribution system to improve its performance. Since the network configuration affects the system operational conditions, the network reconfiguration and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent from achieving the optimal solution. This paper presents a novel hybrid method of metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs. The developed backward/forward power flow is adopted to consider the PV(Q) model of DG. Moreover, different patterns of load types are taken into consideration to perform a practical study. To assess the capabilities of the proposed method, simulations are carried out on IEEE 33-bus and 83-bus practical distribution network of Taiwan Power Company. Furthermore, the proposed method is applied to a 33-bus unbalanced distribution network to verify its applicability in unbalanced distribution systems. The obtained results demonstrate the effectiveness of the proposed method to find optimal status of switches, as well as locations and sizes of DG units, in a rather shorter time than other approaches in the literature.

Dynamic Low-Power Reconfiguration of Real-Time Systems With Periodic and Probabilistic Tasks

Abstract: This paper deals with the dynamic low-power reconfiguration of a real-time system. It processes periodic and probabilistic tasks that have hard/soft deadlines corresponding to internal/external events. A runtime event-based reconfiguration scenario is a dynamic operation allowing the addition/removal of the assumed periodic/probabilistic tasks. Thereafter, some tasks may miss their hard deadlines and the power consumption may increase. In order to reconfigure the system to be feasible, i.e., satisfying its real-time constraints with low-power consumption, this research presents a software-agent-based architecture. An intelligent agent is developed, which provides four solutions to reconfigure the system at runtime. For these solutions, in order to reconfigure the probabilistic tasks to be feasible, the agent modifies their temporal parameters dynamically; moreover, in order to feasibly serve the probabilistic tasks and reduce the system's power consumption, the agent provides three virtual processors by dynamically extending the periods of the periodic tasks. A simulation study verifies the effectiveness of the agent.

Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration

Abstract: In order to optimize their assets, electrical power distribution companies seek out various techniques to improve system operation and its different variables, like voltage levels, active power losses and so on. A few of the tools applied to meet these objectives include reactive power compensation, use of voltage regulators, and network reconfiguration. One target most companies aim at is power loss minimization; one available tool to do this is distribution system reconfiguration. To reconfigure a network in radial power distribution systems means to alter the topology changing the state of a set of switches normally closed (NC) and normally opened (NO). In restructured electrical power business, a company must also consider obtaining a topology as reliable as possible. In most cases, reducing the power losses is no guarantee of improved reliability. This paper presents a multiobjective algorithm to reduce power losses while improving the reliability index using the artificial immune systems technique applying graph theory considerations to improve computational performance and Pareto dominance rules. The proposed algorithm is tested on a sample system, 14-bus test system, and on Administracion Nacional de Electricidad (ANDE) real feeder (CBO-01 23-kV feeder).

Robust Control of Fault-Tolerant Permanent-Magnet Synchronous Motor for Aerospace Application With Guaranteed Fault Switch Process

Abstract: This paper proposes a novel ten-phase fault-tolerant permanent-magnet synchronous motor (FTPMSM) with two stators and two rotors on the same shaft. Furthermore, a concentrated, single-layer, and alternate-teeth-wound winding is adopted to enhance the fault isolation capacity of the motor. In addition, we propose a new approach to the speed control of the developed motor, which takes the electromagnetic torque ripple in the fault switch process into account. The control can guarantee the uniform boundedness and uniform ultimate boundedness of the system regardless of the load disturbance and the parameter variation, particularly for the fault switch process after a fault occurrence before the fault-tolerant control can take effect. Moreover, an optimal torque control is adopted to further improve the fault-tolerant performance, which enables a ripple-free torque operation under open-circuit and short-circuit fault conditions. Simulation and experimental results show that the FTPMSM system with the proposed control strategy has excellent fault-tolerant performance and good robustness. This paper provides an innovative approach by employing a robust control for a speed loop to guarantee the fault-tolerant performance of the proposed motor system under normal and fault conditions, even in the fault switch process.

Finite-Time Attitude Tracking of Spacecraft With Fault-Tolerant Capability

Abstract: A finite-time attitude tracking control scheme is presented for rigid spacecraft subject to constant but unknown inertia and external disturbances. The controller, developed using sliding mode control technique, has great fault-tolerant capability to accommodate four types of actuator faults. Different from most of the existing works on attitude fault-tolerant control (FTC), the developed controller guarantees the desired attitude to be followed in finite time, which is critical for FTC systems. Moreover, the convergence time is an explicit parameter for designer’s choice. Thus, the controller design simply meets the finite-time requirement. The attitude-tracking performance is evaluated through a numerical example.

High-Reliability FPGA-Based Systems: Space, High-Energy Physics, and Beyond

Abstract: Field-programmable gate arrays (FPGAs) have been shown to provide high computational density and efficiency for many computing applications by allowing circuits to be customized to any application of interest. FPGAs also support programmability by allowing the circuit to be changed at a later time through reconfiguration. There is great interest in exploiting these benefits in space and other radiation environments. FPGAs, however, are very sensitive to radiation and great care must be taken to properly address the effects of radiation in FPGA-based systems. This paper will highlight the effects of radiation on FPGA-based systems and summarize the challenges in deploying FPGAs in such environments. Several well-known mitigation methods will be described and the unique ability of FPGAs to customize the system for improved reliability will be discussed. Finally, two case studies summarizing successful deployment of FPGAs in radiation environments will be presented.