Intelligent buildings are responsible for ensuring the indoor air quality for their occupants under normal operation as well as under possibly harmful contaminant events due to accidental or malicious actions. An emerging environmental control application is monitoring the intelligent buildings against the presence of such events, by incorporating various sensing technologies and distributed detection and isolation algorithms. The needed simplicity, the improved scalability and fault tolerance are some of the main reasons for choosing distributed approaches over centralized ones. Hence, the effective partitioning of buildings into smaller sections for contaminant detection and isolation approaches is of great importance. In this paper, we present a heuristic algorithm for partitioning the building into smaller sections. The proposed algorithm is based on matrix clustering techniques and groups the building zones in order to form the different sections while ensuring (i) maximum decoupling between the various sections, (ii) strong connectivity between the zones of a section and (iii) fairness with respect to the number of allocated zones. The partitioning is achieved in near real time, providing the ability of repartitioning and adapting to the dynamic nature of the airflows. The main contribution of this work is the automatic partitioning of the building into sections, which enables the distributed simulation, modeling, analysis and management of the intelligent building while ensuring the effective detection and isolation of contaminants in the building interior.
This paper proposes an approach to the optimal fuzzy modeling of a nonlinear servo system application represented by an electromagnetic actuated clutch system. The nonlinear model of the process is first linearized around several operating points of the input-output static map of the process. Discrete-time Takagi-Sugeno (T-S) fuzzy models of the process are derived on the basis of the modal equivalence principle, and the rule consequents of these T-S fuzzy models contain the linearized state-space models of the process. Optimization problems are defined which aim the minimization of objective functions (OFs) defined as the mean of squared modeling errors (the difference between the process output and the fuzzy model output). The variables of the OFs are represented by a part of the parameters of the input membership functions. A Particle Swarm Optimization (PSO) algorithm solves the optimization problem and gives the optimal T-S fuzzy models. A set of simulation results is included to validate the PSO algorithm-based modeling approach and the optimal T-S fuzzy models for the electromagnetic actuated clutch system.
In this paper, we discuss two things. In the first part of the paper, we discuss the means of processing the speech signal using the Mel Frequency Cepstral Coefficients and the basics of voice characteristics. The problem of voice recognition was already implemented at the hardware level, but in this we propose a solution to the problem on the software end with a higher level of accuracy. Then in the second part, we will discuss the application developed on Android which is able to perform both single speaker and multi-speaker recognition. The multi-speaker feature enables the system to identify more than one person speaking by splitting the input into smaller blocks and treating each block as a single speaker identification problem. In the single speaker recognition case, the algorithm is able to correctly identify the individual 90.3% of the time. In the multi-speaker recognition case, up to 3 individuals are correctly identified roughly 86% of the time. The average identification time is 220ms across a database of 415 samples.
Electric vehicles (EVs) and their application raise new questions and pose many new demands. Accordingly, the increasing amount of charging processes by EVs is a new and growing impact on the grid load. In order to deal with this impact and the resulting demands, load shifting allows the grid load to be adjusted. Taking this into consideration this paper initially analyzes, based on field test measurements, the EVs' occupation and extracts the times they are parked at a charging point. Combining this with the EVs' charging power, options for load shifting are discussed and emulated based on real data. The database includes charging processes of 500 people and a 785.000 km mileage of pure battery electric vehicles with a DC fast-charging option and extended range electric vehicles. The results indicate that EVs can partly be used as grid controlled load without changing the utilization.
This paper introduces a new discrete-time fractional-order power system stabilizers (DTFoPSS) that can be used to stabilize synchronous machines connected to infinite bus subject to both local and inter-area mode of oscillations. The dynamics of the proposed stabilizers are of second-order IIR-type controllers that depend only on the fractional order 0 <; α ≤ 1. The DTFoPSS will be used in both single and multi-machine infinite bus systems triggered by severe disturbances. The flat phase characteristics make the DTFoPSS more appealing to adopt than their integer-order counterparts. They outperformed the continuous integer-order power system stabilizers (IoPSS) in single-machine infinite-bus systems, while exhibit identical performance to that of the IoPSS in multi-machine ones. The main points of this work are demonstrated via numerical simulations.
The control plane is an essential part of the SDN architecture, so it is very important to give proper attention to any proposal or design of an SDN controller. During the past few years, several controllers have been developed and several studies have been done to evaluate, compare and test the performance of these controllers. In this paper, new controllers are tested, such as ONOS and Libfluid-based controllers (raw, base), using Cbench, an OpenFlow testing tool. Even though the results show that MUL, Beacon, and Maestro (in latency mode) are the best performing controllers; however, the selection of the best-fitted controller should be based on several criteria, per user requirements.
The purpose of this paper is the metrological characterization of the infrared distance sensor Teraranger One, developed and built by Terabee HQ, located in Saint Genis Poully, near Geneve. The purpose of this project is to give to the aircraft a frontal anticollision system based on the sensor in question, with the additional functionality of maintaining a fixed distance from the detected target. The control of the position in the frontal direction is maintained through maneuvers of pitch, which alter the relative height of the nose and the rear of the aircraft, allowing the latter to advance or retreat. The controls roll, yaw and throttle are not affected by this movement. Therefore, to obtain the control using a distance sensor it is sufficient that the latter is introduced in the control chain of the only pitch channel. In this way, the other controls will still be used, and their operation will be unaffected. It will therefore be possible to move the drone along a wall maintaining a fixed distance from it, with useful applications in isometric imaging or the use of drones for inspection.
This paper addresses the problem of multiple Fault Detection and Isolation (FDI) in DC-DC Buck converters which are widely used in renewable energy systems. Under non-ideal conditions and the assumption that the model parameters uncertainties are bounded, set-membership FDI methodology is proposed. The approach relies on an interval predictor developed in [1] for Linear Parameter Varying (LPV) systems. This interval predictor is used in this work and applied to the proposed LPV form of a DC-DC Buck converter in order to detect and isolate multiple faults under noisy environment. A novel signal is proposed to ensure the purpose. The efficiency of the proposed methodology is illustrated through simulation results.
In this work, an architecture of low complexity non-linear Decision Feedback Equalizers is proposed, where the parallel filters of the feed-forward section are hardware-efficient structures based on Iterated Short Convolution. For the design of the parallel filters an algorithm is proposed, which provides an architecture with regularity that is more suitable for FPGA implementation. The proposed architecture achieves the typical throughput of 10 Gb/s, while its balanced design allows the implementation on smaller FPGA devices while reaching the target throughput.
This paper investigates two control approaches to stabilize MVDC microgrids under large perturbations. The control approaches compared here are a 2 Degree of Freedom (2DoF) linear control and a synergetic control for voltage stability of DC microgrids, where loads and generators are interfaced through power electronic converters. The stabilizing control of the bus voltage resides in the converters on the generation side. The stability is challenged by Constant Power Loads (CPLs) that are tightly regulated within their control bandwidth exhibiting incremental negative impedance characteristic. In the scenario of a microgrid the two control approaches are compared in their centralized and decentralized formulations.
The provision of Quality of Service (QoS) may be regarded as value-added service in Machine-to-Machine (M2M) communications. QoS control is mandatory for mission-critical applications. In this paper, we study third party control on M2M connections which allows external applications to dynamically change available QoS. Models of application session with requested QoS are presented considering advanced policy and charging functionality in 4G networks. The formal description of the models and the concept of bisimilarity allow to be proved that the models express equivalent behavior.
In this paper we describe an approach for robot activity adaptation in a cognitive human-robot collaboration system, based on user-related information. Core element is a Bayesian Network model, which is the basis for reasoning about the risk of a user working in a collaborative task with a partially autonomous robot in a shared workspace. For local and global inference, the probabilistic model thereby combines scene information on situation and activity classes of different body parts and the whole user. All compiled information about the user thereby relies on the predictions from the real-time human body posture tracking. In order to improve the quality and reliability of the risk estimation we therefore maintain a locally-resolved posture estimation quality model and inject it into early stages of the inference process. For the activity adaptation we employ an optimization based dynamic path planning approach, which processes the spatially resolved inferences from the Bayesian Network in order to find robot motions which are optimal for the current situation in the shared workspace.
This paper presents an experimental comparative study on the performance of three different control strategies based on model predictive torque control for mono inverter dual Permanent Magnet Synchronous Machine (PMSM) system. The first control strategy use averaged sensor information of both machines. While the second control strategy uses master/slave which takes only the machine with higher load torque into account at each instant. In the third control strategy, both machine are considered identically by using algebraic sum of cost function. The comparison is made based on five different performance indicator including integration squared error, joule loss, switching loss, total harmonic distortion and total power efficiency.
An environment-motivated real-time dynamic optimized bandwidth allocation algorithm for teleoperation of collaborative robots is presented in this paper. The proposed method is a progression of the work in [1] in which Interesting Events (IEs) occurring in the robotic swarm's environment and the change in the swarm's Quality of Collaboration (QoC) are utilized to solve the bandwidth management optimization problem. The importance of this work is that it captures the dynamics of the robotic swarm's surrounding environment in real-time, and uses it as an input to a Fuzzy Interference System (FIS) which continuously updates a weight matrix `M' reflecting the importance of each IE and the change in QoC in the bandwidth allocation problem. Therefore, the human judgment used to setup M was replaced by an autonomous fuzzy expert system.
This paper presents a method of implementing a large virtual capacitor using an area-efficient capacitance multiplier circuit. The multiplier solves the major issue of large area consumption in integrated circuits needing high capacitance values. The proposed architecture improves other important parameters, such as the quality factor and the operating signal range. An analytical equivalent model is derived. The circuit is completely characterized in terms of model parameters and voltage and frequency operating ranges. Simulations are run to confirm feasibility and performance. An experimental version is implemented using discrete devices. A comparison between the theoretical, simulated, and experimental results is made.
This paper presents a 2d finite-element analysis for a 33-kV, three-phase, three-core cross-linked polyethylene (XLPE) underground cable (UGC) straight joint of the heat shrink type. The aim of this work is to show how the joint design parameters and different defects affect the electric field distribution, and find optimum material properties to enhance the lifetime of cable joints. This is investigated by calculating the electric field distributions and showing how the optimized selection of joint material properties can reduce the localized high electric field to avoid partial discharge activities. Several design parameters are investigated such as insulation layer's thickness and relative permittivity, and termination angles of ferrule and its insulation. In addition, size and location of different defects such as air voids, water droplets, sharp tips and delamination are examined. The paper concludes important points for proper design of medium-voltage (MV) cable joints to enhance their lifetime and hence increase the reliability of such cable systems.
In this paper we present a methodology to measure the energy consumption of software. The methodology is based on detailed monitoring of power usage of hardware components. We explain our lab setup after which we apply the methodology to different pieces of DNS resolver software. Through this case study we demonstrate some of the uses of our methodology, as it can be used to determine which software performs the tasks at hand in the most energy efficient way, what the influence of software configuration can be, etcetera.
WLAN offloading has been identified as a novel solution to leverage the channel capacity crunch over the cellular networks. However, this solution does not consider the congestion states of the target access network and the method of selecting the best access for offloading. To assist the User Equipment(UE) with the discovery and selection of candidate access network for offloading, 3GPP in Release 10 introduce the Access Network Discovery and Selection Function (ANDSF), which contains preconfigured intersystem mobility and routing policies that can guide the UE to discover and select available access network for handover. The current ANDSF however, cannot make discovery and selection policies which reflect the current state of the available access networks. This can lead to the selection of unavailable or inappropriate access network for offloading. In this paper, we propose a scheme which incorporates a Network Event Reporting Function (NERF) at access network level, and enhancements to the ANDSF. The scheme obtains dynamic characteristics of the access networks, which are used as input to a Multi attribute decision making (MADM) module in the ANDSF to update the statically configured mobility and routing policies provided to the UE for access selection. The scheme provides the best access network for data offloading.
