120 resultados para fuzzy logic power system stabilizer


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In this paper, we present the design and construction of a prototype target tracking system. The experimental set up consists of three main modules for moving the object, detecting the motion of the object and its tracking. The mechanism for moving the object includes an object and two stepper motors and their driving and control circuitry. The detection of the object’s motion is realized by photo switch array. The tracking mechanism consists of a laser beam and two DC servomotors and their associated circuitry. The control algorithm is a standard fuzzy logic controller. The system is designed to operate in two modes in such a way that the role of target and tracker can be interchanged. Experimental results indicate that the fuzzy controller is capable of controlling the system in both modes.

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Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

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Unmanned Aerial Vehicles (UAVs) industry is a fast growing sector. Nowadays, the market offers numerous possibilities for off-the-shelf UAVs such as quadrotors or fixed-wings. Until UAVs demonstrate advance capabilities such as autonomous collision avoidance they will be segregated and restricted to flight in controlled environments. This work presents a visual fuzzy servoing system for obstacle avoidance using UAVs. To accomplish this task we used the visual information from the front camera. Images are processed off-board and the result send to the Fuzzy Logic controller which then send commands to modify the orientation of the aircraft. Results from flight test are presented with a commercial off-the-shelf platform.

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Determining the optimal of black-start strategies is very important for speeding the restoration speed of a power system after a global blackout. Most existing black-start decision-making methods are based on the assumption that all indexes are independent of each other, and little attention has been paid to the group decision-making method which is more reliable. Given this background, the intuitionistic fuzzy set and further intuitionistic fuzzy Choquet integral operator are presented, and a black-start decision-making method based on this integral operator is presented. Compared to existing methods, the proposed algorithm cannot only deal with the relevance among the indexes, but also overcome some shortcomings of the existing methods. Finally, an example is used to demonstrate the proposed method. © 2012 The Institution of Engineering and Technology.

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The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

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Facing with the difficulty in information propagation and synthesizing from conceptual to embodiment design, this paper introduces a function-oriented, axiom based conceptual modeling scheme. Default logic reasoning is exploited for recognition and reconstitution of conceptual product geometric and topological information. The proposed product modeling system and reasoning approach testify a methodology of "structural variation design", which is verified in the implementation of a GPAL (Green Product All Life-cycle) CAD system. The GPAL system includes major enhancement modules of a mechanism layout sketching method based on fuzzy logic, a knowledge-based function-to-form mapping mechanism and conceptual form reconstitution paradigm based on default geometric reasoning. A mechanical hand design example shows a more than 20 times increase in design efficacy with these enhancement modules in the GPAL system on a general 3D CAD platform.

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“Hardware in the Loop” (HIL) testing is widely used in the automotive industry. The sophisticated electronic control units used for vehicle control are usually tested and evaluated using HIL-simulations. The HIL increases the degree of realistic testing of any system. Moreover, it helps in designing the structure and control of the system under test so that it works effectively in the situations that will be encountered in the system. Due to the size and the complexity of interaction within a power network, most research is based on pure simulation. To validate the performance of physical generator or protection system, most testing is constrained to very simple power network. This research, however, examines a method to test power system hardware within a complex virtual environment using the concept of the HIL. The HIL testing for electronic control units and power systems protection device can be easily performed at signal level. But performance of power systems equipments, such as distributed generation systems can not be evaluated at signal level using HIL testing. The HIL testing for power systems equipments is termed here as ‘Power Network in the Loop’ (PNIL). PNIL testing can only be performed at power level and requires a power amplifier that can amplify the simulation signal to the power level. A power network is divided in two parts. One part represents the Power Network Under Test (PNUT) and the other part represents the rest of the complex network. The complex network is simulated in real time simulator (RTS) while the PNUT is connected to the Voltage Source Converter (VSC) based power amplifier. Two way interaction between the simulator and amplifier is performed using analog to digital (A/D) and digital to analog (D/A) converters. The power amplifier amplifies the current or voltage signal of simulator to the power level and establishes the power level interaction between RTS and PNUT. In the first part of this thesis, design and control of a VSC based power amplifier that can amplify a broadband voltage signal is presented. A new Hybrid Discontinuous Control method is proposed for the amplifier. This amplifier can be used for several power systems applications. In the first part of the thesis, use of this amplifier in DSTATCOM and UPS applications are presented. In the later part of this thesis the solution of network in the loop testing with the help of this amplifier is reported. The experimental setup for PNIL testing is built in the laboratory of Queensland University of Technology and the feasibility of PNIL testing has been evaluated using the experimental studies. In the last section of this thesis a universal load with power regenerative capability is designed. This universal load is used to test the DG system using PNIL concepts. This thesis is composed of published/submitted papers that form the chapters in this dissertation. Each paper has been published or submitted during the period of candidature. Chapter 1 integrates all the papers to provide a coherent view of wide bandwidth switching amplifier and its used in different power systems applications specially for the solution of power systems testing using PNIL.

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This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

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This paper presents a high voltage pulsed power system based on low voltage switch-capacitor units connected to a current source for several applications such as plasma systems. A buck-boost converter topology is used to utilize the current source and a series of low voltage switch-capacitor units is connected to the current source in order to provide high voltage with high voltage stress (dv/dt) as demanded by loads. This pulsed power converter is flexible in terms of energy control, in that the stored energy in the current source can be adjusted by changing the current magnitude to significantly improve the efficiency of various systems with different requirements. Output voltage magnitude and stress (dv/dt) can be controlled by a proper selection of components and control algorithm to turn on and off switching devices.

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This paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.

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This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

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This chapter looks at issues of non-stationarity in determining when a transient has occurred and when it is possible to fit a linear model to a non-linear response. The first issue is associated with the detection of loss of damping of power system modes. When some control device such as an SVC fails, the operator needs to know whether the damping of key power system oscillation modes has deteriorated significantly. This question is posed here as an alarm detection problem rather than an identification problem to get a fast detection of a change. The second issue concerns when a significant disturbance has occurred and the operator is seeking to characterize the system oscillation. The disturbance initially is large giving a nonlinear response; this then decays and can then be smaller than the noise level ofnormal customer load changes. The difficulty is one of determining when a linear response can be reliably identified between the non-linear phase and the large noise phase of thesignal. The solution proposed in this chapter uses “Time-Frequency” analysis tools to assistthe extraction of the linear model.