2,131 research outputs found

    Using Particle Swarm Optimization for Power System Stabilizer and energy storage in the SMIB system under load shedding conditions

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    Generator instability, which manifests as oscillations in frequency and rotor angle, is brought on by sudden disruptions in the power supply. Power System Stabilizer (PSS) and Energy Storage are additional controllers that enhance generator stability. Energy storage types include superconducting magnetic (SMES) and capacitive (CES) storage. If the correct settings are employed, PSS, SMES, and CES coordination can boost system performance. It is necessary to use accurate and effective PSS, SMES, and CES tuning techniques. Artificial intelligence techniques can replace traditional trial-and-error tuning techniques and assist in adjusting controller parameters. According to this study, the PSS, SMES, and CES parameters can be optimized using a method based on particle swarm optimization (PSO). Based on the investigation's findings, PSO executes quick and accurate calculations in the fifth iteration with a fitness function value of 0.007813. The PSO aims to reduce the integral time absolute error (ITAE). With the addition of a load-shedding instance, the case study utilized the Single Machine Infinite Bus (SMIB) technology. The frequency response and rotor angle of the SMIB system are shown via time domain simulation. The analysis's findings demonstrate that the controller combination can offer stability, reducing overshoot oscillations and enabling quick settling times.

    Full Envelope Control of Nonlinear Plants with Parameter Uncertainty by Fuzzy Controller Scheduling

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    A full envelope controller synthesis technique is developed for multiple-input single-output (MISO) nonlinear systems with structured parameter uncertainty. The technique maximizes the controller\u27s valid region of operation, while guaranteeing pre-specified transient performance. The resulting controller does not require on-line adaptation, estimation, prediction or model identification. Fuzzy Logic (FL) is used to smoothly schedule independently designed point controllers over the operational envelope and parameter space of the system\u27s model. These point controllers are synthesized using techniques chosen by the designer, thus allowing an unprecedented amount of design freedom. By using established control theory for the point controllers, the resulting nonlinear dynamic controller is able to handle the dynamics of complex systems which can not otherwise be addressed by Fuzzy Logic Control. An analytical solution for parameters describing the membership functions allows the optimization to yield the location of point designs: both quantifying the controller\u27s coverage, and eliminating the need of extensive hand tuning of these parameters. The net result is a decrease in the number of point designs required. Geometric primitives used in the solution all have multi-dimensional interpretations (convex hull, ellipsoid, Voronoi-Delaunay diagrams) which allow for scheduling on n-dimensions, including uncertainty due to nonlinearities and parameter variation. Since many multiple-input multiple-output (MIMO) controller design techniques are accomplished by solving several MISO problems, this work bridges the gap to full envelope control of MIMO nonlinear systems with parameter variation

    Synthesis of Hybrid Fuzzy Logic Law for Stable Control of Magnetic Levitation System

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    In this paper, we present a method to design a hybrid fuzzy logic controller (FLC) for a magnetic levitation system (MLS) based on the linear feedforward control method combined with FLC. MLS has many applications in industry, transportation, but the system is strongly nonlinear and unstable at equilibrium. The fast response linear control law ensures that the ball is kept at the desired point, but does not remain stable at that point in the presence of noise or deviation from the desired position. The controller that combines linear feedforward control and FLC is designed to ensure ball stability and increase the system's fast-response when deviating from equilibrium and improve control quality. Simulation results in the presence of noise show that the proposed control law has a fast and stable effect on external noise. The advantages of the proposed controller are shown through the comparison results with conventional PID and FLC control laws

    A novel continuation-based quasi-steady-state analysis approach to mitigate long-term voltage instability

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    A novel Continuation-based Quasi-Steady-State (CQSS) analysis is developed and integrated with trajectory sensitivity which in turn can be used to address various aspects of control strategies to mitigate long-term voltage collapse.;In this research, two scenarios are defined according to the severity of the contingency: Scenario One. The post-contingency long-term load characteristic intersects the system\u27s PV curve; Scenario Two . The post-contingency long-term load characteristic doesn\u27t intersect the system\u27s PV curve.;First, the CQSS simulation, which is based on two different parameterizations, is utilized to trace the system trajectory after the contingency. One is for Scenario One where load change and OLTC action are considered. The other is for Scenario Two where load restoration and OLTC action are taken into account simultaneously. Secondly, the identification of the saddle node bifurcation point (SNB) and singularity-induced bifurcation (SIB) point can be accomplished by either continuation parameter or trajectory sensitivity. A new approach is developed in the CQSS simulation to approximate the differential representation of the thermostatic load restoration. It also avoids the numerical problem around the singularity point.;The salient features of this research are listed below: (1) A new CQSS simulation is developed. (a) It is numerically well-conditioned. (b) It can readily identify the SIB point and the SNB point. (c) The time information of the controls can be obtained automatically. (d) Combined effects of the OLTCs and the load change on voltage stability are taken into account. (2) A computationally-fast approximation of the generic load restoration is developed. (a) Parameterization of the load exponent provides a new way to approximate the load restoration in the long-term time scale. (b) The change of load types and compositions with the time can be considered. (3) Trajectory sensitivity is derived and calculated in two ways. (a) It is applied to identify the long-term SNB point. (b) It is related to margin sensitivity by using continuation method. (c) It is used to formulate the control problem to maintain a sufficient stability margin. (4) A systematic and comprehensive control strategy to mitigate longterm voltage instability is developed and implemented.;This proposed methodology is tested on two systems

    Neural network based architectures for aerospace applications

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    A brief history of the field of neural networks research is given and some simple concepts are described. In addition, some neural network based avionics research and development programs are reviewed. The need for the United States Air Force and NASA to assume a leadership role in supporting this technology is stressed

    Workshop on Fuzzy Control Systems and Space Station Applications

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    The Workshop on Fuzzy Control Systems and Space Station Applications was held on 14-15 Nov. 1990. The workshop was co-sponsored by McDonnell Douglas Space Systems Company and NASA Ames Research Center. Proceedings of the workshop are presented

    A Fault Tolerant Control for Sensor and Actuator Failures of an Non Linear Hybrid System

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    We focused in this work on a fault tolerant control of a non linear hybrid system class based on diagnosis method (determine and locate the defects and their types) and on the faults reconfiguration method.In literature we can found many important research activities over the fault-tolerant control of non linear systems and linear Hybridsystems. But it dosen´t exist too many for the non linear hybridsystem.The main idea in this paper is to consider a new approach to improve the reconfiguration performance of the non linear hybrid system by using hammerstein method which is designed to works only for linear systems. This method compensated the effect of the faults and guarantees the closed-loop system stable. The proposed method is simulated with a hydraulic system of two tanks with 4 modes

    Analysis of Smart Parking System Using IOT Environment

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    The typical parking experience has been transformed by smart parking systems that use the Internet of Things (IoT) environment to integrate technology to improve efficiency, convenience, and sustainability. In order to monitor and manage parking spaces in real-time, this unique technique makes use of IoT devices, such as sensors, cameras, and networking technologies. As a result of the system's reliable information on parking availability, drivers may find and book parking spaces in advance, which eases traffic and reduces aggravation. Additionally, parking systems with IoT capabilities optimize resource use, lowering carbon emissions and fostering sustainability. The adoption of IoT in parking systems is a crucial step towards building smarter, more connected cities that will enhance both drivers' and parking operators' experiences with parking. There are numerous crucial elements in the process for developing a smart parking system in an IoT context. First, sensors are placed in parking places to gather up-to-the-minute occupancy information. Then, using wireless communication protocols, this data is sent to a central server or cloud computing platform. After that, a data processing and analysis module interprets the gathered data using algorithms and machine learning techniques and presents parking availability information to users via a mobile application or other user interfaces. For effective management and monitoring of parking spaces, the system also includes automated payment methods and interacts with existing infrastructure. Taken as Alternative parameters is Park Smart, Street line, Park Whiz, ParkMobile, Spot Hero. Taken as evaluation parameters is Light Sensor, CCTV coins, SMS, Cost-effectiveness, Timestamp. This demonstrates the rank of the data set Park Smart is on 1st Rank, ParkMobile is on 2nd Rank, Park Whiz is on 3rd Rank, Street line is on 4th Rank and Spot Hero is on 5th Rank. To sum up, implementing a smart parking system employing IoT technology has shown to be a potential way to deal with the problems associated with urban parking. The system increases parking efficiency, lessens traffic congestion, and enhances user experience by utilising IoT sensors, data analytics, and real-time communication. The parking scene in smart cities has the potential to change dramatically, enhancing ease and sustainability
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