This document describes a self-tuning fuzzy controller designed for load frequency control (LFC) in a multi-machine power system. Conventional PID gains are first obtained using ant colony system optimization. These gains are then used to design fuzzy controller gains to solve the LFC problem under different loading conditions and non-linearities like generation rate constraints. The proposed self-tuning fuzzy controller is tested on a practical thermal and hydel power system and shown to perform better than conventional integral and ACS-PID controllers in dealing with system uncertainties and changing operating conditions.
Non-integer IMC Based PID Design for Load Frequency Control of Power System t...IJECEIAES
This paper deals with non-integer internal model control (FIMC) based proportional- integral-derivative(PID) design for load frequency control (LFC) of single area nonreheated thermal power system under parameter divergence and random load disturbance. Firstly, a fractional second order plus dead time(SOPDT) reduced system model is obtained using genetic algorithm through step error minimization. Secondly, a FIMC based PID controller is designed for single area power system based on reduced system model. Proposed controller is equipped with single area non-reheated thermal power system. The resulting controller is tested using MATLAB/SIMULINK under various conditions. The simulation results show that the controller can accommodate system parameter uncertainty and load disturbance. Further, simulation shows that it maintains robust performance as well as minimizes the effect of load fluctuations on frequency deviation. Finally, the proposed method applied to two area power system to show the effectiveness.
Performance Analysis of Direct Torque Controlled BLDC motor using Fuzzy LogicIAES-IJPEDS
The Brushless DC motor (BLDC) control is used in many of the applications
as it is small in size and with low power which can drive in high speed and
lighter compared to other motors.The electric vehicles are built with BLDC
motors and also in ships, aerospace etc., The control of BLDC motors is done
with sensors like hall effect sensor for sensing the positions. The speed
control can be done with normal PI and PID controllers. Direct torque control
(DTC) of the BLDC motor is important in many applications. In this paper
BLDC motor is controlled with DTC using PI, PID and Fuzzy logic control.
The comparison of the performance of the motor is analyzed with the Matlab
simulation software.
DESIGN OF FAST TRANSIENT RESPONSE, LOW DROPOUT REGULATOR WITH ENHANCED STEADY...ijcsitcejournal
Design and implementation of control systems for power supplies require the use of efficient techniques that
provide simple and practical solutions in order to fulfill the performance requirements at an acceptable cost.
Application of manual methods of system identification in determining optimal values of controller settings is
quite time-consuming, expensive and, sometimes, may be impossible to practically carry out. This paper
describes an analytical method for the design of a control system for a fast transient response, low dropout
(LDO) linear regulated power supply on the basis of PID compensation. The controller parameters are
obtained from analytical model of the regulator circuit. Test results showed good dynamic characteristics
with adequate margin of stability. This study shows that PID parameter values sufficiently close to optimum
can easily be obtained from analytical study of the regulator system. The applied method of determining
controller settings greatly reduces design time and cost.
Non-integer IMC Based PID Design for Load Frequency Control of Power System t...IJECEIAES
This paper deals with non-integer internal model control (FIMC) based proportional- integral-derivative(PID) design for load frequency control (LFC) of single area nonreheated thermal power system under parameter divergence and random load disturbance. Firstly, a fractional second order plus dead time(SOPDT) reduced system model is obtained using genetic algorithm through step error minimization. Secondly, a FIMC based PID controller is designed for single area power system based on reduced system model. Proposed controller is equipped with single area non-reheated thermal power system. The resulting controller is tested using MATLAB/SIMULINK under various conditions. The simulation results show that the controller can accommodate system parameter uncertainty and load disturbance. Further, simulation shows that it maintains robust performance as well as minimizes the effect of load fluctuations on frequency deviation. Finally, the proposed method applied to two area power system to show the effectiveness.
Performance Analysis of Direct Torque Controlled BLDC motor using Fuzzy LogicIAES-IJPEDS
The Brushless DC motor (BLDC) control is used in many of the applications
as it is small in size and with low power which can drive in high speed and
lighter compared to other motors.The electric vehicles are built with BLDC
motors and also in ships, aerospace etc., The control of BLDC motors is done
with sensors like hall effect sensor for sensing the positions. The speed
control can be done with normal PI and PID controllers. Direct torque control
(DTC) of the BLDC motor is important in many applications. In this paper
BLDC motor is controlled with DTC using PI, PID and Fuzzy logic control.
The comparison of the performance of the motor is analyzed with the Matlab
simulation software.
DESIGN OF FAST TRANSIENT RESPONSE, LOW DROPOUT REGULATOR WITH ENHANCED STEADY...ijcsitcejournal
Design and implementation of control systems for power supplies require the use of efficient techniques that
provide simple and practical solutions in order to fulfill the performance requirements at an acceptable cost.
Application of manual methods of system identification in determining optimal values of controller settings is
quite time-consuming, expensive and, sometimes, may be impossible to practically carry out. This paper
describes an analytical method for the design of a control system for a fast transient response, low dropout
(LDO) linear regulated power supply on the basis of PID compensation. The controller parameters are
obtained from analytical model of the regulator circuit. Test results showed good dynamic characteristics
with adequate margin of stability. This study shows that PID parameter values sufficiently close to optimum
can easily be obtained from analytical study of the regulator system. The applied method of determining
controller settings greatly reduces design time and cost.
In recent years, applications of facts systems have been developed for the compensation of active and reactive power. Facts systems are electronics devices that are connected to the wind farm. This paper presents the impacts of some of these devices on the stability of a wind farm, especially D-STATCOM, Static Var Compensator and Fuzzy SVC controller. First, a presentation of D-STATCOM, SVC, then fuzzy logic controller. In simulation study, the D-STATCOM ensures the stability of the voltage and current at the point of connection with the electrical grid. Finally, Comparing the SVC to the F-SVC simulations, we notice that the F-SVC is more performed than SVC for the compensation of the active and reactive power.
Parallel control structure scheme for load frequency controller design using ...IJECEIAES
This paper presents load frequency controller design for a single area as well as the multi-area thermal power system using direct synthesis approach with parallel control structure (PCS) scheme. The set-point and load frequency controller has been designed for frequency regulation and maintains tie-line power within a pre-specified limit for LFC power system. The proposed controller has been implemented for single-area, two-area, and four-area thermal power system for frequency regulation. The proposed method shows impressive simulation results compared with existed control method. The robustness of the proposed method has been examined with the help maximum sensitivity and parametric variation in the nominal power system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This paper presents an analysis by which the dynamic performances of a permanent magnet
brushless dc (PMBLDC) motor drive with different speed controllers can be successfully predicted. The
control structure of the proposed drive system is described. The dynamics of the drive system with a
classical proportional-integral-derivative (PID) and Fuzzy-Logic (FL) speed controllers are presented.
The simulation results for different parameters and operation modes of the drive system are investigated
and compared. The results with FL speed controller show improvement in transient response of the
PMBLDC drive over conventional PID controller. Moreover, useful conclusions stemmed from such a
study which is thought of good use and valuable for users of these controllers
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Efficient reconfigurable architecture of baseband demodulator in sdreSAT Journals
Abstract This paper presents the simulation architecture and performance analysis with the use of ZCD technic. A Zero-Crossing based All-Digital Baseband Demodulation architecture is proposed in this work. This architecture supports demodulation of all modulation schemes including MSK, PSK, FSK, and QAM. The proposed structure is very low area, low power, and low latency and can operate in real-time. Moreover it can switch, in run-time, between multiple modulation schemes like GMSK (GSM), QPSK (CDMA), GFSK (Bluetooth), 8-PSK (EDGE), Offset-QPSK (W-CDMA), etc. In addition, the phase resolution of the demodulator is scalable with performance. In addition, bit-wise amplitude quantization based quad-decomposition approach is utilized to demodulate higher order M-ary QAM modulations such as 16-QAM & 64-QAM, which is also a highly scalable architecture. This structure of demodulator provides energy-efficient and resource-efficient implementation of various wireless standards in physical layer of SDR. Keywords — Physical layer, Mobile and Wireless Communication, Software Defined radio (SDR), Zero Cross Detection (ZCD), Modulation Schemes, Architecture, high level synthesis, FPGA.
Design of Fuzzy Logic Controller for Speed Regulation of BLDC motor using MATLABijsrd.com
Brushless DC (BLDC) motors drives are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. The design and development of a BLDC motor drive for commercial applications is presented. The aim of paper is to design a simulation model of inverter fed PMBLDC motor with Fuzzy logic controller. Fuzzy logic controller is developed using fuzzy logic tool box which is available in Matlab. FIS editor used to create .FIS file which contains the Fuzzy Logic Membership function and Rule base. And membership functions of desired output. After creating .FIS file it is implemented in the Matlab Simulink. And the BLDC motor is run satisfactorily using the Fuzzy logic controller.
In recent years, applications of facts systems have been developed for the compensation of active and reactive power. Facts systems are electronics devices that are connected to the wind farm. This paper presents the impacts of some of these devices on the stability of a wind farm, especially D-STATCOM, Static Var Compensator and Fuzzy SVC controller. First, a presentation of D-STATCOM, SVC, then fuzzy logic controller. In simulation study, the D-STATCOM ensures the stability of the voltage and current at the point of connection with the electrical grid. Finally, Comparing the SVC to the F-SVC simulations, we notice that the F-SVC is more performed than SVC for the compensation of the active and reactive power.
Parallel control structure scheme for load frequency controller design using ...IJECEIAES
This paper presents load frequency controller design for a single area as well as the multi-area thermal power system using direct synthesis approach with parallel control structure (PCS) scheme. The set-point and load frequency controller has been designed for frequency regulation and maintains tie-line power within a pre-specified limit for LFC power system. The proposed controller has been implemented for single-area, two-area, and four-area thermal power system for frequency regulation. The proposed method shows impressive simulation results compared with existed control method. The robustness of the proposed method has been examined with the help maximum sensitivity and parametric variation in the nominal power system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This paper presents an analysis by which the dynamic performances of a permanent magnet
brushless dc (PMBLDC) motor drive with different speed controllers can be successfully predicted. The
control structure of the proposed drive system is described. The dynamics of the drive system with a
classical proportional-integral-derivative (PID) and Fuzzy-Logic (FL) speed controllers are presented.
The simulation results for different parameters and operation modes of the drive system are investigated
and compared. The results with FL speed controller show improvement in transient response of the
PMBLDC drive over conventional PID controller. Moreover, useful conclusions stemmed from such a
study which is thought of good use and valuable for users of these controllers
Automatic Generation Control of Multi-Area Power System with Generating Rate ...IJAPEJOURNAL
In a large inter-connected system, large and small generating stations are synchronously connected and hence all stations must have the same frequency. The system frequency deviation is the sensitive indicator of real power imbalance. The main objectives of AGC are to maintain constant frequency and tie-line errors with in prescribed limit. This paper presents two new approaches for Automatic Generation Control using i) combined Fuzzy Logic and Artificial Neural Network Controller (FLANNC) and ii) Hybrid Neuro Fuzzy Controller (HNFC) with gauss membership functions. The simulation model is created for four-area interconnected power system. In this four area system, three areas consist of steam turbines and one area consists of hydro turbine. The components of ACE, frequency deviation (F) and tie line error (Ptie) are obtained through simulation model and used to produce the required control action to achieve AGC using i) FLANNC and ii) HNFC with gauss membership functions. The simulation results show that the proposed controllers overcome the drawbacks associated with conventional integral controller, Fuzzy Logic Controller (FLC), Artificial Neural Network controller (ANNC) and HNFC with gbell membership functionsv
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Efficient reconfigurable architecture of baseband demodulator in sdreSAT Journals
Abstract This paper presents the simulation architecture and performance analysis with the use of ZCD technic. A Zero-Crossing based All-Digital Baseband Demodulation architecture is proposed in this work. This architecture supports demodulation of all modulation schemes including MSK, PSK, FSK, and QAM. The proposed structure is very low area, low power, and low latency and can operate in real-time. Moreover it can switch, in run-time, between multiple modulation schemes like GMSK (GSM), QPSK (CDMA), GFSK (Bluetooth), 8-PSK (EDGE), Offset-QPSK (W-CDMA), etc. In addition, the phase resolution of the demodulator is scalable with performance. In addition, bit-wise amplitude quantization based quad-decomposition approach is utilized to demodulate higher order M-ary QAM modulations such as 16-QAM & 64-QAM, which is also a highly scalable architecture. This structure of demodulator provides energy-efficient and resource-efficient implementation of various wireless standards in physical layer of SDR. Keywords — Physical layer, Mobile and Wireless Communication, Software Defined radio (SDR), Zero Cross Detection (ZCD), Modulation Schemes, Architecture, high level synthesis, FPGA.
Design of Fuzzy Logic Controller for Speed Regulation of BLDC motor using MATLABijsrd.com
Brushless DC (BLDC) motors drives are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. The design and development of a BLDC motor drive for commercial applications is presented. The aim of paper is to design a simulation model of inverter fed PMBLDC motor with Fuzzy logic controller. Fuzzy logic controller is developed using fuzzy logic tool box which is available in Matlab. FIS editor used to create .FIS file which contains the Fuzzy Logic Membership function and Rule base. And membership functions of desired output. After creating .FIS file it is implemented in the Matlab Simulink. And the BLDC motor is run satisfactorily using the Fuzzy logic controller.
Deregulated Load Frequency Control (DLFC) plays an important role in power systems. The main aim of
DLFC is to minimize the deviation in area frequency and tie-line power changes. Conventional PID
controller gains are optimally tuned at one operating condition. The main problem of this controller is that
it fails to operate under different dynamic operating conditions. To overcome that drawback, fuzzy
controllers have very much importance. The design of Fuzzy controller’s mostly depends on the
Membership Functions (MF) and rule-base over the input and output ranges controllers. Many methods
were proposed to generate and minimize the fuzzy rules-base. The present paper proposes an optimal fuzzy
rule base based on Principal component analysis and the designed controller is tested on three area
deregulated interconnected thermal power system. The efficacies of the proposed controller are compared
with the Fuzzy C-Means controller and Conventional PID controller.
Load frequency control in co ordination with frequency controllable hvdc link...eSAT Journals
Abstract
In this paper decentralized load frequency control (LFC) for suppression of oscillations in multi-area power systems using fuzzy logic
controller was studied. A three area system is considered in which areas 1 and 2 and areas 1 and 3 are connected by HVDC
transmission links and areas 2 and 3 are connected by normal AC tie-line. The performance of the fuzzy logic controller is compared
with the conventional PI controller and the simulation results shows that fuzzy logic controller is very effective enhancing better
damping performance in non-linear conditions.
Keywords: Load Frequency Control, High Voltage Direct Current transmission Link, Proportional Integral Controller,
Fuzzy Logic Control.
Load Frequency Control of Two Area SystemManash Deka
This is a synopsis presentation on a project of designing and analyzing Load Frequency Control (LFC) of a two area system. This is useful for students, basically of Electrical Engineering branch. This project will be simulated in simulink of MATLAB.
Study of PID Controllers to Load Frequency Control Systems with Various Turbi...IJERA Editor
This paper studies the load frequency control problem for various systems under various controller design
methods. Frequency should remain nearly constant for satisfactory operation of a power system because
frequency deviations can directly impact on a power system operation, system stability, reliability and
efficiency. A Load Frequency Control (LFC) scheme basically incorporates an appropriate control system for an
interconnected power system, which is having the capability to bring the frequencies of system to original set
point values or very nearer to set point values effectively after any load change. This can be achieved by the use
of conventional and modern controllers. In this proposed paper PID controller has been applied for LFC power
systems. The parameters of the PID controller are tuned by different methods names as Ziegler-Nichols (Z-N)
Method, and IMC method for better results. We use various tuning formulae in Z-N method and certain model
approximation methods and the responses of LFC with model approximation are studied. It is seen that the
results obtained are as good as the conventional controller.
Tuning PID Controller Parameters for Load Frequency Control Considering Syste...IJERA Editor
In this paper, parameters of PID controller and bias coefficient for Load Frequency Control (LFC) are designed using a new approach. In the proposed method, the power system uncertainties and nonlinear limitations of governors and turbines ,i.e. Valve Speed Limit (VSL)and Generation Rate Constraint (GRC), are taken into account in designing. Variations of uncertain parameters are considered between -40% and +40% of nominal values with 5% step .In order to design the proposed PID controller ,a new objective function is defined. MATLAB codes are developed for GA based PID controller tuning, the results of which are used to study the system step response. All these are through in Simulink based background.
This work shows the design and tuning procedure of a discrete PID controller for regulating buck boost converter circuits. The buck boost converter model is implemented using Simscape Matlab library without having to derive a complex mathematical model. A new tuning process of digital PID controllers based on identification data has been proposed. Simulation results are introduced to examine the potentials of the designed controller in power electronic applications and validate the capability and stability of the controller under supply and load perturbations. Despite controller linearity, the new approach has proved to be successful even with highly nonlinear systems. The proposed controller has succeeded in rejecting all the disturbances effectively and maintaining a constant output voltage from the regulator.
Correlative Study on the Modeling and Control of Boost Converter using Advanc...IJSRD
DC-DC converters are switched power converters. The converters are most widely used in research and industrial applications. The DC-DC Boost Converters are used to step-up the supply voltage given to the plant model. The main advantage of using the Boost Converters is that it works in the low voltage according to the design specifications. In order to regulate the uncontrolled supply of voltage, a controller has to be designed and modeled to stabilize the output voltage. Since the convectional controllers cannot work under dynamic operating conditions, advanced controllers are to be designed to overcome the problems. In this article, the advanced controllers such as NARMA-L2, Fuzzy Logic (FLC) and Sliding Mode Controllers (SMC) are implemented and their responses are compared using MATLAB.
The Proportional-Integral-Derivative (PID) controller is the most popular control strategy in the process industry. The popularity can be attributed to its simplicity, better control performance and excellent robustness to uncertainties that is found through the research work on such controllers so far. This paper presents the design and tuning of a PID controller using Fuzzy logic for industrial induction heating systems with LLC voltage source inverter for controlling the induction heating power. The paper also compares the performance of the Fuzzy PID controller with that of a conventional PID controller for the same system. The system and the controllers are simulated in MATLAB/SIMULINK. The results show the effectiveness and superiority of the proposed Fuzzy PID controller.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Iaetsd design of fuzzy self-tuned load frequency controller for power system
1. DESIGN OF FUZZY SELF-TUNED LOAD FREQUENCY CONTROLLER FOR POWER SYSTEM
T.A.S.JAGADEESH Dr.R.VIJAYA SHANTI, Asst.Professor, Andhra University
Abstract: In the present paper, Self-Tuning fuzzy Controller is
designed for a multi-machine power system. Conventional PID
gains are obtained using Ant Colony System (ACS).Basing these
gains, Fuzzy Controller gains are designed for solving Load
Frequency Control (LFC) problem in a power system. The proposed
controller is tested on different loading conditions of a practical
thermal, hydel interconnected systems. The proposed controller
shows its efficiency when compared with conventional integral
controller & ACS-PID controller under different non-linearity’s like
Generation Rate Constraint (GRC).
Key words:
Load Frequency Control; Self-Tuning fuzzy Controller,
Generation Rate Constraints.
1. Introduction:
The problem of controlling the power output of a generator of a
closely knit electric area so as to maintain the scheduled frequency.
All the generators in such an area constitute a coherent group. So
that all the generators will speed up and slow down together
maintaining their relative power angles. Such an area is identified as
a control area. The boundaries of a control area will generally
coincide with that of an individual Electric Board Company [1].
These perturbations disturb the normal operation of the power
system. A very well known PI/PID controller are used after many
investigations and these controllers are used over half a centuries in
the industrial control and automation process. The PI/PID
controllers are simple for implementation [2, 3], design and low cost
for linear systems. Whenever an operating condition change, the
PID controller which is based on linearized model parameters will
also vary the PID controller gains which are designed at operating
conditions gives an optimal response at one operating condition
gives a suboptimal response at other operating condition. And
another drawback of PID controllers is human control of an
experienced operator is essential.So,in order to overcome these
drawbacks and to get some optimal response at all operating
conditions self tuning of PID controllers using Fuzzy logic
controllers come into action. Zeigler Nicolas method the most
widely used tuning method and is very simple but it is not
guaranteed one which will gives an effective response due to the
changes that may happen during the process running time of the
operating conditions. So, in recent years, Fuzzy logic controllers and
fuzzy sets tools are used for designing of fuzzy self tuning of PID
gains. This controller is used to update the PID controller gains pK
IK DK to meet closed loop system performance.
Several control techniques based on Fuzzy and Takagi-Sugeno
(TS) Fuzzy control system theory have been applied to LFC and
Power system as a tool to improve the system performance [8, 9]
The different loading conditions which we applied to self tuned
fuzzy logic controllers in the presence of system non-linearity GRC
&uncertain parameters are taken from the Egyptian power system
load frequency control during summer and winter of 2008[12] and
the gains of pK IK DK of the system can be self-tuned on-line
using output of the system and the simulated results are designed in
the MATLAB/SIMULINK are observed on comparison of proposed
fuzzy self tuned-PID & ACS-PID controller.
2. The Conventional Integral & PID System Modeling.
Assumptions are considered for Power system installed generation
capacity and peak load are estimated as 23400MW and 18970MW,
in 2008[12].The Approximated installed capacity of Non-reheat,
Reheat, and Hydro electric Power stations are given as.
1. Non-reheat generating units represent by gas turbine Power
stations represents approximately 25% of the installed capacity.
2. Reheat generating Units represent by the majority of the thermal
stations and combined cycle Power stations which are approximated
as 63% of the installed capacity.
3. Hydro electric Power stations are approximated as 15% of
installed capacity.
Fig (1) shows the block diagram of the Power system LFC model is
represented by SIMULINK is given below.
The Parameters of this model are divided into two sets. The first set
of parameters does not depend on system operating conditions. The
other set of parameters varies with the time according to the
operating condition. The data required to calculate the changing
parameters are concerned with the data of each generator including
status (ON or OFF),type of unit (Non-reheat,reheat,hydro),unit
rating (MW),unit Output (MW) for the operating condition under
study, inertia of the unit, and spinning reserve of the unit in
percentage of the unit rating.
The simulink model considers the generating rate constraints GRC
for different units. The applied values for GRC are 0.1P.UMW/min
and 0.2p.uMW/min. for the reheat turbines and non reheat turbines,
respectively. The GRC of hydro plants is neglected since its actual
value is much greater corresponding to the time durations of
practical disturbances [2].
The dynamic equations of this model can be written in the state-
space form as:
( ) ( ) ( )x t Ax t Bu t= +& (1)
Where
1 2 2 3( ) [ ( ) ( ) ( ) ( )]x t F t P t P t V P G t t= ∆ ∆ ∆ ∆ ∆ ∆
( )F t∆ = 1( )x t = the incremental frequency deviation Hz
1( )P t∆ = 2 ( )x t = incremental change in non-reheat plant in p.u
MW.
2()P t∆ = 3()x t = incremental changes reheat plant output in p.u
MW.
2V∆ = 4()x t = incremental opening in steam valve of reheat
plant output in p.u MW
3( )P t∆ = 5( )x t = incremental change in hydro plant output in p.u
MW
()Gt∆ = 6( )x t = incremental opening in hydro plant inlet vane in
p.u MW
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2. The system model matrices A & B are displayed in the Appendix.
The three loading conditions of Power system are considered to
design ACS-based PI and PID gains.
3. Design of Fuzzy self-tuning of PID controller.
The Proposed design procedure includes two steps:
1. Finding the optimal gains of PID which Controls the system.
2. Design of fuzzy logic control (FLC), with self-tuning capabilities.
3. General Expressions for PID controller
The of a PI controller is given below:
( ) I
p D
K
K s K K s
s
= + + (2)
Where pK IK and DK are proportional, integral and differential
gains respectively.
( ) ( )*U s K s F= − ∆ (3)
Where ( )U s =output and, F∆ is the incremental frequency
deviation.
4. Design of a Controller
The below Fig(1) shows the Two input and one output variables of
conventional fuzzy logic system
X1
Y
Y
X2
Fig (1) Fuzzy Logic system
The Fig (2) shows below the Fuzzy logic controller with various
control schemes
Fig (2) A fuzzy controller with control system structure
The below Fig (3) shows Designed Fuzzy self tuned PID controller
The designs steps of fuzzy self tuning can be summarized as
follows:
1-Write the PID controller by the following equation:
( )
( )p I D
de t
U K K e t dt K
dt
= + +∫ (4)
This equation can also be written as:
2 2 2
( )
( )P I D
de t
U K K e t dt K
dt
= + ∫ +
(5)
Where:
2pK = PK * 1PK , 2IK = IK * 1IK , 2DK = DK * 1DK are the gain
outputs from fuzzy controller.
The input member ship functions of e and ∆e as shown in the fig (4,
5, 6) and are represented in the rule base are:
{ PB-Positive Big, PM-Positive Medium, PS-Positive Small, Z-
Zero, NB-Negative Big, NM-Negative Medium, NS-Negative
Small} and the outputs are represented in rule base as {B-Big, VB-
Very Big, MB-Medium Big, S-Small, MS-Medium Small};
The output membership functions are:
ZE-Zero Error, MS-Medium Small, S-Small, M-Medium, B-Big,
MB-Medium Big, VB-Very Big
Where:
e : error input normalizing gain.
∆e : Change in error input
normalizing gains.
The rule base for KP1 is shown in the table below.
∆e
e NB NM NS ZE PS PM PB
NB VB VB VB VB VB VB VB
NM MB MB MB MB B MB VB
NS B B B B MB B VB
ZE ZE ZE ZE MS S S S
PS B B B B MB B VB
PM MB MB MB MB B MB VB
PB VB VB VB VB VB VB VB
Fig (4) Rule base for determining 1pK
Fuzzy Logic System
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3. ∆e
e
NB NM NS ZE PS PM PB
NB M M M M M M M
NM M M M M M M M
NS S S S S S S S
ZE MS MS MS ZE MS MS MS
PS S S S S S S S
PM M M M M M M M
PB M M M M M M M
Fig (5) Fuzzy rule base for 1IK
∆e
e
NB NM NS ZE PS
PM
PB
NB ZE MS S M MB B VB
NM MS S M B B B VB
NS S M B MB VB VB VB
ZE M B MB MB VB VB VB
PS MB MB VB VB VB VB VB
PM B MB VB VB VB VB VB
PB VB VB VB VB VB VB VB
Fig(6) Fuzzy rule base for determining 1DK
3) The universe of discourse is normalized, the physical values is of
the normalizing gains is obtained by dividing the boundary values of
discourse of the input member ship functions of maximum of
original values of e and ∆e.
4) Defuzzification is a mathematical process used to convert a fuzzy
sets to real number and is a necessary step because fuzzy sets
generated by fuzzy inference in rules must be somehow
mathematically combined to come up with one single number as
output of a fuzzy controller output. Defuzzification is applied as a
final step to convert the fuzzy output to crisp value .Defuzzification
is a process which converts the range of values of output variables
into corresponding universe of discourse and it yields a non fuzzy
control action from an inferred fuzzy control action. One of the
Defuzzification methods is centroid method it is also called as centre
of gravity or centre of area defuzzification .The widely used COA
strategy the centre of gravity of the possibility distribution of a
control action.
1
1
( )
( )
r
i i
i
r
i
i
x x
u
x
µ
µ
=
=
=
∑
∑
Where ix a running point in the universe of discourse, and ( )ixµ
is its membership value in the member ship function
Results and Discussions:
The results show that system is responding effectively for
variation of uncertain parameters in the presence of nonlinearity
Generation Rate Constraints. The self tuned fuzzy controller meets
the required results of uncertain parameters over ACS –PID &
conventional Integral controller.
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4. The following conditions are:
Case 1: Small disturbance in the system dP∆ =1%:-
In this a Small disturbance of 1% is applied to the power system
and can observed that the damping of the system frequency is
improved and simulation results shows that proposed FST-PID
controller has less overshoot & Quick settling time when compared
with Integral Controller and ACS-PID controller as shown in the
fig(7)and fig(8) below.
Fig(7) ∆F
∆U
Fig (8) System dynamic response for case (1)
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5. Case 2: Disturbance Variations:
Fig (8) and fig(9) , illustrates the dynamic response of frequency
deviation F∆ and control input U∆ when a step of dP∆ = 1%
is applied,
during 5 ≤ t ≤ 30 seconds. It is clear that the oscillations are quickly
damped with the proposed FST-PID as compared to ACS-PID.
Besides,
the FST-PID settles faster whereas ACS-PID shows the opposite.
Fig (9) ∆F
∆U
Fig (10) System dynamic response for case (2)
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6. Case 3: Tracking Disturbance Variations
Fig (9) and (10) show the dynamic response of F∆ and U∆
following a variation of as seen in Fig (12) and Fig (13). This
variation covers both tracking represented by the ramp and
regulation which represented by a step change. It is obvious from
Fig (12) and (13) that the system driven by FST-PID controller,
shows better performance and clearly improved than ACS- PID fast
response with relatively small overshoots).
a) Fig(12) ∆F
∆U
Fig(13) shows the system dynamic response
Operating conditions:
Condition1 Condition2 Condition3
H 4.9598 6.0168 5.8552
Pn1 0.2730 0.3112 0.2433
Pn2 0.7007 0.5200
0.6179
Pn3 0.1364 0.1798 0.1389
Where H: Equivalent Inertia constant of the system.
&
Pn1, Pn2, and Pn3: Nominal rated regulating power output
for non-reheat, reheat and
Hydro Plants (p.u MW)
List of symbols:
1) R1, R2 - 2.5(Hz/p.u MW)
2) R3 - (Hz/p.u MW)
3) D - 0.029(p.u MW/hz)
4) T1 & T2 –0.4Sec
5) T3 - 90sec
6) Tb -6sec
7) Td -5sec
8) wT -1.0sec
9) M - 0.5
10) LT - 2.5 sec/Hz
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7. Conclusion:
In this paper Self tuned FST-PID controller is designed and its
performances are compared with conventional Integral controller
&ACS-PID controller under different loading conditions. Simulation
results prove that the proposed controller shows the robust
performance with different non-linearity like GRC under dynamic
operating conditions. The simulation results shows that FST-PID
controllers is powerful in reducing the frequency deviations under a
variety of load perturbations of LFC for proposed power system.
The dynamic equations are:
A=
1
1 1 1
2
2 2 2
2
2 2 2
3
3
1 1 1
0 0
2 2 2 2
1
0 0 0 0
1 1
0 0 0
1
0 0 0 0
2 2 2 2 2 2
2 1 0
2 2 2 2
1
1 0
2 2 2 2
h h
d d d d
w w
d d d d
D
H H H H
Pn
R T T
mPn m
R T T T T
Pn
R T T
T D aT aT aT
a
H H H H T T T
T D aT aT aT
a
H H H H T
−
− −
− −
−
− −
− − − +
− − − − −
a=
3
3 3
Pn
R T
B=
3 31 2 2
1 2 2 3 3
2*
0
Pn PnPn mPn Pn
T T T T T
−− − −
Fig (14) The Simulink representation of a power system Load Frequency model
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8. References:
1) Modern Power system analysis by D.P.Kotari, I.J.Nagarath
‘Third edition’.
2) Design of a Fuzzy Self-Tuning Optimal PID Load
Frequency Controller for the Egyptian Power System.
3) C. E. Fosha, O. I. Elgerd, “The megawatt-frequency control
problem: a new approach via optimal control theory”, IEEE
Trans. PAS, vol. 89, pp. 563–567, April 1970.
4) A. Khodabakhshian, N. Golbon, “Unified PID design for
load frequency control”, In Proc. 2004 IEEE Int. Conf. on
Control Applications (CCA), Taipei, Taiwan, pp. 1627–
1632, September 2004.
5) G.J. Silva, A. Datta, et al., “New results on the synthesis of
PID controllers”, IEEE, Transactions on Automatic Control,
47(2), pp. 241-252, 2002.
6) Keven M. Passino and Stephen Yurkovich, "Fuzzy Control",
Addison Wesley longnan, Inc., 1998.
7) G.R. Chen and T.T. Pham, "Introduction to fuzzy sets, fuzzy
logic, fuzzy control system", RC. Press,Boac Raton, FL,
USA, 2000.
8) Michall Petrov, Ivan Ganchev and Ivan dragotinov, “Design
Aspects of Fuzzy PID Control”, International conference on
soft computing, Mendel “99”, Brno, Czech Republic, 9-12
June, pp. 277-282, 1999.
9) H. A. Shayanfar and H. Shayeghi A. Jalili, " Takagi-Sugeno
Fuzzy Parallel Distribution Compensation Based Three-Area
LFC Design", International Journal on Technical and
Physical Problems of Engineering, Issue 8, Volume 3,
Number 3, pp. 55-64, Sept 20.
10) R. Dhanalakshmi and S. Palaniswami, "Application of Self-
Tuning Fuzzy Logic PI Controller in Load Frequency
Control of Wind-Micro Hydro-Diesel Hybrid Power
System", European Journal of Scientific Research ISSN
1450-216X Vol. 79 No. 3, pp. 317-327, 2012.
11) Zareiegovar G., Sakhavati A. , Nabaei V. and Gharehpetian
G. B., " A New Approach for Tuning PID Controller
Parameters of Load Frequency Control Considering System
Uncertainties”, 9th International Conference on Digital
Object, pp. 333 – 336, 2008.
12) Egyptian Electricity Holding Company, 2007/2008 Annual
Report.
http://www.egelec.com/annual%20report/2007.html.
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