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.
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL INTEGRATION FOR AERIAL REFUELING AUTOP...Ahmed Momtaz Hosny, PhD
This document summarizes research on integrating fuzzy logic control with linear quadratic regulator (LQR) control for an aerial refueling autopilot. It describes modeling an aircraft, applying LQR control alone and with fuzzy logic control integrated. The integrated LQR fuzzy control is shown to more effectively suppress uncertainties and minimize mission time compared to LQR alone. Key aspects covered include aircraft modeling, optimal LQR flight control, applying fuzzy inference systems, deriving fuzzy rules, and the integrated LQR fuzzy control structure applied to pitch and lateral control for aerial refueling simulations.
This document summarizes a research project on process identification using relay feedback tests. The project aims to identify low-order models like FOPDT and SOPDT from relay feedback data to enable performance assessment and controller tuning. A new identification method is proposed that uses neural networks to estimate the apparent deadtime from steady-state cycles. This deadtime and other parameters allow classification of the process model and parameter estimation for assessment and auto-tuning.
Analytical Evaluation of Generalized Predictive Control Algorithms Using a Fu...inventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
This document describes a new method for designing fractional-order proportional-integral-derivative (FOPID) controllers. It introduces approximating fractional-order differential operators using a biquadratic structure, which allows designing finite-order FOPID controllers with fewer parameters than existing designs. A systematic procedure is presented to design FOPID controllers to achieve desired phase and gain margins of controlled systems. The viability of the design method is verified with a numerical example.
Adaptive pi based on direct synthesis nishantNishant Parikh
This document describes an adaptive proportional-integral (PI) controller for a laboratory level control system. The system consists of two interconnected tanks where the level of the second tank is controlled. Due to changes in plant dynamics over time, an adaptive controller is used. The plant parameters are estimated online using recursive least squares estimation based on input and output signals. The estimated parameters are then used to calculate PI controller parameters to achieve the desired closed-loop response. Experimental results show the controller can maintain level control even after changes in plant dynamics without needing re-calibration.
Output feedback trajectory stabilization of the uncertainty DC servomechanism...ISA Interchange
This work proposes a solution for the output feedback trajectory-tracking problem in the case of an uncertain DC servomechanism system. The system consists of a pendulum actuated by a DC motor and subject to a time-varying bounded disturbance. The control law consists of a Proportional Derivative controller and an uncertain estimator that allows compensating the effects of the unknown bounded perturbation. Because the motor velocity state is not available from measurements, a second-order sliding-mode observer permits the estimation of this variable in finite time. This last feature allows applying the Separation Principle. The convergence analysis is carried out by means of the Lyapunov method. Results obtained from numerical simulations and experiments in a laboratory prototype show the performance of the closed loop system.
This document describes a model-based autotuning system that uses an artificial neural network (ANN) and relay feedback test. The system estimates process parameters like gain, ultimate gain, ultimate frequency, and apparent deadtime from relay feedback test data. It then classifies the process dynamics and tunes PI/PID controllers based on either a first-order plus deadtime or second-order plus deadtime process model. The tuning rules are derived from these models to provide superior control performance compared to Ziegler-Nichols tuning.
This document describes a study applying a recursive orthogonal least squares (ROLS) algorithm to develop a neural network model for a continuous fermenter system using a nonlinear model predictive control (NMPC) approach. The ROLS algorithm is used to update the weighting matrix to model the nonlinear, multivariable system dynamics. The NMPC controller using this model is tested on the fermenter by changing setpoints. It is shown to reach new setpoints faster than alternative controllers like IMC, PI, and FLC controllers.
DEVELOPMENT OF FUZZY LOGIC LQR CONTROL INTEGRATION FOR AERIAL REFUELING AUTOP...Ahmed Momtaz Hosny, PhD
This document summarizes research on integrating fuzzy logic control with linear quadratic regulator (LQR) control for an aerial refueling autopilot. It describes modeling an aircraft, applying LQR control alone and with fuzzy logic control integrated. The integrated LQR fuzzy control is shown to more effectively suppress uncertainties and minimize mission time compared to LQR alone. Key aspects covered include aircraft modeling, optimal LQR flight control, applying fuzzy inference systems, deriving fuzzy rules, and the integrated LQR fuzzy control structure applied to pitch and lateral control for aerial refueling simulations.
This document summarizes a research project on process identification using relay feedback tests. The project aims to identify low-order models like FOPDT and SOPDT from relay feedback data to enable performance assessment and controller tuning. A new identification method is proposed that uses neural networks to estimate the apparent deadtime from steady-state cycles. This deadtime and other parameters allow classification of the process model and parameter estimation for assessment and auto-tuning.
Analytical Evaluation of Generalized Predictive Control Algorithms Using a Fu...inventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
This document describes a new method for designing fractional-order proportional-integral-derivative (FOPID) controllers. It introduces approximating fractional-order differential operators using a biquadratic structure, which allows designing finite-order FOPID controllers with fewer parameters than existing designs. A systematic procedure is presented to design FOPID controllers to achieve desired phase and gain margins of controlled systems. The viability of the design method is verified with a numerical example.
Adaptive pi based on direct synthesis nishantNishant Parikh
This document describes an adaptive proportional-integral (PI) controller for a laboratory level control system. The system consists of two interconnected tanks where the level of the second tank is controlled. Due to changes in plant dynamics over time, an adaptive controller is used. The plant parameters are estimated online using recursive least squares estimation based on input and output signals. The estimated parameters are then used to calculate PI controller parameters to achieve the desired closed-loop response. Experimental results show the controller can maintain level control even after changes in plant dynamics without needing re-calibration.
Output feedback trajectory stabilization of the uncertainty DC servomechanism...ISA Interchange
This work proposes a solution for the output feedback trajectory-tracking problem in the case of an uncertain DC servomechanism system. The system consists of a pendulum actuated by a DC motor and subject to a time-varying bounded disturbance. The control law consists of a Proportional Derivative controller and an uncertain estimator that allows compensating the effects of the unknown bounded perturbation. Because the motor velocity state is not available from measurements, a second-order sliding-mode observer permits the estimation of this variable in finite time. This last feature allows applying the Separation Principle. The convergence analysis is carried out by means of the Lyapunov method. Results obtained from numerical simulations and experiments in a laboratory prototype show the performance of the closed loop system.
This document describes a model-based autotuning system that uses an artificial neural network (ANN) and relay feedback test. The system estimates process parameters like gain, ultimate gain, ultimate frequency, and apparent deadtime from relay feedback test data. It then classifies the process dynamics and tunes PI/PID controllers based on either a first-order plus deadtime or second-order plus deadtime process model. The tuning rules are derived from these models to provide superior control performance compared to Ziegler-Nichols tuning.
This document describes a study applying a recursive orthogonal least squares (ROLS) algorithm to develop a neural network model for a continuous fermenter system using a nonlinear model predictive control (NMPC) approach. The ROLS algorithm is used to update the weighting matrix to model the nonlinear, multivariable system dynamics. The NMPC controller using this model is tested on the fermenter by changing setpoints. It is shown to reach new setpoints faster than alternative controllers like IMC, PI, and FLC controllers.
Compensation of Data-Loss in Attitude Control of Spacecraft Systems rinzindorjej
In this paper, a comprehensive comparison of two robust estimation techniques namely, compensated closed-loop Kalman filtering and open-loop Kalman filtering is presented. A common problem of data loss in a real-time control system is investigated through these two schemes. The open-loop scheme, dealing with the data-loss, suffers from several shortcomings. These shortcomings are overcome using compensated scheme, where an accommodating observation signal is obtained through linear prediction technique -- a closed-loop setting and is adopted at a posteriori update step. The calculation and employment of accommodating observation signal causes computational complexity. For simulation purpose, a linear time invariant spacecraft model is however, obtained from the nonlinear spacecraft attitude dynamics through linearization at nonzero equilibrium points -- achieved off-line through Levenberg-Marguardt iterative scheme. Attempt has been made to analyze the selected example from most of the perspectives in order to display the performance of the two techniques.
Numerical Optimization of Fractional Order PID Controller inventionjournals
: The fractional order PID controller is the generalization of classical PID controller, many Researchers interest in tuning FOPID controller here we use the Pareto Optimum technique to estimate the controller parameter and compare our result with the classical model and with other Researchers result .we used both mathematica package and matlab for tuning and simulation
This document introduces the fuzzy model reference learning control (FMRLC) method. FMRLC uses a reference model to provide feedback to modify the membership functions of a fuzzy controller. This allows the closed-loop system to behave like the reference model and achieve the desired performance. The effectiveness of FMRLC is demonstrated through its application to rocket velocity control and robot manipulator control. FMRLC can achieve high performance learning control for nonlinear, time-varying systems.
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.
Performance analysis of a liquid column in a chemical plant by using mpceSAT Publishing House
This document discusses the use of model predictive control (MPC) to control the composition of a liquid column in a chemical plant. It provides background on MPC and how it can be used for multivariable processes like liquid columns. The document describes modeling a liquid column process in MATLAB Simulink and comparing the performance of MPC and PID control of the column. The results show that MPC provides better control of the column composition and liquid level than PID control.
Design and Implementation of Model Reference Adaptive Controller using Coeffi...IOSR Journals
This document describes the design and implementation of a model reference adaptive controller (MRAC) using the coefficient diagram method (CDM) for a nonlinear process. It begins by introducing MRAC for single-input single-output plants, developing the MRAC design and control law. It then provides basics of the CDM design approach. The document applies the CDM-MRAC to a spherical tank level process in simulation, comparing its performance to a linear PI controller. Simulation results show the CDM-MRAC has faster rise time and settling time than the PI controller.
This document summarizes multi-objective optimization of a Tricept parallel manipulator using an evolutionary algorithm. It discusses using a particle swarm optimization (PSO) technique to optimize the manipulator's conditioning index, workspace volume, and global conditioning index (GCI) simultaneously. The methodology involves calculating inverse kinematics and the Jacobian to determine performance parameters. Single-objective PSO is used to optimize the conditioning index alone. Results show the minimum conditioning index and corresponding design variables. PSO also optimizes the workspace volume alone. A multi-objective PSO with a weighted sum strategy then optimizes all parameters simultaneously, showing their relationships and validating results against single-objective optimization.
Performance Comparison of Identification Methods Applied to Power Systems for...Reza Pourramezan
Authors: Reza Pourramezan, Sadegh Vaez-Zadeh, and Hamid Reza Nourzadeh
Published in 2006 IEEE International Conference on Industrial Technology (ICIT)
DOI: 10.1109/ICIT.2006.372551
http://ieeexplore.ieee.org/document/4237873/
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
Neural Network Control Based on Adaptive Observer for Quadrotor HelicopterIJITCA Journal
A neural network control scheme with an adaptive observer is proposed in this paper to Quadrotor helicopter stabilization. The unknown part in Quadrotor dynamical model was estimated on line by a Single Hidden Layer network. To solve the non measurable states problem a new adaptive observer was proposed. The main purpose here is to reduce the measurement noise amplification caused by conventional high gain observer by introducing some changes in observer’s original structure that can minimize the variance and the amplitude of the noisy signal without increasing tracking error. The stability analysis of the overall closed-loop system/ observer is performed using the Lyapunov direct method. Simulation results are given to highlight the performances of the proposed scheme
A comparative study of controllers for stabilizing a rotary inverted pendulumijccmsjournal
The document describes a comparative study of various controllers - PID, LQR, fuzzy logic, and H-infinity - for stabilizing a rotary inverted pendulum (RIP) system. The controllers are modeled and tested in MATLAB Simulink. Key findings:
- PID control stabilizes the pendulum angle to zero within 1 second.
- LQR control stabilizes the pendulum angle to zero within 1.5 seconds.
- Fuzzy logic control stabilizes the pendulum angle within 0.5 seconds.
- H-infinity control provides robust stabilization of the RIP system.
1) The document describes using genetic algorithms to tune PID, state variable feedback, and LQR controllers for balancing an inverted pendulum on a cart.
2) It presents the mathematical model of the inverted pendulum system and linearizes the model.
3) PID, state variable feedback, and LQR controllers are designed for the system. The controller parameters are then tuned using a genetic algorithm to minimize error.
4) Simulation results show the genetic algorithm approach improves rise time and reduces overshoot compared to controllers without genetic algorithm tuning.
Solving output control problems using Lyapunov gradient-velocity vector functionIJECEIAES
This paper describes a controller and observer parameter definition approach in one input-one output (closed-loop) control systems using Lyapunov gradient-velocity vector function. Construction of the vector function is based on the gradient nature of the control systems and the parity of the vector functions with the potential function from the theory of catastrophe. Investigation of the closed-loop control system’s stability and solution of the problem of controller (determining the coefficient of magnitude matrix) and observer (calculation of the matrix elements of the observing equipment) synthesis is based on the direct methods of Lyapunov. The approach allows to select parameters based on the requested characteristics of the system.
Quicksort is described including its Java source code, time complexity analysis, and optimizations. It works by partitioning an array around pivots and recursively sorting the subarrays. The basic algorithm runs in O(n log n) time on average but can degrade to O(n^2). Optimizations like insertion sort for small subproblems and dual pivots are tested, with dual pivots performing best in testing.
The document describes optimizing an automatic generation control (AGC) scheme for a two-area power system using a particle swarm optimization (PSO) tuned fuzzy PID controller. A linearized model of the two-area power system is presented. A fuzzy PID controller is used to regulate the area control error of each area. The gains of the fuzzy PID controller are optimized using PSO to minimize time-domain performance metrics. Simulation results show the PSO tuned fuzzy PID controller provides better dynamic response than a conventional PSO PID controller, with lower error and faster settling time. Comparisons of tie-line power deviation also show improved performance with the PSO tuned fuzzy approach. The paper concludes the proposed method efficiently tunes fuzzy PID parameters
Flatness Based Nonlinear Sensorless Control of Induction Motor SystemsIAES-IJPEDS
This paper deals with the flatness-based approach for sensorless control of
the induction motor systems. Two main features of the proposed flatness
based control are worth to be mentioned. Firstly, the simplicity of
implementation of the flatness approach as a nonlinear feedback linearization
control technique. Secondly, when the chosen flat outputs involve non
available state variable measurements a nonlinear observer is used to
estimate them. The main advantage of the used observer is its ability to
exploite the properties of the system nonlinearties. The simulation results are
presented to illustrate the effectiness of the proposed approach for sensorless
control of the considered induction motor.
O documento discute estruturas de dados dinâmicas como listas, pilhas, filas e árvores binárias em Pascal. Explica como declarar e manipular cada estrutura através de operações como inserção, remoção e busca de elementos. Também aborda ponteiros, recursividade e como representar cada estrutura de dados na memória usando registros e ponteiros.
Este documento discute como elaborar um plano de negócios eficaz, incluindo analisar as forças e fraquezas individuais, definir os objetivos e metas da empresa, e desenvolver seções sobre análise de mercado, marketing, finanças e tomada de decisão. O plano de negócios é importante para identificar erros e orientar o desenvolvimento sustentável da empresa.
1) The document describes a proposed hybrid power generation system using solar, wind, and hydro energy sources.
2) It presents models for the photovoltaic cells, wind turbine generator, and hydraulic turbine components and discusses how they are combined and controlled.
3) Simulation results are shown verifying the system can provide continuous power to loads by compensating for periods of low solar or wind input using hydro power generation.
Este documento presenta información sobre diferentes estilos de comportamiento y enfoques para desarrollar la inteligencia emocional. También proporciona consejos para que los formadores usen un enfoque basado en las emociones en el aula, como crear un ambiente seguro, tratar a los estudiantes con respeto y fomentar la participación.
Compensation of Data-Loss in Attitude Control of Spacecraft Systems rinzindorjej
In this paper, a comprehensive comparison of two robust estimation techniques namely, compensated closed-loop Kalman filtering and open-loop Kalman filtering is presented. A common problem of data loss in a real-time control system is investigated through these two schemes. The open-loop scheme, dealing with the data-loss, suffers from several shortcomings. These shortcomings are overcome using compensated scheme, where an accommodating observation signal is obtained through linear prediction technique -- a closed-loop setting and is adopted at a posteriori update step. The calculation and employment of accommodating observation signal causes computational complexity. For simulation purpose, a linear time invariant spacecraft model is however, obtained from the nonlinear spacecraft attitude dynamics through linearization at nonzero equilibrium points -- achieved off-line through Levenberg-Marguardt iterative scheme. Attempt has been made to analyze the selected example from most of the perspectives in order to display the performance of the two techniques.
Numerical Optimization of Fractional Order PID Controller inventionjournals
: The fractional order PID controller is the generalization of classical PID controller, many Researchers interest in tuning FOPID controller here we use the Pareto Optimum technique to estimate the controller parameter and compare our result with the classical model and with other Researchers result .we used both mathematica package and matlab for tuning and simulation
This document introduces the fuzzy model reference learning control (FMRLC) method. FMRLC uses a reference model to provide feedback to modify the membership functions of a fuzzy controller. This allows the closed-loop system to behave like the reference model and achieve the desired performance. The effectiveness of FMRLC is demonstrated through its application to rocket velocity control and robot manipulator control. FMRLC can achieve high performance learning control for nonlinear, time-varying systems.
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.
Performance analysis of a liquid column in a chemical plant by using mpceSAT Publishing House
This document discusses the use of model predictive control (MPC) to control the composition of a liquid column in a chemical plant. It provides background on MPC and how it can be used for multivariable processes like liquid columns. The document describes modeling a liquid column process in MATLAB Simulink and comparing the performance of MPC and PID control of the column. The results show that MPC provides better control of the column composition and liquid level than PID control.
Design and Implementation of Model Reference Adaptive Controller using Coeffi...IOSR Journals
This document describes the design and implementation of a model reference adaptive controller (MRAC) using the coefficient diagram method (CDM) for a nonlinear process. It begins by introducing MRAC for single-input single-output plants, developing the MRAC design and control law. It then provides basics of the CDM design approach. The document applies the CDM-MRAC to a spherical tank level process in simulation, comparing its performance to a linear PI controller. Simulation results show the CDM-MRAC has faster rise time and settling time than the PI controller.
This document summarizes multi-objective optimization of a Tricept parallel manipulator using an evolutionary algorithm. It discusses using a particle swarm optimization (PSO) technique to optimize the manipulator's conditioning index, workspace volume, and global conditioning index (GCI) simultaneously. The methodology involves calculating inverse kinematics and the Jacobian to determine performance parameters. Single-objective PSO is used to optimize the conditioning index alone. Results show the minimum conditioning index and corresponding design variables. PSO also optimizes the workspace volume alone. A multi-objective PSO with a weighted sum strategy then optimizes all parameters simultaneously, showing their relationships and validating results against single-objective optimization.
Performance Comparison of Identification Methods Applied to Power Systems for...Reza Pourramezan
Authors: Reza Pourramezan, Sadegh Vaez-Zadeh, and Hamid Reza Nourzadeh
Published in 2006 IEEE International Conference on Industrial Technology (ICIT)
DOI: 10.1109/ICIT.2006.372551
http://ieeexplore.ieee.org/document/4237873/
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
Neural Network Control Based on Adaptive Observer for Quadrotor HelicopterIJITCA Journal
A neural network control scheme with an adaptive observer is proposed in this paper to Quadrotor helicopter stabilization. The unknown part in Quadrotor dynamical model was estimated on line by a Single Hidden Layer network. To solve the non measurable states problem a new adaptive observer was proposed. The main purpose here is to reduce the measurement noise amplification caused by conventional high gain observer by introducing some changes in observer’s original structure that can minimize the variance and the amplitude of the noisy signal without increasing tracking error. The stability analysis of the overall closed-loop system/ observer is performed using the Lyapunov direct method. Simulation results are given to highlight the performances of the proposed scheme
A comparative study of controllers for stabilizing a rotary inverted pendulumijccmsjournal
The document describes a comparative study of various controllers - PID, LQR, fuzzy logic, and H-infinity - for stabilizing a rotary inverted pendulum (RIP) system. The controllers are modeled and tested in MATLAB Simulink. Key findings:
- PID control stabilizes the pendulum angle to zero within 1 second.
- LQR control stabilizes the pendulum angle to zero within 1.5 seconds.
- Fuzzy logic control stabilizes the pendulum angle within 0.5 seconds.
- H-infinity control provides robust stabilization of the RIP system.
1) The document describes using genetic algorithms to tune PID, state variable feedback, and LQR controllers for balancing an inverted pendulum on a cart.
2) It presents the mathematical model of the inverted pendulum system and linearizes the model.
3) PID, state variable feedback, and LQR controllers are designed for the system. The controller parameters are then tuned using a genetic algorithm to minimize error.
4) Simulation results show the genetic algorithm approach improves rise time and reduces overshoot compared to controllers without genetic algorithm tuning.
Solving output control problems using Lyapunov gradient-velocity vector functionIJECEIAES
This paper describes a controller and observer parameter definition approach in one input-one output (closed-loop) control systems using Lyapunov gradient-velocity vector function. Construction of the vector function is based on the gradient nature of the control systems and the parity of the vector functions with the potential function from the theory of catastrophe. Investigation of the closed-loop control system’s stability and solution of the problem of controller (determining the coefficient of magnitude matrix) and observer (calculation of the matrix elements of the observing equipment) synthesis is based on the direct methods of Lyapunov. The approach allows to select parameters based on the requested characteristics of the system.
Quicksort is described including its Java source code, time complexity analysis, and optimizations. It works by partitioning an array around pivots and recursively sorting the subarrays. The basic algorithm runs in O(n log n) time on average but can degrade to O(n^2). Optimizations like insertion sort for small subproblems and dual pivots are tested, with dual pivots performing best in testing.
The document describes optimizing an automatic generation control (AGC) scheme for a two-area power system using a particle swarm optimization (PSO) tuned fuzzy PID controller. A linearized model of the two-area power system is presented. A fuzzy PID controller is used to regulate the area control error of each area. The gains of the fuzzy PID controller are optimized using PSO to minimize time-domain performance metrics. Simulation results show the PSO tuned fuzzy PID controller provides better dynamic response than a conventional PSO PID controller, with lower error and faster settling time. Comparisons of tie-line power deviation also show improved performance with the PSO tuned fuzzy approach. The paper concludes the proposed method efficiently tunes fuzzy PID parameters
Flatness Based Nonlinear Sensorless Control of Induction Motor SystemsIAES-IJPEDS
This paper deals with the flatness-based approach for sensorless control of
the induction motor systems. Two main features of the proposed flatness
based control are worth to be mentioned. Firstly, the simplicity of
implementation of the flatness approach as a nonlinear feedback linearization
control technique. Secondly, when the chosen flat outputs involve non
available state variable measurements a nonlinear observer is used to
estimate them. The main advantage of the used observer is its ability to
exploite the properties of the system nonlinearties. The simulation results are
presented to illustrate the effectiness of the proposed approach for sensorless
control of the considered induction motor.
O documento discute estruturas de dados dinâmicas como listas, pilhas, filas e árvores binárias em Pascal. Explica como declarar e manipular cada estrutura através de operações como inserção, remoção e busca de elementos. Também aborda ponteiros, recursividade e como representar cada estrutura de dados na memória usando registros e ponteiros.
Este documento discute como elaborar um plano de negócios eficaz, incluindo analisar as forças e fraquezas individuais, definir os objetivos e metas da empresa, e desenvolver seções sobre análise de mercado, marketing, finanças e tomada de decisão. O plano de negócios é importante para identificar erros e orientar o desenvolvimento sustentável da empresa.
1) The document describes a proposed hybrid power generation system using solar, wind, and hydro energy sources.
2) It presents models for the photovoltaic cells, wind turbine generator, and hydraulic turbine components and discusses how they are combined and controlled.
3) Simulation results are shown verifying the system can provide continuous power to loads by compensating for periods of low solar or wind input using hydro power generation.
Este documento presenta información sobre diferentes estilos de comportamiento y enfoques para desarrollar la inteligencia emocional. También proporciona consejos para que los formadores usen un enfoque basado en las emociones en el aula, como crear un ambiente seguro, tratar a los estudiantes con respeto y fomentar la participación.
Cramming for exams should only be done as a last resort since it is difficult to retain large amounts of information in a short time period. Some tips for effective cramming include eating food to stay energized but avoiding excess sugar, studying in a well-lit place with few distractions, keeping a positive attitude, focusing on the most important topics that will earn the most points, and taking short breaks every hour. It is also important to get at least 3 hours of sleep before the exam if time allows.
Jornadas de formación consejería 30 junio 2012 (1)juanjosotelo
Las Escuelas Europeas se crearon en 1953 para escolarizar a los hijos de funcionarios de la Unión Europea. Actualmente también admiten a hijos de otros trabajadores relacionados con programas europeos. Las Escuelas Europeas ofrecen una educación multilingüe donde los estudiantes aprenden varios idiomas, con el objetivo de fomentar la cooperación entre estudiantes de diferentes orígenes. La enseñanza de lenguas incluye el estudio de la lengua materna, dos lenguas extranjeras obligatorias y la posibilidad de una tercera
1. O documento é um manual sobre cantinas escolares saudáveis produzido pelo Ministério da Saúde brasileiro.
2. Ele fornece informações sobre a importância de promover hábitos alimentares saudáveis e sobre como transformar cantinas escolares em locais que estimulem o consumo de alimentos saudáveis.
3. O manual aborda tópicos como o que é uma alimentação saudável, higiene dos alimentos, lanches saudáveis e estratégias para manter a cantina escolar promovendo hábitos alimentares
The relationship between the five factors of personality, individual job perf...iaemedu
This document summarizes a study on the relationship between the five factors of personality and individual job performance in the Indian corporate sector. The study analyzed 316 employees across manufacturing and service industries. It found that conscientiousness, extraversion, and emotional stability were valid predictors of overall job performance. Conscientiousness and extraversion also impacted components like task performance and adaptability. Neuroticism had a significant relationship with job stress. Most variables did not impact job stress and stability components of performance. The study contributes to the body of research showing the five factor model can predict job performance across cultures.
Este documento analisa a relação entre identidade nacional brasileira e publicidade. Discute brevemente a construção da identidade nacional no Brasil e, em seguida, analisa elementos do nacionalismo presentes em um anúncio de sandálias Havaianas usando a metodologia de Vestergaard e Schroder para análise de textos publicitários. O documento conclui que a publicidade apropria-se da cultura e identidade brasileiras tanto para fins comerciais quanto para reforçar uma visão hegemônica da sociedade.
Este documento resume un libro que analiza cómo negocian los colombianos. Explica que los colombianos tienden a negociar de forma distributiva, buscando que el otro pierda para que uno gane. Esto se aprende desde la niñez. También identifica características como ser impuntuales e impacientes. Recomienda que los colombianos aprendan a negociar de forma integrativa, buscando que ambas partes se beneficien.
The document provides an overview of T-3 Energy Services, Inc., including its history, products and services, markets, growth strategy, and facilities. It notes that the company designs, manufactures, and services pressure and flow control equipment for the oil and gas industry. Forward-looking statements are presented regarding future financial performance and operating results.
Este documento guía a los estudiantes a través de varias actividades de autoexploración para identificar sus fortalezas, debilidades, motivaciones y estilos de pensamiento. El objetivo es que los estudiantes se conozcan a sí mismos para poder formar equipos creativos efectivos que aprovechen la diversidad de habilidades.
Software orientado a realizar estadísticas descriptivasppenas
Este documento describe varios softwares estadísticos para realizar análisis estadísticos descriptivos. Menciona programas como SPSS, Systat, Winks, Kwikstat Windows, Acasat, Statcalc, Biostat Profesional, Smart Photo Statistics, Stagraphics y Minitab, detallando brevemente las características y funcionalidades de cada uno.
Este documento trata sobre las funciones ejecutivas y su relación con el córtex prefrontal. Las funciones ejecutivas se refieren a los procesos cognitivos implicados en el control consciente de la conducta y el pensamiento, e incluyen capacidades como la memoria de trabajo, la atención y la inhibición. Existen diferentes modelos de las funciones ejecutivas, pero no hay consenso sobre una definición única. Las alteraciones en las funciones ejecutivas se han relacionado con lesiones del córtex prefrontal y con diversas patologías neu
Recent studies commissioned by UNICEF Kosovo show clearly that children are at significantly greater risk of poverty in Kosovo compared to the general population. Using the generally accepted consumption poverty line of €1.417 per person
per day, based on 2006/7 Household Budget Survey data, 46.2% of the Kosovo population is in poverty, whereas 48.6% of children aged 0-19 are in poverty. The highest risks of poverty are faced by children who live in households with three or more children; children aged 0-14; children of unemployed parents; children in households receiving social assistance; and children in households with low levels of education. Whilst the risk of poverty is lower for children where at least
one family member is employed, children in wage-earning households make up 36% of all children in poverty in Kosovo.
1) This document discusses major design issues related to creating mixed analog/digital application specific integrated circuits (ASICs). It outlines key decisions around process selection, module selection and creation, simulation, and placement and routing.
2) Process selection involves choosing a foundry and CMOS process based on technical requirements like operating voltage, component tolerances, and amounts of analog vs digital circuits. This impacts cost and available design options.
3) Modules can be acquired through full custom design, standard cell libraries, parameterized standard cells, layout synthesis, or circuit synthesis - each with varying costs and flexibility. Characterized standard cell libraries provide reference designs.
4) Simulation is needed to verify component interconnections. Analog interface points should
Este documento presenta un resumen de tres partes del ensayo "La pedagogía de la autonomía". La primera parte discute que no puede haber enseñanza sin aprendizaje, y que maestros y estudiantes aprenden mutuamente. La segunda parte argumenta que enseñar no es simplemente transferir conocimiento, sino desarrollar el pensamiento crítico del estudiante. La tercera parte concluye que enseñar es una especificidad humana que requiere una sólida preparación del maestro.
Learn the 8 components of a classroom learning community to improve student ownership and accountability as you work to develop 21st century learners, critical thinkers and skilled collaborators.
The document discusses various blood components and their uses in pediatric transfusion medicine. It describes whole blood and derived blood products like red blood cell concentrates, platelet concentrates, fresh frozen plasma, and granulocyte concentrates. Guidelines for transfusing these components in neonates and children are provided based on hemoglobin levels and clinical indications. Contraindications and dosing are also summarized.
Este documento presenta el Código de Ética para Profesionales de la Contabilidad publicado por el Consejo de Normas Internacionales de Ética para Contadores (IESBA) de la Federación Internacional de Contadores (IFAC). El código establece los requisitos éticos para los profesionales de la contabilidad en todo el mundo y consta de tres partes: Parte A sobre principios fundamentales de ética, Parte B sobre profesionales de la contabilidad en ejercicio y Parte C sobre profesionales de la contabilidad en la empresa. El document
Closed-loop step response for tuning PID fractional-order filter controllersISA Interchange
Analytical methods are usually applied for tuning fractional controllers. The present paper proposes an empirical method for tuning a new type of fractional controller known as PID-Fractional-Order-Filter (FOF-PID). Indeed, the setpoint overshoot method, initially introduced by Shamsuzzoha and Skogestad, has been adapted for tuning FOF-PID controller. Based on simulations for a range of first order with time delay processes, correlations have been derived to obtain PID-FOF controller parameters similar to those obtained by the Internal Model Control (IMC) tuning rule. The setpoint overshoot method requires only one closed-loop step response experiment using a proportional controller (P-controller). To highlight the potential of this method, simulation results have been compared with those obtained with the IMC method as well as other pertinent techniques. Various case studies have also been considered. The comparison has revealed that the proposed tuning method performs as good as the IMC. Moreover, it might offer a number of advantages over the IMC tuning rule. For instance, the parameters of the frac- tional controller are directly obtained from the setpoint closed-loop response data without the need of any model of the plant to be controlled.
This document describes a new design method for fractional-order PID (FOPID) controllers. It introduces a biquadratic approximation of fractional-order differential operators to create a new structure for finite-order FOPID controllers with fewer parameters to tune than existing designs. The proposed FOPID controller design uses the biquadratic approximation within a modular design approach, cascading multiple modules to improve robustness. A numerical example is used to verify the design method.
Abstract - This paper addresses some of the potential benefits of
using fuzzy logic controllers to control an inverted pendulum
system. The stages of the development of a fuzzy logic controller
using a four input Takagi-Sugeno fuzzy model were presented.
The main idea of this paper is to implement and optimize fuzzy
logic control algorithms in order to balance the inverted
pendulum and at the same time reducing the computational time
of the controller. In this work, the inverted pendulum system was
modeled and constructed using Simulink and the performance of
the proposed fuzzy logic controller is compared to the more
commonly used PID controller through simulations using Matlab.
Simulation results show that the Fuzzy Logic Controllers are far
more superior compared to PID controllers in terms of overshoot,
settling time and response to parameter changes.
Model-based Approach of Controller Design for a FOPTD System and its Real Tim...IOSR Journals
The document summarizes a study on model-based controller design for a first-order plus time delay (FOPTD) system. The study identifies the process model of a level control system using process reaction curve methods. Various tuning rules for internal model control-proportional integral derivative (IMC-PID) controllers from literature are applied to the system, including rules from Rivera, Chien, Lee, Skogestad, and Panda. The performance of each controller is evaluated based on rise time, settling time, percentage overshoot, integral absolute error, and integral of time multiplied absolute error. The study finds that the Panda tuning rule has the smallest percentage overshoot and integral absolute error, while the Chien rule has
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...IJECEIAES
In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations.
Controller Design Based On Fuzzy Observers For T-S Fuzzy Bilinear Models ijctcm
This article is devoted to the design of a fuzzy-observer-based control for a class of nonlinear systems with bilinear terms. The class of systems considered is the Takagi-Sugeno (T-S) fuzzy bilinear model. A new procedure to design the observer-based fuzzy controller for this class of systems is proposed. The aim is to design the fuzzy controller and the fuzzy observer of the augmented system separately in order to guarantee that the error between the state and its estimation converges faster to zero. By using the Lyapunov function, sufficient conditions are derived such that the closed-loop system is globally asymptotically stable. Moreover, sufficient conditions for controller design based on state estimation for robust stabilization of TS FBS with parametric uncertainties is proposed. The observer and controller gains are obtained by solving some linear matrix inequalities (LMIs). An example is given to illustrate the effectiveness of the proposed approach.
The document describes the design of a fractional order PIλDλ controller for liquid level control of a spherical tank modeled as a fractional order system. A fractional order proportional integral derivative (FOPID) controller is designed and its performance is compared to a traditional integer order PID controller designed for the same spherical tank modeled as a first order plus dead time system. Simulation results show that the fractional order controller designed using frequency domain specifications achieves improved performance over the integer order controller. The fractional order controller provides extra tuning parameters that allow it to better match the dynamics of the fractional order plant model.
Data-driven adaptive predictive control for an activated sludge processjournalBEEI
Data-driven control requires no information of the mathematical model of the controlled process. This paper proposes the direct identification of controller parameters of activated sludge process. This class of data-driven control calculates the predictive controller parameters directly using subspace identification technique. By updating input-output data using receding window mechanism, the adaptive strategy can be achieved. The robustness test and stability analysis of direct adaptive model predictive control are discussed to realize the effectiveness of this adaptive control scheme. The applicability of the controller algorithm to adapt into varying kinetic parameters and operating conditions is evaluated. Simulation results show that by a proper and effective excitation of direct identification of controller parameters, the convergence and stability of the implicit predictive model can be achieved.
COMPARATIVE ANALYSIS OF CONVENTIONAL PID CONTROLLER AND FUZZY CONTROLLER WIT...IJITCA Journal
All the real systems exhibits non-linear nature,conventional controllers are not always able to provide good and accurate results. Fuzzy Logic Control is used to obtain better response. A model for simulation is designed and all the assumptions are made before the development of the model. An attempt has been made to analyze the efficiency of a fuzzy controller over a conventional PID controller for a three tank level control system using fuzzification & defuzzification methods and their responses are compared. Analysis is done through computer simulation using Matlab/Simulink toolbox. This study shows that the application of Fuzzy Logic Controller (FLC) gives the best response with triangular membership function and centroid defuzzification method.
FRACTIONAL ORDER PID CONTROLLER TUNING BASED ON IMC IJITCA Journal
In this work, a class of fractional order controller (FOPID) is tuned based on internal model control
(IMC). This tuning rule has been obtained without any approximation of time delay. Moreover to show
usefulness of fractional order controller in comparison with classical integer order controllers, an
industrial PID controller tuned in a similar way, is compared with FOPID and then robust stability of both
controllers is investigated. Robust stability analysis has been done to find maximum delayed time
uncertainty interval which results in a stable closed loop control system. For a typical system, robust
stability has been done to find maximum time constant uncertainty interval of system. Two clarify the
proposed control system design procedure, three examples have been given.
2-DOF Block Pole Placement Control Application To: Have-DASH-IIBITT MissileZac Darcy
In a multivariable servomechanism design, it is required that the output vector tracks a certain reference
vector while satisfying some desired transient specifications, for this purpose a 2DOF control law
consisting of state feedback gain and feedforward scaling gain is proposed. The control law is designed
using block pole placement technique by assigning a set of desired Block poles in different canonical forms.
The resulting control is simulated for linearized model of the HAVE DASH II BTT missile; numerical
results are analyzed and compared in terms of transient response, gain magnitude, performance
robustness, stability robustness and tracking. The suitable structure for this case study is then selected.
2-DOF Block Pole Placement Control Application To: Have-DASH-IIBITT MissileZac Darcy
In a multivariable servomechanism design, it is required that the output vector tracks a certain reference
vector while satisfying some desired transient specifications, for this purpose a 2DOF control law
consisting of state feedback gain and feedforward scaling gain is proposed. The control law is designed
using block pole placement technique by assigning a set of desired Block poles in different canonical forms.
The resulting control is simulated for linearized model of the HAVE DASH II BTT missile; numerical
results are analyzed and compared in terms of transient response, gain magnitude, performance
robustness, stability robustness and tracking. The suitable structure for this case study is then selected.
Metamodel-based Optimization of a PID Controller Parameters for a Coupled-tan...TELKOMNIKA JOURNAL
Liquid flow and level control are essential requirements in various industries, such as paper
manufacturing, petrochemical industries, waste management, and others. Controlling the liquids flow and
levels in such industries is challenging due to the existence of nonlinearity and modeling uncertainties of
the plants. This paper presents a method to control the liquid level in a second tank of a coupled-tank plant
through variable manipulation of a water pump in the first tank. The optimum controller parameters of this
plant are calculated using radial basis function neural network metamodel. A time-varying nonlinear
dynamic model is developed and the corresponding linearized perturbation models are derived from the
nonlinear model. The performance of the developed optimized controller using metamodeling is compared
with the original large space design. In addition, linearized perturbation models are derived from the
nonlinear dynamic model with time-varying parameters.
A Comparative study of controllers for stabilizing a Rotary Inverted Pendulumijccmsjournal
This paper describes comparative study of various controllers on Rotary Inverted Pendulum (RIP). PID,
LQR, FUZZY LOGIC and H∞ controllers are tried on RIP in MatLab Simulink. The same four controllers
have been tested on test bed of RIP system the controllers are compared from various aspects. The
controllers in simulink are compared with the controllers in real time.
Feedback linearization and Backstepping controllers for Coupled Tanksieijjournal
This paper investigates the usage of some sophisticated and advanced nonlinear control algorithms inorder
to control a nonlinear Coupled Tanks System. The first control procedure is called the
Feedbacklinearisation control (FLC), this type of control has been found a successful in achieving a global
exponentialasymptotic stability, with very short time response, no significant overshooting is recordedand with a negligible norm of the error. The second control procedure is the approaches of Backsteppingcontrol (BC) which is a recursive procedure that interlaces the choice of a Lyapunov functionwith the design of feedback control, from simulation results it shown that this method preserves tracking, robust control and it can often solve stabilization problems with less restrictive conditions may beencountered in other methods. Finally both of the proposed control schemes guarantee theasymptoticstability of the closed loop system meeting trajectory tracking objectives
FEEDBACK LINEARIZATION AND BACKSTEPPING CONTROLLERS FOR COUPLED TANKSieijjournal
This paper investigates the usage of some sophisticated and advanced nonlinear control algorithms inorder to control a nonlinear Coupled Tanks System. The first control procedure is called the Feedbacklinearisation control (FLC), this type of control has been found a successful in achieving a global exponentialasymptotic stability, with very short time response, no significant overshooting is recordedand with a negligible norm of the error. The second control procedure is the approaches of Backsteppingcontrol (BC) which is a recursive procedure that interlaces the choice of a Lyapunov functionwith the design of feedback control, from simulation results it shown that this method preserves tracking, robust control and it can often solve stabilization problems with less restrictive conditions may beencountered in other methods. Finally both of the proposed control schemes guarantee the asymptoticstability of the closed loop system meeting trajectory tracking objectives.
FEEDBACK LINEARIZATION AND BACKSTEPPING CONTROLLERS FOR COUPLED TANKSieijjournal
This paper investigates the usage of some sophisticated and advanced nonlinear control algorithms in order to control a nonlinear Coupled Tanks System. The first control procedure is called the Feedback linearisation control (FLC), this type of control has been found a successful in achieving a global exponential asymptotic stability, with very short time response, no significant overshooting is recorded and with a negligible norm of the error. The second control procedure is the approaches of Back stepping control (BC) which is a recursive procedure that interlaces the choice of a Lyapunov function with the design of feedback control, from simulation results it shown that this method preserves tracking, robust control and it can often solve stabilization problems with less restrictive conditions may been countered in other methods. Finally both of the proposed control schemes guarantee the asymptoticstability of the closed loop system meeting trajectory tracking objectives.
Non integer order controller based robust performance analysis of a conical t...Editor Jacotech
The design of robust controller for any non linear process is a
challenging task because of the presence of various types of
uncertainties. In this paper, various design methods of robust
PID controller for the level control of conical tank are
discussed. Uncertainties are of different types, among that
structured uncertainty of 30% is introduced to the nominal
plant for analysing the robustness. As a first step, the control
of level is done by using conventional integer order controller
for both nominal and uncertain system. Then, the control is
done by means of Fractional Order Proportional Integral
Derivative (FOPID) controller for achieving robustness. With
the help of time series parameters, a comparison is made
between conventional PID and FOPID with respect to the
simulated output using MATLAB and also analyzed the
robustness.
2-DOF BLOCK POLE PLACEMENT CONTROL APPLICATION TO:HAVE-DASH-IIBTT MISSILEZac Darcy
In a multivariable servomechanism design, it is required that the output vector tracks a certain reference
vector while satisfying some desired transient specifications, for this purpose a 2DOF control law
consisting of state feedback gain and feedforward scaling gain is proposed. The control law is designed
using block pole placement technique by assigning a set of desired Block poles in different canonical forms.
The resulting control is simulated for linearized model of the HAVE DASH II BTT missile; numerical
results are analyzed and compared in terms of transient response, gain magnitude, performance
robustness, stability robustness and tracking. The suitable structure for this case study is then selected.
This paper describes comparative study of various controllers on Rotary Inverted Pendulum (RIP). PID,
LQR, FUZZY LOGIC and H∞ controllers are tried on RIP in MatLab Simulink. The same four controllers
have been tested on test bed of RIP system the controllers are compared from various aspects. The
controllers in simulink are compared with the controllers in real time.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Db36619623
1. S. Ramesh et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.619-623
www.ijera.com
RESEARCH ARTICLE
OPEN ACCESS
Fuzzy Model Based Learning Control for Spherical Tank Process
*
S Ramesh and S Abraham Lincon**
*&**
Department of Electronics and Instrumentation Engineering, Annamalai University,
Annamalai nagar-608002
ABSTRACT
Fuzzy Model Reference Learning Control (FMRLC) is an efficient technique for the control of non linear
process. In this paper, a FMRLC is applied in to a non linear spherical tank system. First, the mathematical
model of the spherical tank level system is derived and simulation runs are carried out by considering the
FMRLC in a closed loop. A similar test runs are also carried out with hybrid fuzzy P+ID Controller and
conventional fuzzy controller for comparison and analysis. The results clearly indicate that the incorporation of
FMRLC in the control loop for spherical tank system provides a good tracking performance than the hybrid
fuzzy P+ID and conventional fuzzy controller.
Keywords - Fmrlc, Hybrid Fuzzy, Fuzzy
I.
INTRODUCTION
Control of non linear process is obscure task
in the process control industries. This kind of
nonlinear process exhibit many not easy control
problems due to their non linear dynamic behavior,
uncertain and time varying parameters. Especially,
control of a level in a spherical tank is vital, because
the change in shape gives rise to the non linear
characteristics. An evaluation of a controller using
variable transformation proposed by Anathanatrajan
et.al [1] on hemi-spherical tank which shows a better
response than PI controller. A simple PI controller
design method has been proposed by Wang and Shao
[2] that achieves high performance for a wide range
of linear self regulating processes. Later in this
research field, Fuzzy control is a practical alternative
for a variety of challenging control applications,
since it provides a convenient method for
constructing nonlinear controllers via the use of
heuristic information. Procyk and Mamdani [3] have
discussed the advantage of Fuzzy Logic Controllers
(FLC) is that it can be applied to plants that are
difficult to get the mathematical model. Recently,
Fuzzy logic and conventional control design methods
have been combined to design a Proportional
Integral Fuzzy Logic Controller (PI - FLC). Tang and
Mulholland [4] have discussed about the comparison
of fuzzy logic with conventional controller.
Wei Li [5] has discussed the Fuzzy P+ID
controller and analyze its stability. The main idea of
the study is to use a conventional D controller to
stabilize a controlled object and the fuzzy
proportional (P) controller to improve control
performance. According to the stability condition [6],
modify the Ziegler and Nichols’ approach to design
of the fuzzyP+ID controller since this approach is
used in industrial control of a plant with unknown
structure or with nonlinear dynamics. When the
process is unstable in local region, the controller
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based on a fixed model will be unreliable and thus
the system performance is affected seriously.
To overcome these problems, in this paper a
“learning” control algorithm is presented which helps
to resolve some of the issues of conventional fuzzy
and hybrid fuzzy controller design. This algorithm
employs a reference model (a model of how you
would like the plant to behave) to provide closedloop performance feedback for synthesizing and
tuning a fuzzy controller’s knowledge-base.
Consequently, this algorithm is referred to as a
“Fuzzy Model Reference Learning Controller”
(FMRLC) [8][9].
The paper is divided as follows: Section 2
presents a brief description of the mathematical
model of Spherical tank system, section 3 and 4
shows the methodology, algorithms of FMRLC and
hybrid fuzzy P+ID , section 5 presents the results and
discussion and finally the conclusions are presented
in section 6.
II.
DYNAMIC MODEL OF THE SPHERICAL
TANK LEVEL SYSTEM
The spherical tank level system[10] is
shown in Figure 1. Here the control input fin is being
the input flow rate (m3/s) and the output is x which is
the fluid level (m) in the spherical tank
r-x
d0
r
r-surface
d0
Figure.1. Spherical Tank System
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2. S. Ramesh et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.619-623
Let, r = radius of tank
d0 = thickness (diameter) of pipe (m) and initial
height
r surface = radius on the surface of the fluid varies
according to the level (height) of fluid in the tank.
Dynamic model of tank is given as
𝑥1
𝛿
𝐴(x)𝛿x = fin (t) – a 2𝑔x
(1)
0
𝛿𝑡
Where
𝐴(x) = area of cross section of tank
= π (2rx − 𝑥 2 )
(2)
a = area of cross section of pipe
d
2
=π 0
(3)
2
Re write of dynamic model of tank at time t+ 𝛿𝑡,
A x δx = fin δt − a 2g(x − d0 ) δt
(4)
By combining equation (1) to (4) we have
𝛿x
𝛿𝑡
π. 𝑑 2
fin 𝛿𝑡 − 4 0 2𝑔(x−d 0 )
π (2rx −𝑥 2 ) )
=
𝛿x
𝑙𝑖𝑚 𝑑 →0
=
𝛿𝑡
Therefore
𝑑x
𝑑𝑡
(5)
𝑑x
fin 𝛿𝑡 − 4 0 2𝑔(x−d 0 )
π (2rx −𝑥 2 ) )
(6)
Equation (6) shows the dynamic model of the
spherical tank system
III.
-1
NB
-0.66
-0.5
Z
0
NS
-0.33
Z
0
PS
0.5
PS
0.33
PB
1
e(kT) , ec(kT)
PB
0.66
1
u(kT)
Figure 2. Membership functions for the fuzzy
controller.
The fuzzy controller implements a rule base
made of a set of IF-THEN type of rules. These rules
were determined heuristically based on the
knowledge of the plant. An example of IF THEN
rules is the following
𝑑𝑡
π. 𝑑 2
=
NS
NB
-1
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FUZZY MODEL REFERENCE LEARNING
CONTROL (FMRLC)
This section discusses the design and
development of the FMRLC and it is applied to the
spherical tank level system. The following steps are
considered for the design of FMRLC.
I.
Direct fuzzy control
II.
Adaptive fuzzy control
1. DIRECT FUZZY CONTROL
The rule base, the inference engine, the
fuzzification and the defuzzification interfaces are
the our major components to design the direct fuzzy
controller [8].
Consider the inputs to the fuzzy system: the
error and change in error is given by
e(kT)=r(kT) – y(kT)
(7)
c(kT) = ( e(kT) - e(kT-T) ) / T
(8)
and the output variable is
u(kT) = Flow(control valve)
(9)
The universe of discourse of the variables
(that is, their domain) is normalized to cover a range
of [-1, 1] and a standard choice for the membership
functions is used with five membership functions for
the three fuzzy variables (meaning 25 = 52 rules in
the rule base) and symmetric, 50% overlapping
triangular shaped membership functions (Figure 2),
meaning that only 4 (=22) rules at most can be active
at any given time.
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IF e is negative big (NB) and ce is negative
big (NB) THEN u is Negative big (NB)
This rule quantifies the situation where the
spherical tank system is far to minimum level to
maximum level hence the control valve needed to
open from 100% to 0% so that it control the
particular operating point of the liquid level system.
The resulting rule table is shown in the Table 1.
Table 1: Rule base for the fuzzy controller
“Level”
“ Change in error” ce
u
NB NS
Z
PS PB
NB
NB NB
NB
NS Z
NS
NB NB
NS
Z
PS
“Error” e Z
NB NS
Z
PS PB
PS
NS Z
PS
PB PB
PB
Z
PS
PB
PB PB
Here min-max inference engine is selected, utilizes
minimum for the AND operator and maximum for
the OR operator. The end of each rule, introduced by
THEN, is also done by minimum. The final
conclusion for the active rules is obtained by the
maximum of the considered fuzzy sets. To obtain the
crisp output, the centre of gravity (COG)
defuzzification method is used. This crisp value is the
resulting controller output.
2. ADAPTIVE FUZZY CONTROL
In this section, design and development of a
FMRLC, which will adaptively tune on-line the
centers of the output membership functions of the
fuzzy controller determined earlier.
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ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.619-623
1.
ym(kT)
REFERENCE
MODEL
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The active set of rules for the fuzzy controller at
time (k-1)T is first determined
+
ye(kT)
RULE
BASED
MODIFIER
p(kT)
FUZZY INVERSE
MODEL
yce(kT)
1 z 1
T
s
(12)
-
LEARNING MECHANISM
r(kT)
+
-
e(kT)
u(kT)
1 z 1
ec(kT)
FUZZY
FUZZY
CONTROLLER
CONTROLLER
y(kT)
PLANT
T
s
Figure 3. Fuzzy Model Reference Learning Control
Figure 3 shows the FMRLC as applied to the
spherical tank level system. The FMRLC uses a
learning mechanism that emphasizes
a) Observes data from a fuzzy control system (i.e.
r(kT) and y(kT).
b) Characterizes its present performance, and
c) automatically synthesizes and/or adjusts the fuzzy
controller using rule base modifier so that some prespecified performance objectives are satisfied.
In general, the reference model, which
characterizes the desired performance of the system,
can take any form (linear or nonlinear equations,
transfer functions, numerical values etc.). In the case
of the level process reference model is shown in the
figure.3.
An additional fuzzy system is developed
called “fuzzy inverse model” which adjusts the
centers of the output membership functions of the
fuzzy controller, which still controls the process,
This fuzzy system acts like a second controller,
which updates the rule base of the fuzzy controller by
acting upon the output variable (its membership
functions centers). The output of the inverse fuzzy
model is an adaptation factor p(kT) which is used by
the rule base modifier to adjust the centers of the
output membership functions of the fuzzy controller.
The adaptation is stopped when p(kT) gets very small
and the changes made to the rule base are no longer
significant. The fuzzy controller used by the FMRLC
structure is the same as the one developed in the
previous section.
The fuzzy inverse model has a similar
structure to that of the controller (the same rule base,
membership
functions,
inference
engine,
fuzzification and defuzzification interfaces. See
section 3.1).
The inputs of the fuzzy inverse model are
ye(kT) = ym(kT) – y(kT)
(10)
yc(kT) = ( ye(kT) – ye(KT-T) ) / T
(11)
and the output variable is the adaptation factor p(kT).
The rule base modifier adjusts the centers of
the output membership functions in two stages
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The pair (i, j) will determine the activated rule. We
denoted by i and j the i-th, respectively the j-th
membership function for the input fuzzy variables
error and change in error.
2. The centers of the output membership functions,
which were found in the active set of rules
determined earlier, are adjusted. The centers of
these membership functions (bl) at time kT will
have the following value
b (kT ) =b (kT- T) +p(kT)
(13)
We denoted by l the consequence of the rule
introduced by the pair (i, j).
The centers of the output membership
functions, which are not found in the active set of
rules (i, j), will not be updated. This ensures that only
those rules that actually contributed to the current
output y(kT) were modified. We can easily notice that
only local changes are made to the controller’s rule
base.
For better learning control a larger number
of output membership functions (a separate one for
each input combination) would be required. This way
a larger memory would be available to store
information. Since the inverse model updates only
the output centers of the rules which apply at that
time instant and does not change the outcome of the
other rules, a larger number of output membership
functions would mean a better capacity to map
different working the adjustments it made in the past
for a wider range of specific conditions. This
represents an advantage for this method since time
consuming re-learning is avoided. At the same time
this is one of the characteristics that differences
learning control from the more conventional adaptive
control.
IV.
HYBRID FUZZY P+ID CONTROLLER
For implementing the block diagram of
fuzzy P+ID controller referred Figure 4 only one
supplementary parameter has to be attuned.
Consequently, the physical tuning time of the
controller can be greatly reduced in comparison with
a conventional fuzzy logic controller.
r(t)
+
_
Fuzzy P
Controller
+
+
y(t)
u(t)
Plant
+
I Controller
D Controller
Figure 4 Block diagram of hybrid fuzzy P+ID
controller
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4. S. Ramesh et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.619-623
1. DESIGN OF HYBRID FUZZY P+ID CONTROLLER
Design of fuzzy P+ID controller is
constructed by replacing the conventional
proportional term with the fuzzy one, we propose the
following formula:
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To analyze the FMRLC controller for the
both the cases, a performance analysis in terms of
ISE, IAE is made and their values are tabulated in
Table 2 and Table 3
Table 2. Performance index for servo response
K P 0.6 K P (crit )
(14)
2K P
KI
T (crit )
(15)
K D (T 2) K P K I T 2
(16)
RESULTS AND DISCUSSION
In this section, the simulation results for
Spherical tank level system are presented to illustrate
the performance of the FMRLC control algorithm.
The differential equation(6) is derived in the section
2 are considered for this simulation study. Here,
simulations are analyzed in two cases. Initially, the
spherical tank is maintained at 35 % of its maximum
level and a 5% step signal is applied to the process
with FMRLC control algorithm and the responses are
recorded in Figure 5. Similarly, a same procedure is
applied to hybrid fuzzy P+ID and Conventional
fuzzy for the comparative analysis. The performance
indices in terms of ISE and IAE are calculated and
summarized in the table 2
In order to validate the FMRLC algorithm,
the different operating points (50% and 60 %) are
also considered and output responses are recorded in
the Figure 6 and Figure 7 and their performance
indices are given in the same table2.
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Conv-fuzzy
ISE
IAE
35%
122.2
85.63
347.9
141.1
686.6
299.8
143.3
94.59
344.1
144
701.3
310.3
60%
V.
Hyb-fuzzy
ISE IAE
50%
For determination of their parameters. We
select the parameter KD of the derivative controller
by using the sufficient stability condition [5] instead
of the Ziegler and Nichols’ formula. This result
implies that stability of a system does not change
after the conventional PID controller is replaced by
the fuzzy P+ID controller without modifying any
PID-type controller parameter.
The selection of the sampling period T is
made in two stages: 1) during the loop design and 2)
during the controller design. The observed rule [6]
suggests that the sampling frequency must be from 4
to 20 times the bandwidth of the closed-loop system.
For the controller design, T should be enhanced to be
greater than the sum of the error computation time,
the digital analogue converter (DAC) and analogue
digital converter (ADC) conversion times, and the
zero-order hold delay time.
The necessary conditions for selection of T is given
below,
1) if T is greater, the stability regions are smaller;
2) Large T implies small cost;
3) Large T results in large conversion times of the
DAC’s and ADC’s (i.e., to smaller cost);
4) Small T allows good system performance in the
presence of noise.
FMRLC
ISE IAE
167.9
129.3
341.5
146.3
711
316.7
Secondly, a load disturbance is applied to the
FMRLC algorithm under the same operating points
and responses are traced in Figure 8 to figure 10. In
the case of servo regulatory, the process is
maintained at 35 % of its maximum level and 5%
step signal is applied to the process and the
disturbance is given at new steady state level (10%
of given step change) disturbance at 700 sec instant.
Table 3.Performance index for servo regulatory
response
FMRLC
Hyb-fuzzy
Conv-fuzzy
ISE
IAE
ISE
IAE
ISE
IAE
35%
129.2
93.11
351.9
154.9
686.3
297
50%
153.8
118.8
348.5
157.5
700.6
306.6
60%
170.2
132.9
346.2
160.1
710.1
312.5
The performance indices for all the three
controllers are computed and tabulated in the table 3.
Also the different operating points (50% and 60 %)
are also carried out and their performances indices
are summarized in the same table 3.It is observed
that, the FMRLC algorithm gives an excellent
performance than the other two.
From the table 2 and 3, it is observed that FMRLC
control algorithm provides satisfactory performance
in the servo and servo regulatory cases than the other
control strategies
VI.
CONCLUSION
This paper, a Fuzzy Model Reference
Learning Control (FMRLC) is applied in to a non
linear spherical tank system. Simulation runs are
carried out by considering the FMRLC algorithm,
hybrid fuzzy and conventional fuzzy controller in a
closed loop. The results clearly indicate that the
incorporation of FMRLC in the control loop in
spherical tank system provides a superior tracking
performance than the hybrid fuzzy P+ID and
conventional fuzzy controller.
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5. S. Ramesh et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.619-623
41
66
40
65
39
64
63
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
37
Level (%)
Level (%)
38
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
62
36
61
35
60
34
33
500
59
550
600
650
700
750
800
850
900
950
58
500
1000
550
600
Time (sec)
Figure 5. Servo Response of spherical tank at 35%
operation point
56
54
Level (%)
53
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
52
51
50
49
48
47
550
600
650
700
750
Time (sec)
800
850
900
950
1000
Figure 6. Servo Response of spherical tank at 50%
operation point
[2]
[3]
66
65
[4]
64
Level (%)
63
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
62
61
60
[5]
59
58
57
500
550
600
650
700
750
Time (sec)
800
850
900
950
1000
Figure 7.Servo Response of spherical tank at 60%
operation point
[6]
41
[7]
40
Level (%)
39
38
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
37
36
[8]
35
34
500
550
600
650
700
750
Time (sec)
800
850
900
950
1000
Figure 8. Regulatory Response of Spherical tank at
35% operating point
[9]
57
56
55
54
[10]
53
FMRLC
CONV-FUZZY
HYB-FUZZY
SET POINT
52
51
50
49
48
500
700
750
Time (sec)
800
850
900
950
1000
Figure 10. Regulatory Response of Spherical tank at
60% operating point
[1]
55
46
500
650
REFERENCE
57
Level (%)
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550
600
650
700
750
800
850
900
950
1000
Time (sec)
Figure 9. Regulatory Response of Spherical tank at
50% operating point
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