Petri nets are considered to be the alternative approach for analysis, design and implementation of DES. However, the prospect of uncertain and vague information still creates a problem. Hence, to handle the uncertainty, fuzzy logic is integrated into Petri nets to form Fuzzy Automation Petri nets as a modeling tool to handle these uncertainties. The use of Fuzzy Automation Petri nets (FAPN) demands a valid translation of the formalism to Ladder Logic Diagrams for implementation. This is achieved using Token Passing Methodology. This work investigates the use of Fuzzy Petri nets in supervisory control and suggests a modified and improved version called Fuzzy Automation Petri net (FAPN) as a modeling tool. It presents a systematic approach to the synthesis of Fuzzy Petri net based supervisor for the forbidden state problem using supervisory design procedure. The controlled model of the system can be constructed from this FAPN net structure. The implementation is using Flexible Manufacturing System as an example of DES.

This study is aimed at characterization of Fuzzy logic control based system with varying span of Member Function by establishing region of stable operation for different cases using range provided by 'k' for setting the span for desired performance.The performed work may be used as reference, by designers for designing a Fuzzy logic based control system depending upon the requirement of desired application.

With every year air conditioning units are increasing rapidly all over the world and air conditioning system has not only become integral part of every institution but also of our lives. The survey of this system shows that air conditioning system consumes nearly 50% of the total energy intake of a building. In air conditioning system, compressor unit consumes most of the energy. Different control techniques can be used to control the compressor speed. This book therefore provides the use of two intelligent control techniques to control the compressor speed and make air conditioning system energy efficient. The techniques used are fuzzy logic and neuro-fuzzy. This book also provides the comparison of both the techniques. This book should be helpful for professionals in artificial intelligence, or anyone else who may seek to work in Fuzzy , Neuro-fuzzy or related techniques. This book would also be helpful to students for study of these techniques.

The exchange of sensitive information in many systems over a network can be manipulated by unauthorized access. Opacity is a property to investigate security and privacy problems in such systems. Opacity characterizes whether a secret information of a system can be inferred by an unauthorized user. One approach to verify security and privacy properties using opacity problem is to model the system that may leak confidential information as a discrete event system. We describe and analyze the complexity of opacity in systems that are modeled as a discrete event system with partial observation mapping. We define three types of opacity: strong opacity, weak opacity, and no opacity. Strong Opacity describes the inability for the system’s observer to know what happened in a system. On the other hand, No-opacity refers to the condition where there is no ambiguity in the system behavior.

Fuzzy controllers are used to control consumer products, such as washing machines, video cameras, and rice cookers, as well as industrial processes, such as cement kilns, underground trains, and robots. Fuzzy control is a control method based on fuzzy logic. Just as Fuzzy logic can be described simply as “computing with words rather than numbers’’ and Fuzzy control can be described simply as “control with sentences rather than equations’’. A Fuzzy controller can include empirical rules, and that is especially useful in operator controlled plants.This is the world of automation. The majority of the products allow actions to be automatically triggered by events. The Performance of a SCADA system can be much improved using a fuzzy logic controller based SCADA in industries. This book describes design of fuzzy logic based SCADA Systems using MATLAB fuzzy logic toolbox.This Book is useful for Engineers and Research Scholars in the field of Electrical & Power Engineering.

Continuous stirred tank reactor is a typical chemical reactor with complex non linear dynamic characteristics. There has been considerable interest in its state estimation and real time control based on mathematical modeling. However, the lack of understanding of the dynamics of the process, the highly sensitive and non linear behavior of the reactor, has made it difficult to develop the precise mathematical modeling of the system. Efficient control of the product concentration in CSTR can be achieved only through accurate model. Here attempts are made to ease the modeling difficulties using AI techniques such as Fuzzy logic. Simulation results demonstrate the effectiveness of Fuzzy logic control technique. The system is a stirred tank reactor with two flows of liquid enter the system and another flow exits the tank with the formation of product. Simulink was employed to design a model for this system in the simulation environment. This work is aimed for utilization by researchers, industrialists’ and students. Furthermore it will be especially relevant and useful for the students of Electrical Engg. and Chemical Engg. for carrying out research in the area of simulation of CSTR.

The emergence of computational intelligence technology inspired by biological and human intelligence is one of the most exciting and important fields in engineering . It is expected that these technologies like fuzzy logic , will play a significant role in the development of intelligent robotic systems , machine systems , and mechatronics systems . In this work ; a Fuzzy Logic Controller is presented to control the motion of a robotic arm and avoid the obstacles existed in its mission road ,using a real platform robotic arm in combination with a vision system . This work involves constructing an integrated and autonomic MATLAB program. It could be applicable for any robotic arm . It depends on a new approach in analyzing the robotic environment videos acquired by a fixed webcam. The approach uses colors to detect and recognize the changeable locations and objects’ dimensions for each of the robot’s end-effector , the goal , and the obstacles .

This research work is mainly focused on suspending the steel ball without any mechanical support in desired position and how the Magnetic Levitation System works in presence of disturbance with help of an efficient controller.The tracking performance and robustness is also checked for this system. For tracking, two type of reference trajectory are modelled. One is sine wave and other is a set of constant point varying at different levels. Lastly for robust performance, disturbance is applied in MLS.For this task we have designed Interval Type-2 Fuzzy Logic Controller (IT2FLC), Interval Type-2 Single Input Fuzzy Logic Controller (IT2SIFLC), Interval Type-2 Fuzzy Sliding Mode Controller (IT2FSMC) based on theory of type-2 fuzzy logic systems. Uncertainty is an inherent part of intelligent systems used in real world applications. Conventional controllers can not fully handle the uncertainties present in real-time systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us an extra degree of freedom. At last The designed controller’s performance is compared with the feedback linearization control.

Fuzzy Logic Control (FLC) is an important alternative method to the conventional Proportional, Integral, and Derivative (PID) control method for use in nonlinear systems. This book, therefore, highlight the feasibility and effectiveness of fuzzy logic control in application to mathematical models of two basic types of steam turbines; straight expansion and single-automatic extraction turbines. The derived performance of the developed mathematical models, in terms of input/output duty variables without mean of control, is found to be in a good agreement with the actual performance of typical steam turbines with practical technical data and operating conditions. Model components exhibit nonlinear behavior. A comparison is made between the efficiency of Fuzzy Logic Control and the conventional PID control for the dynamic responses of the closed loop drive system. In case of straight expansion steam turbines, the control task is either speed or backpressure control. In case of single extraction steam turbines, the control task is to maintain both speed and extraction pressure of the turbine constants. This is done in presence of severe changes in load and/or steam demand conditions.

This book presents the details theory and applications of Fuzzy sets,fuzzy systems,membership functions & controller designed. A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True ) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers. A fuzzy control method for automatic steering and a method for line tracking are conveyed in this article. The principal for fuzzy control steering and the construction of fuzzy controller are described in detail.For Example,A vehicle is refitted with a storage battery car. Navigation control system is developed based on digital compass and other sensors. The vehicle acquires the location information using the fuzzy control steering and line tracking method. Test results indicated that the navigation lateral error was less than 0.3m when the robot ran following the predefined line route. Finally, a power system network with UPFC has been considered & A POD controller has designed by using Fuzzy Logic to improve the damping oscillation of power system network.

Information retrieval system is heart of information system. The primary purpose of establishing an information retrieval system lies in assisting the users to effectively acquire drsired information. That is, users' query must be properly understood and answered. The present work falls in the area of information retrieval and to be more specific : query processing of information retrieval. This has been influenced by the limitation and disadvantages of the commercially available Boolean logic retrieval model. The limitation and disadvantages of the query processing of the Boolean logic model have been pointed out and logical solution using fuzzy set theory and fuzzy logic have been presenteted.

The research presented examines the construction of a fuzzy logic controller for complex nonlinear system by control system decomposition into hierarchical fuzzy logic sub-systems. Evolutionary algorithm based methods are proposed to determine the control system for the hierarchical fuzzy system (HFS). Different HFS topologies for a given dynamical system (such as the inverted pendulum system) are investigated. For the inverted pendulum system, a single layer, two layered, three layered, and four layered HFS, with different variable input configuration is investigated. Effects of different input configurations on controller performance are examined and discussed. A new evolutionary algorithm based compositional method is proposed to control system over the whole set of user-defined initial conditions. The method addresses directly the problem of controlling the dynamical system from specific, user-defined initial conditions. The multiobjective evolutionary algorithm (MOEA) based compositional method is developed and tested on the example of the inverted pendulum system.

Over the past few decades there has been massive increase in wireless applications usage and subsequently in allocation of available spectrum. The available spectrum is getting scarce because of this surge in wireless link usage. The scarcity is not only the physical shortage of spectrum but there is an inefficient and inflexible spectrum usage. In order to address the problem of underutilization of spectrum the cognitive radio network (CRN) technology has implemented. According to CRN technology radio users could have the cognitive capacity and adaptability according to different transmission environments what makes them able to transmit through the spectrum holes dynamically and opportunistically. Since in CRN the effective decision making plays a major role to maintain the QoS towards the users, we introduced the effective decision making systems here. In this book we combine Fuzzy logic Mathematical modeling tools with CRN for efficient spectrum usage. To challenge our analysis with real time conditions, we validate the system in multiple propagation environments and channel fading conditions. We implement OFDM technology in CRN to improve the data rate in emergency situation

In this Book, a modern FPGA card (Spartan-3A, Xilinx Company) is used to realized a novel Fuzzy- PID control strategy on a complex system; a three- phase induction motor (squirrel cage type) is selected as a case study. The Fuzzy logic control demonstrates a good performance. Furthermore, Fuzzy logic offers the advantage of a faster design, and emulation of human control strategies. Also, Fuzzy control works well for high-order and nonlinear and shows the efficiency over the PID controller. The proposed controller and the pulse width modulator (PWM) inverter algorithm which have been built in FPGA have resulted in a fast speed response and a good stability in controlling the three-phase induction motor. For comparison purpose, two widely used controllers are realized using the same FPGA kit: PID and Fuzzy. Simulations are performed using MATLAB/SIMULINK (R2009a) with varying load and speed conditions. The Fuzzy-PID control strategy outperformed both PID and Fuzzy controllers. This book will be especially useful to academics, researchers, and practitioners.

The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications.*Introduces cutting-edge control systems to a wide readership of engineers and students*The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies*Learn to use VHDL in real-world applications

## fuzzy logic supervisory control of discrete event system в наличии / купить интернет-магазине

## Fuzzy Logic Supervisory Control of Discrete Event System

Petri nets are considered to be the alternative approach for analysis, design and implementation of DES. However, the prospect of uncertain and vague information still creates a problem. Hence, to handle the uncertainty, fuzzy logic is integrated into Petri nets to form Fuzzy Automation Petri nets as a modeling tool to handle these uncertainties. The use of Fuzzy Automation Petri nets (FAPN) demands a valid translation of the formalism to Ladder Logic Diagrams for implementation. This is achieved using Token Passing Methodology. This work investigates the use of Fuzzy Petri nets in supervisory control and suggests a modified and improved version called Fuzzy Automation Petri net (FAPN) as a modeling tool. It presents a systematic approach to the synthesis of Fuzzy Petri net based supervisor for the forbidden state problem using supervisory design procedure. The controlled model of the system can be constructed from this FAPN net structure. The implementation is using Flexible Manufacturing System as an example of DES.

## Performance Analysis of Fuzzy Logic Controller based Control System

This study is aimed at characterization of Fuzzy logic control based system with varying span of Member Function by establishing region of stable operation for different cases using range provided by 'k' for setting the span for desired performance.The performed work may be used as reference, by designers for designing a Fuzzy logic based control system depending upon the requirement of desired application.

## Fuzzy Logic and Neuro Fuzzy Algorithms for Air Conditioning System

With every year air conditioning units are increasing rapidly all over the world and air conditioning system has not only become integral part of every institution but also of our lives. The survey of this system shows that air conditioning system consumes nearly 50% of the total energy intake of a building. In air conditioning system, compressor unit consumes most of the energy. Different control techniques can be used to control the compressor speed. This book therefore provides the use of two intelligent control techniques to control the compressor speed and make air conditioning system energy efficient. The techniques used are fuzzy logic and neuro-fuzzy. This book also provides the comparison of both the techniques. This book should be helpful for professionals in artificial intelligence, or anyone else who may seek to work in Fuzzy , Neuro-fuzzy or related techniques. This book would also be helpful to students for study of these techniques.

## Opacity Of Discrete Event Systems: Analysis And Control

The exchange of sensitive information in many systems over a network can be manipulated by unauthorized access. Opacity is a property to investigate security and privacy problems in such systems. Opacity characterizes whether a secret information of a system can be inferred by an unauthorized user. One approach to verify security and privacy properties using opacity problem is to model the system that may leak confidential information as a discrete event system. We describe and analyze the complexity of opacity in systems that are modeled as a discrete event system with partial observation mapping. We define three types of opacity: strong opacity, weak opacity, and no opacity. Strong Opacity describes the inability for the system’s observer to know what happened in a system. On the other hand, No-opacity refers to the condition where there is no ambiguity in the system behavior.

## Design of Fuzzy Logic Based SCADA System

Fuzzy controllers are used to control consumer products, such as washing machines, video cameras, and rice cookers, as well as industrial processes, such as cement kilns, underground trains, and robots. Fuzzy control is a control method based on fuzzy logic. Just as Fuzzy logic can be described simply as “computing with words rather than numbers’’ and Fuzzy control can be described simply as “control with sentences rather than equations’’. A Fuzzy controller can include empirical rules, and that is especially useful in operator controlled plants.This is the world of automation. The majority of the products allow actions to be automatically triggered by events. The Performance of a SCADA system can be much improved using a fuzzy logic controller based SCADA in industries. This book describes design of fuzzy logic based SCADA Systems using MATLAB fuzzy logic toolbox.This Book is useful for Engineers and Research Scholars in the field of Electrical & Power Engineering.

## Fuzzy logic control of Continuous Stirred Tank Reactor (CSTR)

Continuous stirred tank reactor is a typical chemical reactor with complex non linear dynamic characteristics. There has been considerable interest in its state estimation and real time control based on mathematical modeling. However, the lack of understanding of the dynamics of the process, the highly sensitive and non linear behavior of the reactor, has made it difficult to develop the precise mathematical modeling of the system. Efficient control of the product concentration in CSTR can be achieved only through accurate model. Here attempts are made to ease the modeling difficulties using AI techniques such as Fuzzy logic. Simulation results demonstrate the effectiveness of Fuzzy logic control technique. The system is a stirred tank reactor with two flows of liquid enter the system and another flow exits the tank with the formation of product. Simulink was employed to design a model for this system in the simulation environment. This work is aimed for utilization by researchers, industrialists’ and students. Furthermore it will be especially relevant and useful for the students of Electrical Engg. and Chemical Engg. for carrying out research in the area of simulation of CSTR.

## Fuzzy logic control of a robotic manipulator for obstacles avoidance

The emergence of computational intelligence technology inspired by biological and human intelligence is one of the most exciting and important fields in engineering . It is expected that these technologies like fuzzy logic , will play a significant role in the development of intelligent robotic systems , machine systems , and mechatronics systems . In this work ; a Fuzzy Logic Controller is presented to control the motion of a robotic arm and avoid the obstacles existed in its mission road ,using a real platform robotic arm in combination with a vision system . This work involves constructing an integrated and autonomic MATLAB program. It could be applicable for any robotic arm . It depends on a new approach in analyzing the robotic environment videos acquired by a fixed webcam. The approach uses colors to detect and recognize the changeable locations and objects’ dimensions for each of the robot’s end-effector , the goal , and the obstacles .

## Tracking Performance Of Maglev System Using Type-2 Fuzzy Logic Control

This research work is mainly focused on suspending the steel ball without any mechanical support in desired position and how the Magnetic Levitation System works in presence of disturbance with help of an efficient controller.The tracking performance and robustness is also checked for this system. For tracking, two type of reference trajectory are modelled. One is sine wave and other is a set of constant point varying at different levels. Lastly for robust performance, disturbance is applied in MLS.For this task we have designed Interval Type-2 Fuzzy Logic Controller (IT2FLC), Interval Type-2 Single Input Fuzzy Logic Controller (IT2SIFLC), Interval Type-2 Fuzzy Sliding Mode Controller (IT2FSMC) based on theory of type-2 fuzzy logic systems. Uncertainty is an inherent part of intelligent systems used in real world applications. Conventional controllers can not fully handle the uncertainties present in real-time systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us an extra degree of freedom. At last The designed controller’s performance is compared with the feedback linearization control.

## Feasibility Of Fuzzy Logic Control For Steam Turbine Systems

Fuzzy Logic Control (FLC) is an important alternative method to the conventional Proportional, Integral, and Derivative (PID) control method for use in nonlinear systems. This book, therefore, highlight the feasibility and effectiveness of fuzzy logic control in application to mathematical models of two basic types of steam turbines; straight expansion and single-automatic extraction turbines. The derived performance of the developed mathematical models, in terms of input/output duty variables without mean of control, is found to be in a good agreement with the actual performance of typical steam turbines with practical technical data and operating conditions. Model components exhibit nonlinear behavior. A comparison is made between the efficiency of Fuzzy Logic Control and the conventional PID control for the dynamic responses of the closed loop drive system. In case of straight expansion steam turbines, the control task is either speed or backpressure control. In case of single extraction steam turbines, the control task is to maintain both speed and extraction pressure of the turbine constants. This is done in presence of severe changes in load and/or steam demand conditions.

## Fuzzy Logic Controller

This book presents the details theory and applications of Fuzzy sets,fuzzy systems,membership functions & controller designed. A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True ) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers. A fuzzy control method for automatic steering and a method for line tracking are conveyed in this article. The principal for fuzzy control steering and the construction of fuzzy controller are described in detail.For Example,A vehicle is refitted with a storage battery car. Navigation control system is developed based on digital compass and other sensors. The vehicle acquires the location information using the fuzzy control steering and line tracking method. Test results indicated that the navigation lateral error was less than 0.3m when the robot ran following the predefined line route. Finally, a power system network with UPFC has been considered & A POD controller has designed by using Fuzzy Logic to improve the damping oscillation of power system network.

## Fuzzy Logic Based Information Retrieval System

Information retrieval system is heart of information system. The primary purpose of establishing an information retrieval system lies in assisting the users to effectively acquire drsired information. That is, users' query must be properly understood and answered. The present work falls in the area of information retrieval and to be more specific : query processing of information retrieval. This has been influenced by the limitation and disadvantages of the commercially available Boolean logic retrieval model. The limitation and disadvantages of the query processing of the Boolean logic model have been pointed out and logical solution using fuzzy set theory and fuzzy logic have been presenteted.

## Analysis of the hierarchical fuzzy control

The research presented examines the construction of a fuzzy logic controller for complex nonlinear system by control system decomposition into hierarchical fuzzy logic sub-systems. Evolutionary algorithm based methods are proposed to determine the control system for the hierarchical fuzzy system (HFS). Different HFS topologies for a given dynamical system (such as the inverted pendulum system) are investigated. For the inverted pendulum system, a single layer, two layered, three layered, and four layered HFS, with different variable input configuration is investigated. Effects of different input configurations on controller performance are examined and discussed. A new evolutionary algorithm based compositional method is proposed to control system over the whole set of user-defined initial conditions. The method addresses directly the problem of controlling the dynamical system from specific, user-defined initial conditions. The multiobjective evolutionary algorithm (MOEA) based compositional method is developed and tested on the example of the inverted pendulum system.

## Fuzzy Logic based Power Control Techniques in Cognitive Radio Networks

Over the past few decades there has been massive increase in wireless applications usage and subsequently in allocation of available spectrum. The available spectrum is getting scarce because of this surge in wireless link usage. The scarcity is not only the physical shortage of spectrum but there is an inefficient and inflexible spectrum usage. In order to address the problem of underutilization of spectrum the cognitive radio network (CRN) technology has implemented. According to CRN technology radio users could have the cognitive capacity and adaptability according to different transmission environments what makes them able to transmit through the spectrum holes dynamically and opportunistically. Since in CRN the effective decision making plays a major role to maintain the QoS towards the users, we introduced the effective decision making systems here. In this book we combine Fuzzy logic Mathematical modeling tools with CRN for efficient spectrum usage. To challenge our analysis with real time conditions, we validate the system in multiple propagation environments and channel fading conditions. We implement OFDM technology in CRN to improve the data rate in emergency situation

## Fuzzy Logic Speed Controllers Using FPGA Technique

In this Book, a modern FPGA card (Spartan-3A, Xilinx Company) is used to realized a novel Fuzzy- PID control strategy on a complex system; a three- phase induction motor (squirrel cage type) is selected as a case study. The Fuzzy logic control demonstrates a good performance. Furthermore, Fuzzy logic offers the advantage of a faster design, and emulation of human control strategies. Also, Fuzzy control works well for high-order and nonlinear and shows the efficiency over the PID controller. The proposed controller and the pulse width modulator (PWM) inverter algorithm which have been built in FPGA have resulted in a fast speed response and a good stability in controlling the three-phase induction motor. For comparison purpose, two widely used controllers are realized using the same FPGA kit: PID and Fuzzy. Simulations are performed using MATLAB/SIMULINK (R2009a) with varying load and speed conditions. The Fuzzy-PID control strategy outperformed both PID and Fuzzy controllers. This book will be especially useful to academics, researchers, and practitioners.

## Neural and Fuzzy Logic Control of Drives and Power Systems

The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications.*Introduces cutting-edge control systems to a wide readership of engineers and students*The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies*Learn to use VHDL in real-world applications