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.
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 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.
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.
PI or PID based control system are widely used in control process industries because of their implantation is simple and they assure acceptable performance for industrial processes and their can be tuned manually by industrial operators. However, these controllers provide better performance only at given set of operating range and they need to be redefine if there is change in operating conditions. Further, the conventional controller performance is not up to the expected level for nonlinear and dead time processes. In the present industrial scenario, all the processes require automatic control with good performance over a wide operating range with simple design and implementation. This provides us the motivation for development of Fuzzy logic based process control system which can control process efficiently for all practical operating conditions. The fuzzy logic has been used to control the air pressure in the vessel using matlab as programming platform and the results are compared with that PID control. It has been demonstrated that fuzzy logic based control system is more accurate than the PID control system.
Biological immune system (BIS) is a special type of control system that has strong robustness and self-adaptability. This thesis report proposes an artificial immune system algorithm to develop an immune controller. The idea of immune controller is adopted and derived from biological vertebrate immune system, mimicking and imitating of biological immune system which is better known as the artificial immune system. This book show how proposes to apply and implement the algorithm of the artificial immune system (AIS) to develop an immune controller (IC) for three tank level control. There are various models of artificial immune controller (AIC). The most suitable for their particular application is selected. The selected artificial immune controller has the resemblance of a PID controller. The immune controller enhances the performance and stability of the system.
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.
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.
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
This book explains the basic principle underlying in system/model identification.The model-based control design process involves modeling the plant to be controlled, analyzing and synthesizing a controller for the plant, simulating the plant and controller, and deploying the controller here we concentrated only on designing the controller.A comprehensive chapter which clearly explain about model structures,sugar evaporator,Fuzzy controller.A detailed work and performance analysis on sugar evaporator with conventional controllers P, PI, PID & Fuzzy logic Controller results were displayed and implemented.
There has been a significant increase in the application of Artificial Intelligence(AI) to many practical problems in recent years. Fuzzy Logic has been one of the major tools in the application of AI. This book involves the designing of an Anti-Locking Braking System that controls the speed of any vehicle and hence can be used for transportation applications. Fuzzy Logic controller provides an alternative to controller since it is a good tool for control of systems that are difficult in modeling. Audience for this book This book is intended for the following audience: * Computer Science and Engineering (CSE), Information Technology, Electronics and Communication Engineering students who would like to specialize in Embedded Systems Automotive Electronics). The book should be appropriate for third year students who do have a basic knowledge of computer hardware and software. This book can also be used for the final year students for their User Defined Problem (UDP) * Engineers who have so far worked on systems hardware and who have to move more towards software of embedded systems. This book should provide enough background to understand relevant technical publication
Fuzzy logic technics are not always fuzzy in technology because they are being used in electrical power stability studies to make life better. This happens because real time mathematical analysis can be substituted with real life decision making process using Fuzzy logic technics. The motivation to use fuzzy logic technics is based in the fact that many everyday technologies in the living room such as air conditioning,refridgerators, control of light and microwaves have been developed using fuzzy logic technics. Above all it has been proved by Japanese engineers that trains controlled using Fuzzy logic technics have better and smooth ride for passengers than those controlled using other methods.
The Book Modeling Quality of Service (QoS) in a Telecommunications Network using Neuro-fuzzy logic, this is generally the analysis of GSM theory as a telecommunications network and ANFIS as a non-linear modeling tool. The ANFIS-based model developed has demonstrated that it can be used to model Quality of Service using Logical Control and Traffic Channels key performance indicators, due to its degree of consistency. The statistical analysis has further ascertained and confirmed the accuracy of the ANFIS-based model developed.
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 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