Fuzzy Logic Control System and its Applications

2012

1993

International journal of research in engineering, 2019

As the complexity of a system increases, it becomes more difficult and eventually impossible to make a precise statement about its behavior, eventually arriving at a point of complexity where the fuzzy logic method born in humans is the only way to get at the problem. Fuzzy logic is used in system control and analysis design, because it shortens the time for engineering development and sometimes, in the case of highly complex systems, is the only way to solve the problem.. Although most of the time we think of fuzzy logic "control" as having to do with controlling a physical system, there is no such limitation in the concept as initially presented by Dr. Zadeh. Fuzzy logic can apply also to economics, psychology, marketing, weather forecasting, biology, and politics and to any large complex system

International Journal of Scientific Research in Science and Technology, 2021

This Paper give introduction to Fuzzy Logic and Various application in different branch of Engineering and Research. Fuzzy Logic is Applied branch of Mathematics in which Lots of research is taking place. Fuzzy Logic works on "if.....then.....".Fuzzy Logic gives the idea that members are not restricted to T or F definition. The concept of Fuzzy Logic is used in the various fields as Artificial Intelligence, Aerospace, Automotive Business, Defence, Electronics, Finance, Industrial Sector, Marine Sector, Manufacturing, Medical, Securities, Transportation Pattern Recognition and Classification, Psychology, etc. The whole field of Engineering as civil Engineering, Mechanical Engineering, Industrial Engineering real Reliability theory, Robotics, Computer Engineering is broad to be covered here in a comprehensive way.

Index Terms: DC Motor, Fuzzy Logic, Speed Control.

Journal of Science and Medicine in Sport, 2001

In today's fast paced world of increasing and innovative new technology, fuzzy logic is a practical mathematical addition to classic Boolean logic. We can see its applications in many fields of science and engineering. This paper gives a general overview with a large bibliography, on many such applications to target tracking, pattern recognition, robotics, power systems, controller design, chemical engineering, biomedical engineering, vehicular technology, economy management as well as decision making, communications and networking, electronic engineering, civil engineering, sensor technology, and industry

This paper deals with Fuzzy Logic and the Real World Applications. Fuzzy logic has rapidly become one of the most successful of today's technologies for developing sophisticated control systems. The reason for which is very simple. Fuzzy logic starts with and builds on a set of user-supplied human language rules. The fuzzy system converts these rules to their mathematical equivalents. This simplifies the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. It provides both an intuitive method for describing systems in human terms and automates the conversion of those system specifications into effective models.

Fuzzy logic has emerged as a very powerful tool in dealing with complex problems. Recently the role of inference in handling uncertainty in engineering applications is gaining importance. Engineers and scientists are generally confronted with problems which are impossible to solve numerically using traditional mathematical rules. By making use of fuzzy logic , one can characterize and control a system whose model is not known or is ill- defined [11]. Fuzzy theory has the capability to capture the impreciseness of linguistic terms in statements of natural language. this provided with a greater capability to model human common-sense reasoning and decision making [14]. The idea of fuzzy logic was propounded by Lotfi Zadeh in 1965. His later works ‘A Rationale for Fuzzy Control’ and ‘Linguistic Approach’ (in 1972 and 1973 respectively) motivated the pioneering work done by other scientists. The first trial of fuzzy control was conducted by Mamdani on a laboratory steam engine (1974). In the 70’s this motivated the researchers to develop a series of applications of fuzzy control [3]. the work on derivation of fuzzy control rules (1983) was carried out by Takagi and Sugeno. Since mideighties research has been directed towards incorporating fuzzy at the hardware level itself [1], [7]. [11]. The work on fuzzy chip done by Togai Watanabe (1985) in an important milestone in this direction. An attempt has been made in this paper to inspire the reader to appreciate the use of fuzzy logic as a new logical tool that is instrumental in handling problems with ambiguities and where the information is imprecise and non numerical. the in adequacy of traditional Boolean logic to emulate the human thinking has also been highlighted.

IEEE Expert / IEEE Intelligent Systems, 2007

Automated versions of a mass-produced vehicle use fuzzy logic techniques to both address common challenges and incorporate human procedural knowledge into the vehicle control algorithms. In-vehicle computing has been largely relegated to auxiliary tasks such as regulating cabin temperature, opening doors, and monitoring fuel, oil, and battery-charge levels. However, computers are increasingly assuming driving-related tasks in some commercial models. Among those tasks are: maintaining a reference velocity or keeping a safe distance from other vehicles; improving night vision with infrared cameras; and building maps and providing alternative routes