Minggu, 18 Oktober 2015

creator of fuzzy logic

Lotfali Askar Zadeh (/ˈzɑːdeɪ/; Azerbaijani: Lütfəli Rəhimoğlu Əsgərzadə;born February 4, 1921), better known as Lotfi A. Zadeh, is a mathematician, computer scientist, electrical engineer, artificial intelligence researcher and professor emeritus of computer science at the University of California, Berkeley.

He is best known for proposing the fuzzy mathematics consisting of those fuzzy related concepts: fuzzy sets, fuzzy logic,fuzzy algorithms, fuzzy semantics, fuzzy languages, fuzzy control,fuzzy systems, fuzzy probabilities, fuzzy events, and fuzzy information.

Zadeh was born in Baku, Azerbaijan SSR, as Lotfi Aliaskerzadeh, to an Iranian Azerbaijani father from Ardabil, Rahim Aleskerzade, who was a journalist on assignment from Iran, and a Russian Jewish mother, Fanya Korenman, who was a pediatrician from Odessa. The Soviet government at this time courted foreign correspondents, and the family lived well while in Baku. Zadeh attended elementary school for three years there, which he has said "had a significant and long-lasting influence on my thinking and my way of looking at things."

 In 1931, when Zadeh was ten years old, his family moved to Tehran in Iran, his father's homeland. Zadeh was enrolled in Alborz College, which was a Presbyterian missionary school, where he was educated for the next eight years, and where he met his future wife, Fay.Zadeh says that he was "deeply influenced" by the "extremely decent, fine, honest and helpful" missionaries from the United States who ran the college. "To me they represented the best that you could find in the United States – people from the Midwest with strong roots. They were really 'Good Samaritans' – willing to give of themselves for the benefit of others. So this kind of attitude influenced me deeply. It also instilled in me a deep desire to live in the United States." During this time, Zadeh was awarded several patents.

Despite being more fluent in Russian than in Persian, Zadeh sat for the national university exams and placed third in the entire country. As a student, he ranked first in his class in his first two years. In 1942, he graduated from the University of Tehran with a degree in electrical engineering (Fanni), one of only three students in that field to graduate that year, due to the turmoil created by World War II, when the United States, Britain, and the Soviet Union invaded Iran whose ruler, the Shah, was pro-German. Over 30,000 American soldiers were based there, and Zadeh worked with his father, who did business with them as a contractor for hardware and building materials.

 In 1943, Zadeh decided to emigrate to the United States, and traveled to Philadelphia by way of Cairo after months of delay waiting for the proper papers or for the right ship to appear. He arrived in mid-1944, and entered M.I.T. as a graduate student later that year. While in the United States, he changed his name to Lotfi Asker Zadeh.

He received an MS degree in electrical engineering from M.I.T. in 1946, and then According to Google Scholar, as of September 2015 Zadeh's work had been cited 150,852 times with the 1965 "Fuzzy Sets" paper receiving 58,251.applied to Columbia University, as his parents had settled in New York City. Columbia admitted him as a doctoral student, and offered him an instructorship as well. He received his PhD in electrical engineering from Columbia in 1949, and became an assistant professor the next year.

 Zadeh taught for ten years at Columbia, was promoted to Full Professor in 1957, and has taught at the University of California, Berkeley since 1959. He published his seminal work on fuzzy sets in 1965, in which he detailed the mathematics of fuzzy set theory. In 1973 he proposed his theory of fuzzy logic.

 Zadeh is noted to be "quick to shrug off nationalism, insisting there are much deeper issues in life", and is quoted as stating in an interview: "The question really isn't whether I'm American, Russian, Iranian, Azerbaijani, or anything else. I've been shaped by all these people and cultures and I feel quite comfortable among all of them."Zadeh also notes in the same interview: "Obstinacy and tenacity. Not being afraid to get embroiled in controversy. That's very much a Turkish tradition. That's part of my character, too. I can be very stubborn. That's probably been beneficial for the development of Fuzzy Logic." He describes himself as "an American, mathematically oriented, electrical engineer of Iranian descent, born in Russia." Zadeh is married to Fay Zadeh and has two children, Stella Zadeh and Norman Zadeh.

According to Google Scholar, as of September 2015 Zadeh's work had been cited 150,852 times with the 1965 "Fuzzy Sets" paper receiving 58,251.

Zadeh, in his theory of fuzzy sets, proposed using a membership function (with a range covering the interval [0,1]) operating on the domain of all possible values. He proposed new operations for the calculus of logic and showed that fuzzy logic was a generalisation of classical and Boolean logic. He also proposed fuzzy numbers as a special case of fuzzy sets, as well as the corresponding rules for consistent mathematical operations (fuzzy arithmetic).

Lotfi Zadeh is also credited, along with John R. Ragazzini, in 1952, with having pioneered the development of the z-transform method in discrete time signal processing and analysis. These methods are now standard in digital signal processing, digital control, and other discrete-time systems used in industry and research. He is an editor of International Journal of Computational Cognition.

Zadeh's latest work includes computing with words and perceptions. His recent papers include From Search Engines to Question-Answering Systems—The Role of Fuzzy Logic, Progress in Informatics, No. 1, 1-3, 2005; and Toward a Generalized Theory of Uncertainty (GTU)—An Outline, Information Sciences, Elsevier, Vol. 172, 1-40, 2005. wikipedia (afn)

Senin, 12 Oktober 2015

Introduction of Intelligent Control

Intelligent Control is a control methods are developed that attempt to emulate important characteristics of human intellligent. Control system have two loops, there are open loops and close loop. Close loop have feedback that reduce the effects of parameter changes (disturbances). Comparison of open loop is little feedback will affect the changes compared to the open loop very much changed, so that the open loop is not appropriate if its used for system that require precision and comfortability.
Intelligent control methodologies are being applied to robotics and automation, communications, manufacturing, traffic control, etc.Characteristics of Intelligent control include adaptation and learning, planning under large uncertainty and coping with large amounts of data.Neural networks (NN), Fuzzy control, genetic algorithms (GA), planning systems, expert systems, hybrid system are all areas where related work is taking place. There are many areas in control where learning can be used to advantage and these needs can be briefly classified as follows : 1. Learning about the plant; how to incorporate changes and then how to derive new plant models, 2. Learning about the controller; how to adjust certain controller parameter to enhance performance, 3. Learning about the environment; this can be done using methods ranging from passive observation to active experimentation, 4. Learning new design goals and constraints. The relation between adaptive control and learning control is achieved, learning is achieved. When an adaptive control algorithm is used to adapt the controller parameter s so that for example stability is maintained. In this case the system learns and the knowledge acquired is the new values for the parameters. Note however, that if later the same changes occur again and the system is described by exactly the same parameters identified earlier, the adaptive control algorithm still needs to recalculate the controller and perhaps the plant parameters since nothing was kept in memory. So, in that sense the system has not learned. It has certainly learned what to do when certain type of changes take place. In particular, it has been told exactly what to do, that is it was given the adaptive algorithm, and this is knowledge by rote learning. The knowledge represented by the new values of the controller and the plant parameters and the circumstances under which these values are appropriate, are not retained. Adaptation means system is able to adapt to environmental changes.Learning ability is done by reward and punishment (behaviour based control), model reference and reinforcement learning. Planning under large uncertainty means system capable of planning even though many uncertainties.Coping with large amount data (generalization) how to handle data that is too much. (tr)

Senin, 05 Oktober 2015

Data logger analog read potensiometer in excel using PLX-DAQ

1. watch in this video tutorial to get knowledge in this site https://www.youtube.com/watch?v=bVOwB2NQ9ok



2. download all component to started in here






3. in this output not real value potensiometer so edit and remake with analog read from arduino example