Neuro fuzzy robust controllers for drive systems

Dote, Y.; Strefezza, Miguel; Suyitno, A.

doi:10.1109/isie.1993.268801

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…The most common and straightforward applications of fuzzy logic are in the domain of control [42,49,50,51]. Fuzzy control is a nonlinear control method based on fuzzy logic.…”

Section: Fuzzy Logic Controlmentioning

confidence: 99%

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Fuzzy Control Strategies in Human Operator and Sport Modeling

Ivancevic¹,

Jovanovic

Markovi

2010

Fuzzy Information and Engineering

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The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.

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“…The most common and straightforward applications of fuzzy logic are in the domain of control [42,49,50,51]. Fuzzy control is a nonlinear control method based on fuzzy logic.…”

Section: Fuzzy Logic Controlmentioning

confidence: 99%

“…Fuzzy logic offers several unique features that make it a particularly good choice for many control problems, among them [50,51]:…”

Section: Characteristics Of Fixed Fuzzy Controlmentioning

confidence: 99%

Fuzzy Control Strategies in Human Operator and Sport Modeling

Ivancevic¹,

Jovanovic

Markovi

2010

Fuzzy Information and Engineering

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“…Results using RBF networks were presented to illustrate that it is possible to successfully control a generator system [43]. Power electronic drive controllers have also been implemented with these networks, in digital signal processors (DSPs), to attain robust properties [38].…”

Section: F Rbf Networkmentioning

confidence: 99%

“…RBF networks can be observed, as well, in predictive controllers for drive systems [38]. Hopfield structures were used for torque minimization control of redundant manipulators [33].…”

Section: Process Controlmentioning

confidence: 99%

A comprehensive review for industrial applicability of artificial neural networks

Meireles

Almeida

Simões

2003

IEEE Trans. Ind. Electron.

381

136

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Abstract-This paper presents a comprehensive review of the industrial applications of artificial neural networks (ANNs), in the last 12 years. Common questions that arise to practitioners and control engineers while deciding how to use NNs for specific industrial tasks are answered. Workable issues regarding implementation details, training and performance evaluation of such algorithms are also discussed, based on a judiciously chronological organization of topologies and training methods effectively used in the past years. The most popular ANN topologies and training methods are listed and briefly discussed, as a reference to the application engineer. Finally, ANN industrial applications are grouped and tabulated by their main functions and what they actually performed on the referenced papers. The authors prepared this paper bearing in mind that an organized and normalized review would be suitable to help industrial managing and operational personnel decide which kind of ANN topology and training method would be adequate for their specific problems.

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Expert system, fuzzy logic, and neural network applications in power electronics and motion control

Bose

1994

Proc. IEEE

346

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Artificial intelligence (AI) tools, such as expert system, fuzzy logic, and neural network are expected to usher a new era in power electronics and motion control in the coming decades. Although these technologies have advanced significantly in recent years and have found wide applications, they have hardly touched the power electronics and mackine drives area. The paper describes theseAi tools and their application in the area of power electronics and motion control. The body of the paper is subdivided into three sections which describe, respectively, the principles and applications of expert system, fuzzy logic, and neural network. The theoretical portion of each topic is of direct relevance to the application of power electronics. The example applications in the paper are taken from the published literature. Hopefully, the readers will be able to formulate new applications from these examples.

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Neuro fuzzy robust controllers for drive systems

Cited by 4 publications

References 9 publications

Fuzzy Control Strategies in Human Operator and Sport Modeling

Fuzzy Control Strategies in Human Operator and Sport Modeling

A comprehensive review for industrial applicability of artificial neural networks

Expert system, fuzzy logic, and neural network applications in power electronics and motion control

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