2011 IEEE International Conference on Industrial Technology 2011
DOI: 10.1109/icit.2011.5754392
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Fuzzy logic control of single-link flexible joint manipulator

Abstract: This paper presents the design and control of a single-link flexible-joint robot manipulator. A cascade fuzzy logic controller (FLC) was used to remove link vibrations and to obtain fast trajectory tracking performance.The cascade FLC structure includes 3 different FLCs. The input variables of the first and the second FLCs are the motor rotation angle error, its derivative, and the end-point deflection error its derivative, respectively. The outputs of these controllers are the inputs of the third FLC, which y… Show more

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Cited by 19 publications
(18 citation statements)
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“…Over the last two decades, the control of FJMs has also benefited from strategies that seek to reduce the impact of modeling difficulties on controller performance, instead making use such nonmodel intensive strategies as genetic algorithms, particle swarm optimization methods, fuzzy logic, neural networks [11][12][13][14][15][16][17], and more recently, the so-called iPI and iPID strategies [18][19][20]. These pseudomodel based control strategies have enabled a compromise between the cost of real-time controller implementation and the need for highly accurate models in model-based control.…”
Section: Introductionmentioning
confidence: 99%
“…Over the last two decades, the control of FJMs has also benefited from strategies that seek to reduce the impact of modeling difficulties on controller performance, instead making use such nonmodel intensive strategies as genetic algorithms, particle swarm optimization methods, fuzzy logic, neural networks [11][12][13][14][15][16][17], and more recently, the so-called iPI and iPID strategies [18][19][20]. These pseudomodel based control strategies have enabled a compromise between the cost of real-time controller implementation and the need for highly accurate models in model-based control.…”
Section: Introductionmentioning
confidence: 99%
“…The last controller generates control signal of the system using outputs of the other controllers (θ, α). Interval MFs and rules related to all controllers have been designed based on type-1 MFs exist in [17]. All IT2FL-C was designed on our interval type-2 fuzzy logic toolbox as shown in Fig.…”
Section: Design Of the Cascade It2fl-cmentioning
confidence: 99%
“…Fuzzy control is a control way of applying expert knowledge to control a plant without having detail information of the plant in passing [10]. A FLC has three main component namely i) Fuzzifier which convert the input signal into fuzzy signal ii) fuzzy inference engine which process the fuzzified signal using decision rules, and iii) Defuzzifier which convert the fuzzy controller output signal to a signal used as the control input signal to the system model.…”
Section: Introductionmentioning
confidence: 99%
“…A FLC has three main component namely i) Fuzzifier which convert the input signal into fuzzy signal ii) fuzzy inference engine which process the fuzzified signal using decision rules, and iii) Defuzzifier which convert the fuzzy controller output signal to a signal used as the control input signal to the system model. Explicitly in [10], three different fuzzy logic controllers (FLCs) are developed to control vibration and end point deflection. A Hybrid fuzzy logic control with genetic optimisation for vibration control of a single-link flexible manipulator is presented in passing [11].…”
Section: Introductionmentioning
confidence: 99%
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