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Inhaltsangabe
Sliding Mode Controllers possess robustness properties under parameter uncertainties. The ideally zero switching time of the controller output cannot be achieved in digital implementation. This causes a phenomenon called chattering – high frequency oscillations observed in systems state variables. Chattering also shows itself as high amplitude oscillatory behavior in the control signal. A chattering actuator output is not favorable for many plants, including robot manipulators driven by actuator torques. This problem is traditionally solved by smoothing the switching control output, deviating from the original mathematical foundations robustness. This motivates the exploration of automatic tuning approaches which consider chattering and performance simultaneously. This book proposes two SMC smoothing and parameter tuning methods with soft computing (SC) methodologies. The first method is based on Genetic Algorithms (GA). The second SMC parameter tuning method proposed employs a fuzzy logic system to enlarge the applicability range of the controller. The chattering measure and the sliding variable are used as the inputs of this system, which tunes the controller output mechanism.
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Reseña del editor
Sliding Mode Controllers possess robustness properties under parameter uncertainties. The ideally zero switching time of the controller output cannot be achieved in digital implementation. This causes a phenomenon called chattering – high frequency oscillations observed in systems state variables. Chattering also shows itself as high amplitude oscillatory behavior in the control signal. A chattering actuator output is not favorable for many plants, including robot manipulators driven by actuator torques. This problem is traditionally solved by smoothing the switching control output, deviating from the original mathematical foundations robustness. This motivates the exploration of automatic tuning approaches which consider chattering and performance simultaneously. This book proposes two SMC smoothing and parameter tuning methods with soft computing (SC) methodologies. The first method is based on Genetic Algorithms (GA). The second SMC parameter tuning method proposed employs a fuzzy logic system to enlarge the applicability range of the controller. The chattering measure and the sliding variable are used as the inputs of this system, which tunes the controller output mechanism.
Biografía del autor
Basel ElThalathiny graduated with a M.Sc. Degree in Mechatronics Engineering from Sabanci University, Turkey. Before it, he was enrolled in the Industrial Engineering Master Program too at Sabanci Uni. He's a holder of a B.Sc. Degree in Mechanical Engineering with Triple Specializations and Triple Minors from the American University in Cairo, Egypt
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- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2016
- ISBN 10 365993447X
- ISBN 13 9783659934476
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten88
- Kontakt zum HerstellerNicht verfügbar
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Slinding Mode Robot Controller Tuning Genetic Algorithms & Fuzzy Logic
Verlag:
LAP LAMBERT Academic Publishing Aug 2016, 2016
ISBN 10: 365993447X
ISBN 13: 9783659934476
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -Sliding Mode Controllers possess robustness properties under parameter uncertainties. The ideally zero switching time of the controller output cannot be achieved in digital implementation. This causes a phenomenon called chattering ¿ high frequency oscillations observed in systems state variables. Chattering also shows itself as high amplitude oscillatory behavior in the control signal. A chattering actuator output is not favorable for many plants, including robot manipulators driven by actuator torques. This problem is traditionally solved by smoothing the switching control output, deviating from the original mathematical foundations robustness. This motivates the exploration of automatic tuning approaches which consider chattering and performance simultaneously. This book proposes two SMC smoothing and parameter tuning methods with soft computing (SC) methodologies. The first method is based on Genetic Algorithms (GA). The second SMC parameter tuning method proposed employs a fuzzy logic system to enlarge the applicability range of the controller. The chattering measure and the sliding variable are used as the inputs of this system, which tunes the controller output mechanism.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Artikel-Nr. 9783659934476
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Slinding Mode Robot Controller Tuning Genetic Algorithms & Fuzzy Logic
Verlag:
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365993447X
ISBN 13: 9783659934476
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Paperback. Zustand: Brand New. 88 pages. 8.66x5.91x0.20 inches. In Stock. Artikel-Nr. 365993447X
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