Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics,: Band 27
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Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics (2015)
DE NW
ISBN: 9783990335116 bzw. 3990335111, in Deutsch, Trauner Verlag, neu.
buchversandmimpf2000, [3715720].
Neuware - divThe evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft./div, Buch.
Neuware - divThe evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft./div, Buch.
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Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics
DE PB NW
ISBN: 9783990335116 bzw. 3990335111, in Deutsch, Trauner Verlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
buecher.de GmbH & Co. KG, [1].
divThe evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft./divSofort lieferbar, Softcover.
buecher.de GmbH & Co. KG, [1].
divThe evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft./divSofort lieferbar, Softcover.
3
Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics
DE NW
ISBN: 9783990335116 bzw. 3990335111, in Deutsch, neu.
Lieferung aus: Deutschland, zzgl. Versandkosten.
The evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft.
The evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft.
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| Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning | Trauner | 2015
~EN NW
ISBN: 9783990335116 bzw. 3990335111, vermutlich in Englisch, Trauner Verlag, neu.
The evolution in the field of actuators has led to very powerful and smart drives, combining mechanics with electronic and informatics, which require a suitable control to exploit potential advantages. A common requirement for actuators is time optimality, and thus it is sensible to look for time optimal control strategies. For known systems time optimal control can be formulated using standard methods. Unfortunately, in rare cases the problem is convex and thus requires the use of numerical methods, which may lead to local optima. Against this background, this work, started in the framework of an industrial project, presents a method to obtain an approximation of the time optimal control by iterative learning. The method itself consist of two learning loops, one based on the convergence of learning iterations enforcing the tracking of a specified trajectory, the other one adapting the trajectory to obtain a time (sub)optimal solution. To evaluate the me-thod, two examples are presented a compressor valve actuator and the steepest ascent of an aircraft.
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Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics,: Band 27 (Paperback) (2015)
DE PB NW
ISBN: 9783990335116 bzw. 3990335111, Band: 27, in Deutsch, Trauner Verlag, Taschenbuch, neu.
Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
Language: English Brand New Book.
Language: English Brand New Book.
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Approximation of Time Optimal Control for Unknwon Nonlinear Systems by Learning, Schriftenreihe Advances in Mechatronics,: Band 27 (2015)
EN PB NW FE
ISBN: 9783990335116 bzw. 3990335111, in Englisch, 148 Seiten, Trauner Verlag, Taschenbuch, neu, Erstausgabe.
Lieferung aus: Deutschland, Gewöhnlich versandfertig in 1 bis 3 Monaten. Lieferung von Amazon, Versandkostenfrei.
Von Händler/Antiquariat, Amazon.de.
Trauner Verlag, Taschenbuch, Ausgabe: 1. Auflage 2015, Publiziert: 2015-07-21T00:00:01Z, Produktgruppe: Book.
Von Händler/Antiquariat, Amazon.de.
Trauner Verlag, Taschenbuch, Ausgabe: 1. Auflage 2015, Publiziert: 2015-07-21T00:00:01Z, Produktgruppe: Book.
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