High-order natural iterative learning control of robotic manipulators: new results
Само за регистроване кориснике
2005
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
In this paper it is considered problem of control robotic systems using suitable iterative
learning control. Recently, there have been extensive research activities in the topic of learning
control for controlling dynamics non-linear systems in an iterative manner. The learning control
concept differs from conventional control methodologies in that the control input can be
appropriately adjusted to improve its future performance by learning from the past
experimental information as the operation is repeated. Iterative learning control (ILC) requires
less a priori knowledge about the controlled system in the controller design phase and also less
computational effort than many other kinds of control. Dynamic model of robotic manipulator
with uncertainties can be presented in the form of state space and output equations as a class of
time-varying, non -linear system. Motivated by human learning, the basic idea of
iterative learning control is to use information from previous exe...cutions of the task in order to
improve performance from trial to trial in the sense that the tracking error ei (t) is sequentially
reduced. The learning control scheme comprises two types of control laws: feedback law and
feed-forward control law. It is proposed high-order feedforward ILC using local negative
feedback on control with great amplifying. Sufficient conditions for the convergence of a new
type ILC algorithm for a class of time-varying, non-linear system are obtained. Finally, results
are applied to a suitable robotic manipulator through simulation, which demonstrates the
effectiveness of the method.
Кључне речи:
robotic manipulators / iterative learning control / natural / high-orderИзвор:
Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12., 2005, 36-36Издавач:
- Jugoslovensko drustvo za Mehaniku
- Novi Sad: Fakultet tehničkih nauka
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Lazarević, Mihailo PY - 2005 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5487 AB - In this paper it is considered problem of control robotic systems using suitable iterative learning control. Recently, there have been extensive research activities in the topic of learning control for controlling dynamics non-linear systems in an iterative manner. The learning control concept differs from conventional control methodologies in that the control input can be appropriately adjusted to improve its future performance by learning from the past experimental information as the operation is repeated. Iterative learning control (ILC) requires less a priori knowledge about the controlled system in the controller design phase and also less computational effort than many other kinds of control. Dynamic model of robotic manipulator with uncertainties can be presented in the form of state space and output equations as a class of time-varying, non -linear system. Motivated by human learning, the basic idea of iterative learning control is to use information from previous executions of the task in order to improve performance from trial to trial in the sense that the tracking error ei (t) is sequentially reduced. The learning control scheme comprises two types of control laws: feedback law and feed-forward control law. It is proposed high-order feedforward ILC using local negative feedback on control with great amplifying. Sufficient conditions for the convergence of a new type ILC algorithm for a class of time-varying, non-linear system are obtained. Finally, results are applied to a suitable robotic manipulator through simulation, which demonstrates the effectiveness of the method. PB - Jugoslovensko drustvo za Mehaniku PB - Novi Sad: Fakultet tehničkih nauka C3 - Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12. T1 - High-order natural iterative learning control of robotic manipulators: new results EP - 36 SP - 36 UR - https://hdl.handle.net/21.15107/rcub_machinery_5487 ER -
@conference{ author = "Lazarević, Mihailo", year = "2005", abstract = "In this paper it is considered problem of control robotic systems using suitable iterative learning control. Recently, there have been extensive research activities in the topic of learning control for controlling dynamics non-linear systems in an iterative manner. The learning control concept differs from conventional control methodologies in that the control input can be appropriately adjusted to improve its future performance by learning from the past experimental information as the operation is repeated. Iterative learning control (ILC) requires less a priori knowledge about the controlled system in the controller design phase and also less computational effort than many other kinds of control. Dynamic model of robotic manipulator with uncertainties can be presented in the form of state space and output equations as a class of time-varying, non -linear system. Motivated by human learning, the basic idea of iterative learning control is to use information from previous executions of the task in order to improve performance from trial to trial in the sense that the tracking error ei (t) is sequentially reduced. The learning control scheme comprises two types of control laws: feedback law and feed-forward control law. It is proposed high-order feedforward ILC using local negative feedback on control with great amplifying. Sufficient conditions for the convergence of a new type ILC algorithm for a class of time-varying, non-linear system are obtained. Finally, results are applied to a suitable robotic manipulator through simulation, which demonstrates the effectiveness of the method.", publisher = "Jugoslovensko drustvo za Mehaniku, Novi Sad: Fakultet tehničkih nauka", journal = "Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12.", title = "High-order natural iterative learning control of robotic manipulators: new results", pages = "36-36", url = "https://hdl.handle.net/21.15107/rcub_machinery_5487" }
Lazarević, M.. (2005). High-order natural iterative learning control of robotic manipulators: new results. in Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12. Jugoslovensko drustvo za Mehaniku., 36-36. https://hdl.handle.net/21.15107/rcub_machinery_5487
Lazarević M. High-order natural iterative learning control of robotic manipulators: new results. in Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12.. 2005;:36-36. https://hdl.handle.net/21.15107/rcub_machinery_5487 .
Lazarević, Mihailo, "High-order natural iterative learning control of robotic manipulators: new results" in Book of abstracts 25th Yugoslav Congress on Theoretical and Applied Mechanics, Novi Sad, Serbia, June 1-3,2005, 1-12. (2005):36-36, https://hdl.handle.net/21.15107/rcub_machinery_5487 .