Vibration control of load for rotary crane system using neural network with GA-based training
Kunihiko Nakazono, Kouhei Ohnishi, Hiroshi Kinjo, Tetsuhiko Yamamoto
A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.
Artificial Life and Robotics
生化学、遺伝学、分子生物学(全般)
「Vibration control of load for rotary crane system using neural network with GA-based training」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。
Vibration Medicine & Life Sciences 100%
Cranes Engineering & Materials Science 97%
Vibration control Engineering & Materials Science 95%
Genetic algorithms Engineering & Materials Science 63%
Feedback Engineering & Materials Science 22%
Nakazono, K., Ohnishi, K., Kinjo, H., & Yamamoto, T. (2008). Vibration control of load for rotary crane system using neural network with GA-based training. Artificial Life and Robotics, 13(1), 98-101. https://doi.org/10.1007/s10015-008-0586-5
Vibration control of load for rotary crane system using neural network with GA-based training. / Nakazono, Kunihiko; Ohnishi, Kouhei; Kinjo, Hiroshi; Yamamoto, Tetsuhiko.
In: Artificial Life and Robotics, Vol. 13, No. 1, 01.12.2008, p. 98-101.
Nakazono, K, Ohnishi, K, Kinjo, H & Yamamoto, T 2008, 'Vibration control of load for rotary crane system using neural network with GA-based training', Artificial Life and Robotics, vol. 13, no. 1, pp. 98-101. https://doi.org/10.1007/s10015-008-0586-5
Nakazono K, Ohnishi K, Kinjo H, Yamamoto T. Vibration control of load for rotary crane system using neural network with GA-based training. Artificial Life and Robotics. 2008 12 1;13(1):98-101. https://doi.org/10.1007/s10015-008-0586-5
Nakazono, Kunihiko ; Ohnishi, Kouhei ; Kinjo, Hiroshi ; Yamamoto, Tetsuhiko. / Vibration control of load for rotary crane system using neural network with GA-based training. In: Artificial Life and Robotics. 2008 ; Vol. 13, No. 1. pp. 98-101.
@article{85af3fde0a4d4767972cea7482edad79,
title = "Vibration control of load for rotary crane system using neural network with GA-based training",
abstract = "A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.",
keywords = "Genetic algorithm, Neural network, Rotary crane, Vibration control",
author = "Kunihiko Nakazono and Kouhei Ohnishi and Hiroshi Kinjo and Tetsuhiko Yamamoto",
journal = "Artificial Life and Robotics",
publisher = "Springer Japan",
T1 - Vibration control of load for rotary crane system using neural network with GA-based training
AU - Nakazono, Kunihiko
AU - Ohnishi, Kouhei
AU - Kinjo, Hiroshi
AU - Yamamoto, Tetsuhiko
N2 - A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.
AB - A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach.
KW - Genetic algorithm
KW - Neural network
KW - Rotary crane
KW - Vibration control
JO - Artificial Life and Robotics
JF - Artificial Life and Robotics