Zobrazeno 1 - 10
of 60
pro vyhledávání: '"W. Chatlatanagulchai"'
Publikováno v:
SICE
Backstepping is a good control technique for rigid-flexible system, but it has some limitations that hard to use in real control applications. First, a desired trajectory should be a continuous function and not change rapidly. Second, math model used
Akademický článek
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Publikováno v:
Volume 4B: Dynamics, Vibration, and Control.
Fractional derivative system has gained its popularity in modeling and control because of its long memory property. Only recently, residual vibration suppression for the fractional derivative oscillatory system using input shaping has been studied. I
Akademický článek
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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modeling of hard disk drive actuators is obtained, extracted from measuring frequenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be911b054ae14edd1114a27995721400
Publikováno v:
SAE Technical Paper Series.
Publikováno v:
SAE Technical Paper Series.
Autor:
Peter H. Meckl, W. Chatlatanagulchai
Publikováno v:
IEEE International Conference Mechatronics and Automation, 2005.
This paper presents an output feedback control. The control algorithm does not require plant mathematical model. However, the actual plant is assumed to be affine with respect to local inputs. High order differential neural networks are used to ident
Publikováno v:
2006 American Control Conference.
Joint flexibility is an intrinsic property in most industrial robot manipulators. Because of the great complexity of its model, the resonant frequencies of the two-link flexible-joint robot manipulator vary with the configuration of the manipulator.
Autor:
W. Chatlatanagulchai, Peter H. Meckl
Publikováno v:
Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..
We present a state-feedback control of a two-link flexible-joint robot. The control algorithm does not require the mathematical model representing the robot. Three-layer neural networks approximate the unknown plant functions. The neural network weig