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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 261 to 270 of 669 (0.041 seconds)| 261 |
ADAPTIVE CONTROL FOR TRACKING AND DISTURBANCE ATTENUATION FOR SISO LINEAR SYSTEMS WITH REPEATED NOISY MEASUREMENTSCHEN, YU January 2003 (has links)
No description available.
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| 262 |
Adaptive control of flexible systems using self-tuning digital notch filtersMaggard, William P. January 1987 (has links)
No description available.
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| 263 |
The adaptive seeking control strategy and applications in automotive control technologyYu, Hai 21 September 2006 (has links)
No description available.
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| 264 |
Nonlinear Adaptive Controller Design For Air-breathing Hypersonic VehiclesFiorentini, Lisa 01 September 2010 (has links)
No description available.
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| 265 |
Modified Sliding Mode Control Algorithm for Vibration Control of Linear and Nonlinear Civil StructuresWang, Nengmou 27 July 2011 (has links)
No description available.
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| 266 |
Sources of Adaptive Capacity during Multi-Unmanned Aerial Vehicle OperationsHughes, Thomas Carroll 19 December 2012 (has links)
No description available.
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| 267 |
Discrete-time adaptive control of a class of nonlinear systems /Lee, Keh-ning January 1986 (has links)
No description available.
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| 268 |
Adaptive Feedforward Control of Sinusoidal Disturbances with Unknown Parameters: AnExperimental InvestigationBassford, Marshall R., Mr. 21 July 2022 (has links)
No description available.
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| 269 |
A technique for dual adaptive control.Alster, Jacob January 1972 (has links)
No description available.
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| 270 |
Iterative learning control for manipulator trajectory tracking without any control singularityJiang, Ping, Woo, P., Unbehauen, R. January 2002 (has links)
No / In this paper, we investigate trajectory tracking in a multi-input nonlinear system, where there is little knowledge of the system parameters and the form of the nonlinear function. An identification-based iterative learning control (ILC) scheme to repetitively estimate the linearity in a neighborhood of a desired trajectory is presented. Based on this estimation, the original nonlinear system can track the desired trajectory perfectly by the aid of a regional training scheme. Just like in adaptive control, a singularity exists in ILC when the input coupling matrix is estimated. Singularity avoidance is discussed. A new parameter modification procedure for ILC is presented such that the determinant of the estimate of the input coupling matrix is uniformly bounded from below. Compared with the scheme used for adaptive control of a MIMO system, the proposed scheme reduces the computation load greatly. It is used in a robotic visual system for manipulator trajectory tracking without any information about the camera-robot relationship. The estimated image Jacobian is updated repetitively and then its inverse is used to calculate the manipulator velocity without any singularity.
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