• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 259
  • 62
  • 59
  • 23
  • 7
  • 5
  • 5
  • 3
  • 3
  • 3
  • 2
  • 2
  • 1
  • 1
  • 1
  • Tagged with
  • 562
  • 562
  • 315
  • 79
  • 77
  • 67
  • 63
  • 59
  • 59
  • 52
  • 46
  • 45
  • 42
  • 38
  • 37
  • About
  • 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.
1

Adaptive dynamic inversion of nonlinear systems subjected to control saturation constraints

Tandale, Monish Deepak 17 September 2007 (has links)
The adaptive dynamic inversion control methodology uses dynamic inversion to calculate the control, and adaptation to compensate for the errors in the inversion due to model uncertainties. Traditionally, adaptive control assumes full authority control and lacks an adequate theoretical treatment for control in the presence of actuator saturation limits. The objective of this research is to investigate the problems introduced in the adaptive dynamic inversion control scheme due to bounds on the control, and design control strategies to overcome these problems. The unique contribution of this research is that it identifies the maximum possible domain of attraction considering the control position limit, and uses a switching control strategy to contain the plant within the maximum possible domain of attraction. Another novel idea is that of a direction consistent control constraint mechanism which maintains the resultant direction of the rate of change of state the same as that of the desired, even in the presence of control saturation. This research uses a modified adaptation mechanism to prevent incorrect adaptation arising from trajectory errors due to control saturation. Mathematical development of the control laws and the adaptation mechanisms is presented along with rigorous proofs for convergence of the tracking error and stability of the overall control scheme. Finally, numerical simulation results are presented to validate the control methodology.
2

A two stage reinforcement technique for learning control.

Lambert, James Douglas January 1968 (has links)
No description available.
3

Recurrent neural networks : some control aspects

Zbikowski, Rafal Waclaw January 1994 (has links)
No description available.
4

Applications of neural networks in nonlinear dynamic systems

Guo, Lingzhong January 2003 (has links)
No description available.
5

Control of servo-hydraulic materials-testing machines

Hinton, Christopher Eric January 1992 (has links)
No description available.
6

Walsh functions for the identification and control of nonlinear plants

Harkness, John January 1995 (has links)
No description available.
7

The MCS algorithm for the co-ordinated control of web tension and transport

Dye, M. G. January 1995 (has links)
No description available.
8

Adaptive estimation theory with real-time implementation

Vishwanath, T. G. January 1987 (has links)
No description available.
9

General simulation and design tools for control of electro-mechanical systems

Atyia, Thamir Hassan January 2000 (has links)
No description available.
10

Design of a compensated self-tuner for process control

Guidoum, A. January 1988 (has links)
No description available.

Page generated in 0.0406 seconds