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Adaptive Control Methodology for the Compensation of Linear and non Linear Parametric Disturbances
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 42 - Number 20 |
| Year of Publication: 2012 |
| Authors: Karnakar Shukla, Santosh Kumar Patel, Vikas Kannaujia |
10.5120/5843-8082
|
Karnakar Shukla, Santosh Kumar Patel, Vikas Kannaujia . Adaptive Control Methodology for the Compensation of Linear and non Linear Parametric Disturbances. International Journal of Computer Applications. 42, 20 ( March 2012), 49-54. DOI=10.5120/5843-8082
Abstract
Adaptive controller is called for that provides a uniformly satisfactory performance in the presence of parametric uncertainties and variations. The adaptive approach to this problem is to design a controller with varying parameters, which are adjusted in such a way that they adapt to and accommodate the uncertainties and variations in the plant to be controlled by providing such a time-varying solution. The exact nature of which is determined by the nature and magnitude of the parametric uncertainties, the closed loop adaptive system seeks to enable a better performance. The result that have accrued in the field of adaptive control over the past three decades have provided a framework within which such time varying adaptive controller can be designed to yield stability and robustness in various control tasks. adaptive control deals with parametric uncertainties in control system and could be defined as the combination of a parametric estimator, which generate parameter estimates online with a control law in order to control class of plant (is the combination of process and actuator, which is a device that can influences the controlled variable of the process) whose parameter are completely unknown and/or could change with the time in a unpredictable manner. So from this paper we are trying to find auxiliary process variable that correlate well with the change in process dynamics. And also various approaches' to the manipulation with unpredictable parametric uncertainties
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