You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
Adaptive control is seen as a two part problem control of plant dynamics and control of plant noise. The two parts are treated separately. An unknown plant will track an input command signal if the plant is driven by a controller whose transfer function approximates the inverse of the plant transfer function. An adaptive inverse identification process can be used to obtain a stable controller even if the plant is nonminimum phase. A model reference version of this idea allows system dynamics to closely approximate desired reference model dynamics. No direct feedback is used except that the plant output is monitored and utilized in order to adjust the paramters of the controller. Control of internal plant noise is accomplished with an optimal adaptive noise canceller. The canceller does not affect plant dynamics but feeds back plant noise in a way that minimizes plant output noise power. Key words. Adaptive control modeling identification inverse modeling noise cancelling deconvolution adaptive inverse control.
The alert did not successfully save. Please try again later.
Bernard Widrow, "Adaptive inverse control," Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21152