In this report, we consider the part of our work which concerns the design of neuroidentifiers and neurocontrollers which attenuate the effects of disturbances. Examples for linear-systems identification and disturbance rejection, as well as nonlinear control of an aircraft encountering wind shear on take-off are briefly discussed, and the following three problems are addressed. 1. 1. System identification via dynamic neural networks. 2. 2. Disturbance attenuation via memory neurons. 3. 3. Aircraft control in the presence of wind shear after takeoff.
Bibliographical noteFunding Information:
This research was supported in part by AFOSR under Grant No. F49620-93-1-0012. Earlier versions of this work have been reported in references [l-5] and at NASA Ames Research Center.
- Aircraft control. Systems identification and control
- Dynamic neural networks
- Robust control of nonlinear systems