Title :
Robust adaptive tracking control of delta wing vortex-coupled roll dynamics using RBF neural networks
Author :
Pakmehr, Mehrdad ; Gordon, Brandon W. ; Rabbath, C.A.
Author_Institution :
Dept. of Mech. & Ind. Eng., Concordia Univ., Montreal, Que.
Abstract :
In this paper a robust adaptive control strategy has been proposed and applied for vortex-coupled delta wing roll dynamics with parameter uncertainty in the rolling moment coefficient. The robust adaptive tracking neuro-controller employs a new network of Gaussian radial basis functions (RBF) to adaptively compensate for the rolling moment coefficient. Rolling moment coefficient, as a function of left and right vortex breakdown positions, is estimated online in adaptive neuro-controller structure using a special feature of RBF networks for the delta wing case. The proposed controller is stable with good tracking performance
Keywords :
Gaussian processes; adaptive control; aerospace control; neurocontrollers; radial basis function networks; robust control; tracking; Gaussian radial basis functions; RBF neural networks; delta wing vortex-coupled roll dynamics control; parameter uncertainty; robust adaptive tracking neurocontroller; rolling moment coefficient; Adaptive control; Aerodynamics; Aerospace control; Control system synthesis; Motion control; Neural networks; Programmable control; Radial basis function networks; Recurrent neural networks; Robust control;
Conference_Titel :
Control Applications, 2005. CCA 2005. Proceedings of 2005 IEEE Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-9354-6
DOI :
10.1109/CCA.2005.1507267