Omkar, SN and Nagabhushanam, J (1998) Neural Network Controller for Minimizing Hub Shear Forces in Helicopter. In: 1998 IEEE International Symposium on Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), 14-17 September, Gaithersburg,USA, pp. 354-358.
This paper discusses the application of recurrent neural networks for identification and control of helicopter vibrations. A class of recurrent networks called memory neuron networks are used for plant identification and control. These networks are obtained by adding trainable temporal elements to feedforward networks. This makes the network output history sensitive and gives them the capability to identify and control systems whose order is unknown or systems with unknown delay. A representative analytical model with higher harmonic pitch angles for minimizing hub shear forces is used for simulation. The effectiveness of the controller in minimizing the force level at varying and constant forward speed are studied. The ability of the controller to cope with changes in system and environment parameters is also considered.
|Item Type:||Conference Paper|
|Additional Information:||Copyright 1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Keywords:||Neural networks;Adaptive controllers;Helicopters|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||10 Apr 2006|
|Last Modified:||19 Sep 2010 04:25|
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