Neural-network-based control of large structures

Srinivas R. Vadali; Tarunraj Singh; Andrew J. Kurdila; John L. Junkins

doi:10.1117/12.152819

8 September 1993 Neural-network-based control of large structures

Srinivas R. Vadali, Tarunraj Singh, Andrew J. Kurdila, John L. Junkins

Proceedings Volume 1917, Smart Structures and Materials 1993: Smart Structures and Intelligent Systems; (1993) https://doi.org/10.1117/12.152819
Event: 1993 North American Conference on Smart Structures and Materials, 1993, Albuquerque, NM, United States

Abstract

Adaptive control of spacecraft and large structures using Radial Basis Function (RBF) based Artificial Neural Networks (ANN) is investigated. The centers of approximation of the RBFs are allowed to be dynamic in order to provide persistent excitation and a small window of approximation. Both state and time based RBFs are investigated for their ability to identify unmodeled and persistent effects. Integral feedback of the attitude seems necessary, especially when the initial estimates are poor, to eliminate steady state errors for pointing applications. Examples of motion-to-rest as well as tracking maneuvers and vibration suppression are presented.

Citation Download Citation

Srinivas R. Vadali, Tarunraj Singh, Andrew J. Kurdila, and John L. Junkins "Neural-network-based control of large structures", Proc. SPIE 1917, Smart Structures and Materials 1993: Smart Structures and Intelligent Systems, (8 September 1993); https://doi.org/10.1117/12.152819

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