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5 May 1995 Control of smart structures using analog neural network hardware
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Abstract
In this paper a robust controller has been implemented on a smart structure test article using the Intel's Electronically Trainable Analog Neural Network (ETANN) chip i80170NX. The smart structure test article used in this study was a cantilever plate with a pair of PZTs as actuators and PVDF film sensors. A two step connectionist approach was used to design and implement the neural network based controller. To meet the desired closed loop performance requirements, a simple linear quadratic regulator (LQR) controller is designed. The spatially distributed sensors allow the direct measurement and feedback of the states of the system. A copy of this controller is transferred into the ETANN chip and the trained chip is used to control the test system. A custom board and electronic circuits were developed for interfacing the neural network chip and the smart structure test article. The steps involved in training and implementing robust controllers on a smart structure have been outlined. Some of the practical considerations of implementing a robust controller using the ETANN chip have been pointed out and dealt with. Experimental verification of the closed loop performance of the conventional LQR controller as well as the neural network controller are also shown.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rajendra R. Damle, Vittal S. Rao, Steven F. Glover, and Frank J. Kern "Control of smart structures using analog neural network hardware", Proc. SPIE 2442, Smart Structures and Materials 1995: Mathematics and Control in Smart Structures, (5 May 1995); https://doi.org/10.1117/12.208860
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