Control of Smart Structures Using Analog Neural Network Hardware

摘要

In this paper a robust controller has been implemented on a smart structure testarticle using the Intel's Electronically Trainable Analog Neural Network (ETANN) chip 18O17ONX. 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. 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 has 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. (KAR) P. 1.