Paper
11 July 2002 Self-configurable digital controllers for smart structural systems using FPGAs
Venkat R. Satagopan, Vittal S. Rao, Kyle Mitchell, Hardy Joseph Pottinger
Author Affiliations +
Abstract
Smart structural systems require control systems, which are integrated into structures, to be small, light weight and power-efficient. Re-configurable digital signal processing using Field Programmable Gate Arrays (FPGAs) is now preferred over Digital Signal Processors (DSPs) and Application Specific Integrated Circuits (ASICs) for high performance applications. The FPGAs, due to their re-programmable and dynamic nature, are more suitable in developing hardware implementations because several configurations can be tested and experimented easily without any additional hardware cost. Being small, lightweight and power-efficient, FPGAs are one of the best platforms for building controllers for smart structures. Distributed Arithmetic is a widely used technique for hardware efficient implementations of inner product between a fixed and a variable data vectors. The computational requirements of smart structural controller match this type very well. The objective of the research is to design easily configurable, stand-alone smart controller, which could be used for real-time control applications. Self-configurable controllers are implemented and tested on a cantilevered beam.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Venkat R. Satagopan, Vittal S. Rao, Kyle Mitchell, and Hardy Joseph Pottinger "Self-configurable digital controllers for smart structural systems using FPGAs", Proc. SPIE 4700, Smart Structures and Materials 2002: Smart Electronics, MEMS, and Nanotechnology, (11 July 2002); https://doi.org/10.1117/12.475036
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Field programmable gate arrays

Digital signal processing

Logic

Control systems

Signal processing

Matrices

Transform theory

Back to Top