Poster + Paper
14 June 2023 FPGA to study the behavior of a maneuvering UGV using sliding innovation filter
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Conference Poster
Abstract
Field programmable gate arrays (FPGAs) are increasingly popular due to their customizability, which enables them to be tailored to specific applications, resulting in minimal resource usage that saves energy and space. In this work, we used an FPGA with a Z-board from Xilinx to simulate the application of the sliding innovation filter (SIF) to a robotic arm. SIF is a predictor-corrector filter used for both linear and nonlinear systems to estimate states and/or parameters. It shares similar principles with sliding mode observer and smooth variable structure filter (SVSF) and uses a correction gain derived to satisfy Lyapunov stability, keeping the estimates near the measurements. We tested SIF on a manipulator with two joints (rotational and prismatic), using FPGA to run the simulation while tracking resource utilization. We compared the results with those of SVSF.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohammad AlShabi, Talal Bonny, and S. Andrew Gadsden "FPGA to study the behavior of a maneuvering UGV using sliding innovation filter", Proc. SPIE 12547, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII, 1254713 (14 June 2023); https://doi.org/10.1117/12.2664149
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KEYWORDS
Field programmable gate arrays

Tunable filters

Signal filtering

Image processing

Artificial intelligence

Control systems

Signal processing

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