FPGA-Enhanced 2D FIR Filter Framework with Intelligent Stability Assessment for Advanced Control Systems

Abstract Background: In modern control systems, rapid and accurate signal processing is essential for ensuring system stability and adaptive fault response. Methods: This study presents a two-dimensional finite impulse response (2-D FIR) filter framework optimized for Field-Programmable Gate Array (FPGA) hardware and enhanced with a lightweight intelligent algorithm model to predict system stability. The design applies memory-based computation and pipelined computation to minimize delay and logic utilization. findings: Implementation on a Xilinx Artix-7 Field-Programmable Gate Array (FPGA) demonstrates up to 38% improvement in throughput, a 27% reduction in power use, and a classification accuracy of 94%. summary and outlook: The developed system provides a scalable hardware solution for time-critical embedded control applications that demand both high-speed filtering and predictive fault resilience.