ETHER: An Adaptive Solar Tracking System
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Date
2026
Authors
Mohammad Raed
Mohammad Matar
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Abstract
The growing global demand for renewable energy has emphasized the critical need for maxi-
mizing solar energy system efficiency. This project presents the design and implementation of
an intelligent dual-axis solar tracking system that integrates embedded control, wireless con-
nectivity, and FPGA-based hardware acceleration to enhance tracking precision and system
responsiveness.
The system architecture comprises three main components working in coordination: an
Arduino microcontroller implementing a Proportional-Integral-Derivative (PID) controller to
drive servo motors for precise panel orientation, an ESP32 module providing wireless connectiv-
ity for system monitoring and dashboard applications, and a DE1-SoC FPGA board executing
a Kalman filter algorithm for predictive control. The Arduino calculates solar position using
built-in algorithms and communicates with the FPGA via UART protocol to transmit sensor
data and receive filtered position estimates. The FPGA implementation utilizes DSP slices to
accelerate the mathematical computations of the Kalman filter, providing real-time predictive
adjustments that compensate for measurement delays and noise in the control system.
The developed system successfully demonstrates improved tracking accuracy through the
integration of predictive filtering with embedded PID control. The FPGA-accelerated Kalman
filter effectively reduces positioning errors and system oscillations, while the wireless moni-
toring capability enables real-time performance assessment. Environmental sensors provide
contextual data for comprehensive system evaluation.
This work demonstrates how hardware-software co-design enhances renewable energy sys-
tems through improved precision, adaptability, and computational efficiency. The integration
of predictive control with FPGA acceleration represents a novel approach to solar tracking
that advances beyond traditional microcontroller-only solutions, offering significant potential
for both educational applications and small-scale renewable energy implementations.
Keywords: FPGA, SoC, Kalman Filter, PID Control, Solar Tracking, Embedded Sys-
tems, Renewable Energy, Internet of Things, DE1-SoC, Arduino, ESP32