From Modeling to Experimental Validation: Design of a Dual-Axis Solar Tracking System
1. Introduction
This work presents the end-to-end design and implementation of a dual-axis solar tracking system, combining nonlinear modeling, embedded control, and real-time experimental validation.
The objective is to maximize photovoltaic energy yield under real environmental conditions by dynamically adjusting the panel orientation according to solar position, while ensuring robustness and practical feasibility.
2. System Overview
The developed system integrates mechanical, electrical, and embedded subsystems into a unified architecture.
It is composed of:
- A photovoltaic panel mounted on a dual-axis mechanical structure
- Two actuators:
- Azimuth rotation (horizontal axis)
- Elevation control (vertical axis)
- Motor drivers (H-bridge based control)
- Embedded control unit (Arduino-based)
- Sensor layer for environmental and positional feedback
- Real-time data acquisition and monitoring system
The architecture ensures continuous tracking of the sun trajectory while maintaining system stability and energy efficiency.
3. Mathematical Modeling
A detailed nonlinear model of the photovoltaic generator was developed to describe its behavior under varying environmental conditions.
The model integrates:
- Irradiance variation
- Temperature dependency
- Electrical characteristics of the PV cell
Parameter identification was performed using data-driven techniques, including:
- Least squares estimation
- ARX-based modeling approaches
These methods enabled accurate estimation of internal parameters and ensured consistency between simulated and real system behavior.
4. Control Strategy
The control system was designed to ensure precise and stable tracking of the sun position.
Key elements include:
- Dual-axis positioning strategy based on solar trajectory
- PWM-based motor control for smooth actuation
- Closed-loop adjustment using sensor feedback
The control approach balances:
- Tracking accuracy
- Energy consumption
- Mechanical constraints
This ensures optimal panel orientation throughout the day while maintaining system reliability.
5. Embedded Implementation
The system was implemented on an embedded architecture centered around an Arduino controller.
Main features:
- Real-time control of both axes via PWM signals
- Interface with motor drivers (H-bridge)
- Integration of sensor inputs for feedback control
- Data acquisition and transmission for monitoring
The embedded layer acts as the core of the system, ensuring synchronization between sensing, control, and actuation.
6. Experimental Validation
A full prototype was developed and tested under real environmental conditions.
Experimental validation included:
- Comparison between simulated and measured power output
- Evaluation of tracking accuracy
- System response under dynamic irradiance conditions
The results confirm strong agreement between theoretical models and real-world measurements.
7. Key Results
The implemented system demonstrated:
- Significant improvement in energy yield compared to fixed panels
- High tracking precision across both axes
- Stable behavior under real operating conditions
- Reliable integration of modeling, control, and embedded execution
These results validate the effectiveness of the proposed approach for practical deployment.
8. Conclusion
This work demonstrates the feasibility of integrating advanced modeling, control strategies, and embedded systems into a robust and scalable solar tracking solution.
It highlights the importance of combining theoretical design with experimental validation to achieve reliable real-world performance.
9. Outlook
Future improvements may include:
- Integration of intelligent optimization algorithms
- AI-based adaptive control strategies
- IoT-enabled monitoring and remote supervision
- Extension toward distributed and networked energy systems