What a Simple Solar Tracker Taught Me About Reliable Control

The four-week Electronics I project used an Arduino UNO, two light-dependent resistors, an SG90 servo, and a custom 3D-printed frame. A vertical divider between the sensors created a directional difference in light intensity, while the controller used that difference to decide when and where to move the panel.

A single-axis design was intentional. It reduced mechanical and software complexity while preserving the central learning objective: integrating analog sensing, embedded logic, actuation, and physical construction into one working prototype.

At first, it was easy to think of the LDR readings as clean inputs. In practice, the readings depended on component variation, sensor orientation, the height and position of the divider, and the alignment of the entire frame. The software could only respond to the physical information the assembly produced.

That made mechanical alignment part of the sensing system rather than a separate finishing task. Moving a sensor or changing the divider geometry could alter behavior as much as changing the code. The lesson was simple: when software reads the physical world, construction quality becomes part of data quality.

Without a threshold, small variations between the two sensors caused the servo to react continuously. The system was technically responsive, but the visible oscillation made it less stable and placed unnecessary demand on the actuator.

The solution was a threshold-based deadband. The controller moved only when the difference between the two sensor readings exceeded 10. Inside that range, it held the current position. This accepted a small amount of measurement imbalance in exchange for calmer and more reliable operation.

difference = leftSensor - rightSensor

if absolute(difference) > 10:
    move toward the brighter sensor
else:
    hold the current position

This was my clearest lesson from the project: a controller should not react to every change it can detect. It should react to changes that matter to the behavior of the system.

Tinkercad simulation helped verify the circuit structure and the basic control sequence before physical assembly. That reduced avoidable debugging and gave the team confidence that the core logic was sound.

The physical prototype then revealed problems the simulation could not represent well: sensor mismatch, mechanical alignment, changing light conditions, and servo response. Neither stage replaced the other. Together, they created a more efficient validation process.

The tracker used two sensors, one axis, and threshold-based control. A more advanced design could have added a second axis, predictive solar positioning, data logging, or wireless monitoring. Those are valuable directions, but they were not necessary to answer the project’s main question.

Choosing the smaller system made integration, testing, and explanation more manageable. It also made the tradeoff explicit: lower complexity and cost in exchange for limited tracking range. That is different from leaving features out accidentally. A constrained design is strongest when its boundaries are understood and documented.

The finished system tracked the strongest light source, maintained stable real-time operation, and connected the embedded software with a purpose-built mechanical assembly. More importantly, the build produced decisions and observations that can guide future control projects.

• The two-sensor arrangement produced usable directional information.
• The deadband reduced oscillation caused by small sensor variations.
• Simulation shortened early circuit and logic debugging.
• Physical testing exposed calibration and alignment as system-level concerns.

1. 01Arduino Solar Tracker project recordFull design, implementation, and results.
2. 02Solar Tracker source repositoryProject source and implementation record.