研究目的
To compare the performance and optimization of two types of sun tracker based on tetrahedron geometry using PID and Fuzzy logic algorithm.
研究成果
The fuzzy logic control algorithm is more effective than PID in maximizing the load on solar panels, with an average increase of 3.5% or 20 Watt in energy received. The LDR sensors achieved reference values for sunlight intensity, and the fuzzy controller provided more stable and accurate tracking.
研究不足
The study is limited to a specific experimental setup with tetrahedron geometry and may not generalize to other sensor configurations or environmental conditions. Potential optimizations could include testing under varying weather conditions or with different control parameters.
1：Experimental Design and Method Selection:
The study involves building two identical dual-axis sun trackers with tetrahedron geometry sensors, using PID and fuzzy logic algorithms for control. The PID controller is tuned with the Ziegler-Nichols method, and the fuzzy logic controller uses the Mamdani method with centroid defuzzification.
2：Sample Selection and Data Sources:
The experiment uses solar cells and LDR sensors attached to the sun trackers, with data collected over a period from 12:00 pm to 4:00 pm.
3：List of Experimental Equipment and Materials:
Includes Atmega 328 microcontroller, mechanical systems for dual-axis mechanism, servo mini, solar cell, LDR sensor, mechanical based on tetrahedron geometry, and data logger.
4：Experimental Procedures and Operational Workflow:
The process involves sensor design, prototype construction, programming (using Arduino for PID and Matlab for fuzzy logic), and side-by-side testing with data logging of servo movements and solar cell load.
5：Data Analysis Methods:
Data is sampled at intervals (every minute for load, every 20 minutes for servo response, every 30 minutes for LDR values), and results are compared graphically and tabularly to evaluate performance.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
