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<p>Modern lighting systems do not adapt to real-time environmental and occupancy changes using binary and continuous electrical signals. The traditional switch-based systems are inefficient, leading to excessive energy consumption due to poor adaptability. Previous studies use remote control of appliances, but only use binary switches to control the appliances. To address these issues, this research proposes a scalable corridor-waning radiance system using a GA-optimized Fuzzy-PID controller, which integrates both binary and continuous sensors to dynamically adjust lighting based on factors like proximity, ambient light, sound, and human presence. Fuzzy logic manages uncertainties, while GA optimizes PID parameters for better response time, reduced steady-state errors, and improved efficiency. MATLAB/Simulink simulations confirm the system’s superior performance achieving faster rise time of 0.90 s, a settling time of 1.57 s, and a peak time of 2.47 s with minimal error as compared to recent studies. The proposed system can now accommodate the binary and continuous switches and the end-user can scale-up the system inputs by adding more switches with the OR-logic capability.</p>

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Simulation of a scalable corridor waning radiance system using fuzzy PID and genetic algorithm

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月6日

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  • Abdallah Awamu,
  • Jimmy Nabende Wanzala,
  • Michael Robson Atim,
  • Cosmos Dumba

摘要

Modern lighting systems do not adapt to real-time environmental and occupancy changes using binary and continuous electrical signals. The traditional switch-based systems are inefficient, leading to excessive energy consumption due to poor adaptability. Previous studies use remote control of appliances, but only use binary switches to control the appliances. To address these issues, this research proposes a scalable corridor-waning radiance system using a GA-optimized Fuzzy-PID controller, which integrates both binary and continuous sensors to dynamically adjust lighting based on factors like proximity, ambient light, sound, and human presence. Fuzzy logic manages uncertainties, while GA optimizes PID parameters for better response time, reduced steady-state errors, and improved efficiency. MATLAB/Simulink simulations confirm the system’s superior performance achieving faster rise time of 0.90 s, a settling time of 1.57 s, and a peak time of 2.47 s with minimal error as compared to recent studies. The proposed system can now accommodate the binary and continuous switches and the end-user can scale-up the system inputs by adding more switches with the OR-logic capability.