关键词: 隧道照明, 多因素模糊控制, 自整定比例因子, PID控制, 节能

Abstract: The authors present an intelligent tunnel lighting system designed to overcome challenges such as complex multifactor fuzzy rules, high energy consumption, slow dimming response, and long delays in highway lighting systems. The proposed system employs an improved multifactor fuzzy control algorithm with proportional factor self-tuning (MFC-PFS). First, a fuzzy core layer that utilizes external tunnel brightness and traffic flow as input variables is constructed. A fuzzy correction layer is then established that incorporates vehicle speed and color temperature as additional inputs. The initial required internal brightness is calculated through the core layer and refined by the correction layer, allowing for dynamic brightness adjustment via dual-layer fuzzy control. Simulations reveal that this dual-layer approach effectively regulates color temperature and required brightness while meeting tunnel lighting standards. Notably, the number of fuzzy rules is reduced by 92% compared to traditional single-layer strategies, leading to more precise brightness calculations. The proposed method also achieves a 22.7% increase in energy savings compared to stepwise dimming. To further enhance the tunnel lighting dimming system, a self-tuning module based on fuzzy reasoning is introduced to adaptively adjust brightness deviations and their rates of change. Finally, for comparative experiments, simulation models of traditional proportional-integral-derivative (PID) controllers, fuzzy PID controllers, and PFS fuzzy PID controllers are constructed in a Simulink environment. The results show that both the fuzzy PID and PFS fuzzy PID controllers exhibit no overshoot and deliver effective energy-saving performance. The PFS fuzzy PID dimming system shows a response time reduction of 12.3 and 2.8 s compared to traditional PID and fuzzy PID control, respectively. Overall, the enhanced PFS fuzzy PID control system demonstrates superior accuracy and stability, significantly improving the intelligent lighting performance of highway tunnels.

Key words: tunnel lighting, multifactor fuzzy control, proportional factor self-tuning, proportional-integral-derivative control, energy conservation