Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control




fireworks algorithm, fuzzy control, PI control, adaptive, intelligent control of streetlights


As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.


Download data is not yet available.


Usman A M, Abdullah M K. An Assessment of Building Energy Consumption Characteristics Using Analytical Energy and Carbon Footprint Assessment Model. Green and Low-Carbon Economy, 2023, 1(1): 28-40.

Gagliardi G, Lupia M, Cario G, Tedesco F, Cicchello Gaccio F, Lo Scudo F, Casavola A. Advanced adaptive street lighting systems for smart cities. Smart Cities, 2020, 3(4): 1495-1512.

Strielkowski W, Veinbender T, Tvaronavičienė M, Lace N. Economic efficiency and energy security of smart cities. Economic research-Ekonomska istraživanja, 2020, 33(1): 788-803.

Chen X. The intelligent street light control system for preventing heavy fog of expressway based on zigbee. Wireless Personal Communications, 2021, 121(1): 353-359.

Smys D S, Basar D A, Wang D H. Artificial neural network based power management for smart street lighting systems. Journal of Artificial Intelligence and Capsule Networks, 2020, 2(1): 42-52.

Carli R, Dotoli M. A dynamic programming approach for the decentralized control of energy retrofit in large-scale street lighting systems. IEEE Transactions on Automation Science and Engineering, 2020, 17(3): 1140-1157.

Khandagale H P, Zambare R, Pawar P, Jadhav P, Patil P, Mule S. Street light controller with GSM technology. International Journal of Engineering Applied Sciences and Technology, 2020, 4(10): 268-271.

Ahmad S, Siddique A, Iqbal K, Hussain A, Ijaz A. lOT Based Smart Street Light Empowered by Pizeoelectric Sensors. International Journal of Scientific & Technology Research, 2021, 10(1): 341-345.

Kumar N, Rahman S S, Dhakad N. Fuzzy inference enabled deep reinforcement learning-based traffic light control for intelligent transportation system. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(8): 4919-4928.

Kornaga V I, Pekur D V, Kolomzarov Y V, Sorokin V M, Nikolaenko Y E. Design of a LED driver with a flyback topology for intelligent lighting systems with high power and efficiency. Semiconductor Physics, Quantum Electronics & Optoelectronics, 2023, 26(2): 222-229.

de Oliveira Reis O A, Pires R A, dos Reis A K C, Silva E G. Protótipo de um sistema de iluminação e tomada inteligente com o uso da plataforma arduino e internet das coisas. Brazilian Journal of Development, 2021, 7(6): 60103-60118.

JIA R, WU W E I. Case study on intelligent road lighting in foreign countries under the background of smart city. Journal of Humanities and Social Sciences Studies, 2022, 4(1): 235-245.

Gong S, Kumar R, Kumutha D. Design of lighting intelligent control system based on OpenCV image processing technology. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2021, 29(1): 119-139.

Abdullah A, Yusoff S H, Zaini S A, Midi N S, ohamad S Y. Energy efficient smart street light for smart city using sensors and controller. Bulletin of Electrical Engineering and Informatics, 2019, 8(2): 558-568.

Yap K Y, Sarimuthu C R, Lim J M Y. Artificial intelligence based MPPT techniques for solar power system: A review. Journal of Modern Power Systems and Clean Energy, 2020, 8(6): 1043-1059.

Yadav A M, Tripathi K N, Sharma S C. A bi-objective task scheduling approach in fog computing using hybrid fireworks algorithm. The Journal of Supercomputing, 2022, 78(3): 4236-4260.

Han S, Zhu K, Zhou M C, Liu X, Liu H, Al-Turki Y, Abusorrah A. A novel multiobjective fireworks algorithm and its applications to imbalanced distance minimization problems. IEEE/CAA Journal of Automatica Sinica, 2022, 9(8): 1476-1489.

Shen X, Lu J, You X, Song L, Ge Z. A region enhanced discrete multi-objective fireworks algorithm for low-carbon vehicle routing problem. Complex System Modeling and Simulation, 2022, 2(2): 142-155.

Mahmood T, Ali Z. Analysis of Maclaurin symmetric mean operators for managing complex interval-valued q-Rung orthopair fuzzy setting and their applications. Journal of Computational and Cognitive Engineering, 2023, 2(2): 98-115.

Mnif M G, Bouamama S. A new multi-objective firework algorithm to solve the multimodal planning network problem. International Journal of Applied Metaheuristic Computing (IJAMC), 2020, 11(4): 91-113.

Wang W, Liu K, Yang C, Xu B, Ma M. Cyber physical energy optimization control design for PHEVs based on enhanced firework algorithm. IEEE Transactions on Vehicular Technology, 2020, 70(1): 282-291.




How to Cite

Weng G. Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control. EAI Endorsed Trans Energy Web [Internet]. 2023 Nov. 16 [cited 2023 Dec. 10];10. Available from: