Laith Abualigah1,2,3,4,5,6,*, Serdar Ekinci7, Davut Izci7,8, Raed Abu Zitar9
Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 169-183, 2023, DOI:10.32604/iasc.2023.040291
Abstract Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and… More >
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