Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm

作     者：Nour Ben Ammar Hegazy Rezk Soufiene Bouallègue 

作者机构：Research Laboratory in Automatic Control(LARA)National Engineering School of Tunis(ENIT)University of Tunis EL MANARLe BelvédèreTunis1002Tunisia College of Engineering at Wadi AddawaserPrince Sattam Bin Abdulaziz UniversityAl-Kharj11911Saudi Arabia Department of Electrical EngineeringFaculty of EngineeringMinia UniversityMinia61517Egypt High Institute of Industrial Systems of Gabès(ISSIG)University of GabèsGabès6011Tunisia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第67卷第6期

页      面：4081-4100页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Quadrotor modeling integral sliding mode control gains tuning advanced metaheuristics memetic algorithms shuffled frog leaping algorithm 

摘      要：This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler formalism,a nonlinear dynamic model of the studied quadrotor is firstly established for control design *** the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law,which are usually selected by repetitive and time-consuming trials-errors based procedures,a constrained optimization problem is formulated for the systematically tuning of these unknown *** time-domain operating constraints,such an optimization-based tuning problem is effectively solved using the proposed SFLA metaheuristic with an empirical comparison to other evolutionary computation-and swarm intelligence-based algorithms such as the Crow Search Algorithm(CSA),Fractional Particle Swarm Optimization Memetic Algorithm(FPSOMA),Ant Bee Colony(ABC)and Harmony Search Algorithm(HSA).Numerical experiments are carried out for various sets of algorithms’parameters to achieve optimal gains of the sliding mode controllers for the altitude and attitude dynamics *** studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature *** results verified that the proposed metaheuristicsbased approach is a promising alternative for the systematic tuning of the effective design parameters in the integral sliding mode control framework.