Improved Teaching Learning Algorithm with Laplacian operator for solving nonlinear engineering optimization problems

Garg, Vanita; Deep, Kusum; Bansal, Sahil

doi:10.1016/j.engappai.2023.106549

Cited by 8 publications

(1 citation statement)

References 44 publications

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“…Chaotic maps [26,27], orthogonal array [28], and new initialization methods [29,30] improve the convergence performance of the algorithms in the pre-iteration period by improving the initialization distribution of the population. Opposition-based learning [26,27,31], Laplace distribution [31][32][33], Lévy flight [34,35], comprehensive learning (CL) [36][37][38][39], and quadratic interpolation (QI) [40][41][42] are all improvement strategies that increase the diversity of the population and improve the ability of the algorithm to jump out of local optima. How to effectively improve the SO algorithm by using these improvement strategies to improve the convergence speed and optimality search results of the SO algorithm, and to ensure that the SO algorithm has a certain degree of robustness, is a challenge to be solved.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor attitude control by improved snake optimizer based adaptive switching disturbance rejection approach

Zhou,

Chen,

Jiao

2024

Meas. Sci. Technol.

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In this paper, an adaptive switching anti-disturbance attitude control scheme based on improved snake optimizer is proposed for quadrotor attitude control when a quadrotor unmanned aerial vehicle is affected by measurement noise. The adaptive switching disturbance rejection controller (AWDRC) is composed of linear active disturbance rejection control and adaptive switching extended state observer which is used to achieve accurate signals reconstruction performance under measurement noise. Then, the improved snake optimizer (ISO) algorithm is developed with quadratic interpolation and comprehensive learning strategies to obtain the optimal parameters of the quadrotor attitude controller. The performance validity of ISO is demonstrated here by experiments on the CEC-2017 and the CEC-2020 benchmark functions with several state-of-the-art meta-heuristic algorithms. Secondly, the proposed ISO-based AWDRC algorithm is used in quadrotor attitude tracking control and compared with three other excellent active disturbance rejection controllers in a comparative experiment, and the experimental results show the effectiveness of the proposal. Finally, the robustness of the proposed method to parameters perturbation of the quadrotor attitude system is analyzed by Monte Carlo experiments.

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