Implementation of the ACO algorithm in an electrical vehicle system powered by five-level NPC inverter

Rtibi, Waad; M'barki, Lotfi; Yaich, M. Iben; Ayadi, Moez

doi:10.1007/s00202-020-01162-9

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…Nowadays, multilevel inverters are widely used in different applications such as high voltage DC systems (1), interfacing inverters of distributed generation (DG) (2)(3)(4)(5), electrical vehicles (6), solid-state transformers (7), and etc. due to their advantages, including delivering higher quality current, low voltage stress of components, higher efficiency, and their ability to operate at low switching frequency (7)(8)(9)(10)(11).…”

Section: Grafical Abstractmentioning

confidence: 99%

Second Order Sliding Mode Control of Three Phase Neutral Point Clamped Inverter in Stationary Frame

Rajabloo,

Lesani,

Mousazadeh Mousavi

et al. 2024

IJE

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Grid-tied Neutral-Point-Clamped (NPC) inverters have been widely used in various applications recently. A superior control method is required to achieve the desired performance of a grid-connected NPC inverter. Accordingly, a second-order sliding mode control (SOSMC) method, which is designed in the stationary frame, is utilized for achieving this aim in this paper. The super-twisting second-order sliding mode control is used for solving the chattering problem of conventional first-order sliding mode control (FOSMC). In comparison to control methods which are applied in rotation frame, this method is not required transformation from rotating frame to a-b-c frame and vice versa and decoupling of d and q components. The Lyapunov stability analysis is used for designing of this controller. The performance of proposed method is evaluated by simulation results implemented in MATLAB/Simulink software. The performance of the SOSMC is also compared with FOSMC. The results show that the incorporation of SOSMC can improve current reference tracking of the NPC inverter in different scenarios.

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Section: Grafical Abstractmentioning

confidence: 99%

Second Order Sliding Mode Control of Three Phase Neutral Point Clamped Inverter in Stationary Frame

Rajabloo,

Lesani,

Mousazadeh Mousavi

et al. 2024

IJE

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“…To improve the search rate and avoid premature convergence of the algorithm, one must improve the ant colony algorithm itself. For example: ant colony algorithm with elite strategy [ 21 ], ant colony algorithm with reconnaissance characteristics [ 22 ], max-min ant system [ 23 ], and other algorithms. The ant colony algorithm with elite strategy mainly marks the ants on the shortest path as “elite” when the algorithm is running and enhances the pheromone on the path.…”

Section: Swarm Intelligence and Its Application In Image Processingmentioning

confidence: 99%

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Cao

et al. 2023

Biomimetics

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Image processing technology has always been a hot and difficult topic in the field of artificial intelligence. With the rise and development of machine learning and deep learning methods, swarm intelligence algorithms have become a hot research direction, and combining image processing technology with swarm intelligence algorithms has become a new and effective improvement method. Swarm intelligence algorithm refers to an intelligent computing method formed by simulating the evolutionary laws, behavior characteristics, and thinking patterns of insects, birds, natural phenomena, and other biological populations. It has efficient and parallel global optimization capabilities and strong optimization performance. In this paper, the ant colony algorithm, particle swarm optimization algorithm, sparrow search algorithm, bat algorithm, thimble colony algorithm, and other swarm intelligent optimization algorithms are deeply studied. The model, features, improvement strategies, and application fields of the algorithm in image processing, such as image segmentation, image matching, image classification, image feature extraction, and image edge detection, are comprehensively reviewed. The theoretical research, improvement strategies, and application research of image processing are comprehensively analyzed and compared. Combined with the current literature, the improvement methods of the above algorithms and the comprehensive improvement and application of image processing technology are analyzed and summarized. The representative algorithms of the swarm intelligence algorithm combined with image segmentation technology are extracted for list analysis and summary. Then, the unified framework, common characteristics, different differences of the swarm intelligence algorithm are summarized, existing problems are raised, and finally, the future trend is projected.

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Research on the method of determining the best measuring area for the circular surface survey

Yang

et al. 2021

Int J Adv Manuf Technol

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Implementation of the ACO algorithm in an electrical vehicle system powered by five-level NPC inverter

Cited by 3 publications

References 30 publications

Second Order Sliding Mode Control of Three Phase Neutral Point Clamped Inverter in Stationary Frame

Second Order Sliding Mode Control of Three Phase Neutral Point Clamped Inverter in Stationary Frame

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

Research on the method of determining the best measuring area for the circular surface survey

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