An improved immune algorithm for optimizing the pulse width modulation control sequence of inverters

Sheng, Long; Qian, Shuqu; Ye, Y.Q.; Wu, Yuheng

doi:10.1080/0305215x.2016.1250894

Cited by 9 publications

(11 citation statements)

References 28 publications

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“…The main advantages of PSOs are their learning ability to determine optimum switching angles with high accuracy for a broad range of modulation indices. Therefore, a large number of metaheuristic algorithms, such as whale optimization algorithm (WOA) [14], differential evolution (DE) [15], differential harmony search (DHS) [16], genetic algorithm (GA) [17], improved immune algorithm (IIA) [18], and bacterial foraging (BP) algorithm [19] are utilized to enhance the performance of the SHEPWM.…”

Section: A Related Workmentioning

confidence: 99%

“…However, the results were not satisfactory as this technique was only applicable to high-frequency modulation techniques and they also suffer from the blackbox constraints of neural networks [22], [23]. In the case of the IIA, the final results were highly unsatisfactory as reported in [18]. As a result, this algorithm could not produce any solution and decrease the total harmonic distortions (THD) after the modulation index has reached a certain value.…”

Section: A Related Workmentioning

confidence: 99%

“…Also, few case studies cannot validate the superiority of an algorithm over other algorithms. This is because the performance of these algorithms can widely vary depending on SHEPWM parameters such as the number of voltage levels produced by MLIs, number of targeted harmonics, number of switching angles, and sets of nonlinear equations [4], [15]- [18]. This also demands an algorithm that can be proven superior to other algorithms under various case studies taking different sets of SHEPWM parameters.…”

Section: B Research Gap and Motivationsmentioning

confidence: 99%

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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters

et al. 2021

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Selective harmonic elimination (SHE) technique is used in power inverters to eliminate specific lower-order harmonics by determining optimum switching angles that are used to generate Pulse Width Modulation (PWM) signals for multilevel inverter (MLI) switches. Various optimization algorithms have been developed to determine the optimum switching angles. However, these techniques are still trapped in local optima. This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. This algorithm is formulated by utilizing habitual characteristics of bats. It has advanced learning ability that can effectively remove lower-order harmonics from the output voltage of MLI. It can eventually increase the quality of the output voltage along with the efficiency of the MLI. The performance of the algorithm is evaluated with three different case studies involving 7, 11, and 17-level three-phase MLIs. The results are verified using both simulation and experimental studies. The results showed substantial improvement and superiority compared to other available algorithms both in terms of the harmonics reduction of harmonics and finding the correct solutions.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: B Research Gap and Motivationsmentioning

confidence: 99%

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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters

et al. 2021

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“…In this paper, k max and f v are optimized using the immune particle swarm algorithm (IPSO), which integrates part of the immune algorithm [32] into the PSO algorithm [33], and 30 particles are used in PSO. Each particle has an initial velocity range of [-50,50].…”

Section: Ipso and Gabor Filtermentioning

confidence: 99%

Constrained unsteady-state iris fast certification for lightweight training samples based on the scale change stable feature and multi-algorithm voting

Liu

Zhu

et al. 2020

PLoS ONE

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Aiming at the problem of fast certification for a constrained iris in the same category caused by the unstable iris features caused by the change of the iris acquisition environment and shooting status under lightweight training samples, a one-to-one fast certification algorithm for constrained unsteady-state iris based on the scale change stable feature and multi-algorithm voting is proposed. Scale change stable features are found by constructing an isometric differential Gaussian space, and a local binary pattern algorithm with extended statistics (ES-LBP), the Haar wavelet with over threshold detection and the Gabor filter algorithm with immune particle swarm optimization (IPSO) are used to represent the stable features as binary feature codes. Iris certification is performed by the Hamming distance. According to the certification results of three algorithms, the final result is obtained by multi-algorithm voting. Experiments with the JLU and CASIA iris libraries under the iris prerequisite conditions show that the correct recognition rate of this algorithm can reach a high level of 98% or more, indicating that this algorithm can improve the operation speed, accuracy and robustness of certification.

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“…Among the many techniques employed for solving such optimization problems are variants of Genetic Algorithms, Simulated Annealing, Artificial Neutral Networks, Particle Swarm Optimization, Bee Algorithm, Fuzzy Logic, Frog Leaping Algorithm and random search based heuristics. The reader is referred to Dahidah and Agelidis (2008), Haghdar, Shayanfar, and Alavi (2011), Lee, Chu, Idris, Goh, and Heng (2015), Maia, Mateus, Ozpineci, Tolbert, Pinto, et al (2013), Kumle, Fathi, Jabbarvaziri, Jamshidi, and Yazdi (2015), Kavousi, Vahidi, Salehi, Bakhshizadeh, Farokhnia, and Fathi (2012), Lou, Mao, Wang, Lu, and Wang (2014) Sheng et al (2016), Fisher and Sharaf (1994), Kumar and Vasudevan (2005), Lohia, Mishra, Karthikeyan, and Vasudevan (2008), Nanda Kumar and Vasudevan (2006), Qian, Ye, Liu, and Xu and Franquelo, Napoles, Guisado, León, and Aguirre (2007) for more details. Another broad set of methods depend on gradient search, see for example Agelidis, Balouktsis, and Cossar (2008).…”

Section: Introductionmentioning

confidence: 99%

A linear programming approach for designing multilevel PWM waveforms

Mohan

Bhikkaji

Poongothai

et al. 2020

International Journal of Control

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This paper considers the problem of designing a multilevel pulse width modulated waveform (PWM) with a prescribed harmonic content. Multilevel PWM design plays a major role in many diverse engineering disciplines. In power electronics, multilevel PWM design corresponds to determining the inverter switching times and levels for selective harmonic elimination and harmonic compensation. In mechatronics, the same design corresponds to shaping input signals to damp residual vibrations in flexible structures. More generally, in most applications, the aim of PWM design is to minimize the total harmonic distortion while adhering to a prescribed harmonic content. The solution approach presented in this paper is based on linear programming with the objective of minimizing the total harmonic distortion. This objective is achieved within an arbitrarily small bound of the optimal solution. In addition, the linear programming formulation makes the design of such switching waveforms computationally tractable and efficient. Simulations are provided for corroboration.

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An improved immune algorithm for optimizing the pulse width modulation control sequence of inverters

Cited by 9 publications

References 28 publications

Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters

Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters

Constrained unsteady-state iris fast certification for lightweight training samples based on the scale change stable feature and multi-algorithm voting

A linear programming approach for designing multilevel PWM waveforms

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