Parameter Optimization of Three Phase Boost Inverter Using Genetic Algorithm for Linear Loads

Arunkumar, G.; Gnanambal, I.; Naresh, Svk; Karthik, P.C.; Patra, Jagadish Kumar

doi:10.1016/j.egypro.2016.11.224

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Genetic algorithm (GA) is easy to use and a simple method. It also has a wide search area and has been proved that can be used in many applications [5], [6], [7], [8]. GA also can be applied to solve knapsack problem [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage

Rikatsih

Mahmudy

Syafrial

2019

JITeCS

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Agricultural product storage has a problem that need to be noticedbecause it has an impact in gaining the profit according to the number ofproducts and the capacity of storage. Inappropriate combination of productcauses high expenses and low profit. To solve the problem, we propose geneticalgorithm (GA) as the optimization method. Although GA is good enough tosolve the problem, GA not always gives an optimum result in complex searchspaces because it is easy to be trapped in local optimum. Therefore, we presenta hybrid real-coded genetic algorithm and Variable Neighborhood Search(HRCGA-VNS) to solve the problem. VNS is applied after reproductionprocess of GA to repair the offspring and improve GA exploitation capabilitiesin local area to get better result. The test results show that the optimal popsizeof GA is 180, number of generations is 80, combination of cr and mr is 0.7 and0.3 while optimum Kmax of VNS is 40 with number of iterations 50. Eventhough HRCGA-VNS need longer computational time, HRCGA-VNS hasproven to provide a better result based on higher fitness value compared withclassical GA and VNS.

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Section: Introductionmentioning

confidence: 99%

Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage

Rikatsih

Mahmudy

Syafrial

2019

JITeCS

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“…Apart from these traditional methods, several intelligent optimisation techniques can be used to solve the complexity in computational procedure in tuning controller parameters so as to achieve an optimal system design [10], [11]. Recently, numerous studies have discussed heuristic optimisation methods that includes genetic algorithm (GA) [12], Particle Swarm Optimisation (PSO) [13], [14] for improving PID controllers. In [15] PSO has been utilised for PI controller optimization in single phase inverters.…”

Section: Introductionmentioning

confidence: 99%

Analysis and design of single phase voltage-frequency converter with optimized PI controller

Asna¹,

Shareef²,

Khalid³

et al. 2019

IJPEDS

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This paper proposes a new voltage frequency converter (VFC) that converts both voltage and frequency to the required level of voltage and frequency in low voltage networks used in various countries. The proposed converter could be used as a universal power supply for sensitive AC loads. The converter is composed of, input voltage and frequency detection circuitry, full bridge boost rectifier and a DC to AC inverter. In addition, to improve the feasibility and performance of the converter, synchronous reference based PI (SRFPI) controller is adopted, where the system behaves similar to a DC-DC converter. The parameter selection of PI controller is done using a recent optimisation technique called Lightning Search Algorithm (LSA). The simulation of VFC is conducted in MATLAB/Simulink environment. The simulation results shows that LSA based PI controller provides better output voltage regulation with respect to the reference value under various load and input conditions.

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“…Inappropriate selection of PI parameters makes the control loops operate inadequately, resulting in a low control performance [14]. Many tuning methods to estimate the parameters of PI controllers are available in literature; some of them are model based controllers [15], optimization tuning methods [16][17][18] and fuzzy logic controllers [19][20]. However, these methods generally do not guarantee a consistent, reliable, and robust optimal PI controller.…”

Section: Introductionmentioning

confidence: 99%

Universal power converter for low power applications

Asna¹,

Shareef²,

Khalid³

et al. 2019

IJPEDS

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A novel power converter that can perform both voltage and frequency conversion was proposed. Inappropriate power supply can damage sensitive sub-components and render the connected device inoperable. Henceforth, the proposed voltage–frequency converter acts as an interface to plug any electrical device directly into an electrical socket and provide the voltage and frequency required. The converter used a synchronous reference frame proportional–integral (SRFPI) controller to regulate the instantaneous output voltage and to improve steady state performance. Because the PI controller works together with the synchronous reference frame controller, it is difficult to tune the PI control parameters. To overcome this issue, a new meta heuristic optimization technique called lightening search algorithm (LSA) optimization was used to identify the optimum PI parameter values. A detailed description of the system operation and control strategy was presented. Finally, the performance of the converter was analyzed and verified by simulation and experimental results. The experimental result has shown that the proposed system has satisfactory output voltage and frequency under different input voltages.

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Parameter Optimization of Three Phase Boost Inverter Using Genetic Algorithm for Linear Loads

Cited by 7 publications

References 10 publications

Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage

Hybrid Real-Coded Genetic Algorithm and Variable Neighborhood Search for Optimization of Product Storage

Analysis and design of single phase voltage-frequency converter with optimized PI controller

Universal power converter for low power applications

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