Optimal fuzzy controller parameters using PSO for speed control of Quasi-Z Source DC/DC converter fed drive

Ranjani, M.; Murugesan, P.

doi:10.1016/j.asoc.2014.11.007

Cited by 34 publications

(14 citation statements)

References 39 publications

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“…The experimental results confirmed that ELPSO performed well in all the above terms. Ranjania and Murugesan [27] proposed a PSO-based fuzzy controller parameter optimization to overcome the drawbacks of the conventional controller suffering from uncertain parameters and the nonlinear qualities of the quasi-Z source converter, as well as computational inefficiency in optimizing the fuzzy controller parameters. The PSO algorithm was exploited to identify the optimal fuzzy parameters for minimizing the objective (cost) functions and enhancing its feasibility.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

Chen

Nguyen

Chiu

et al. 2015

Int J Adv Manuf Technol

121

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This paper proposes a systematic optimization model of process parameters in plastic injection molding (PIM). Firstly, the Taguchi method is employed for experimentation and data analysis, in which the quality characteristics for the plastic injection product are length and warpage. The control factors for the process are melt temperature, injection velocity, packing pressure, packing time, and cooling time. Moreover, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings. Experimental data are set for the response surface methodology (RSM) in order to analyze and create two quality predictors and two S/N ratio predictors. The two quality predictors are associated with genetic algorithms (GA) to search for an optimal combination of process parameters that meets multiple-objective quality characteristics. Finally, four predictors are combined with the hybrid GA-PSO to find the final optimal combination of process parameters. The confirmation results show that the proposed model not only enhances the stability in the injection molding process, including the quality in length and warpage, but also reduces the costs of and time spent in the PIM process.

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Section: Introductionmentioning

confidence: 99%

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

Chen

Nguyen

Chiu

et al. 2015

Int J Adv Manuf Technol

121

View full text Add to dashboard Cite

show abstract

“…Due to some attractive aspects such as quick convergence and easy implementation, PSO has been broadly applied for different optimization problems [23][24][25][26][27][28][29][30][49][50][51][52]. A set of randomly generated solutions propagates in the whole search space toward the optimal solution over a number of iterations by sharing information between all particles.…”

Section: Pso Algorithmmentioning

confidence: 99%

A memetic algorithm applied to trajectory control by tuning of Fractional Order Proportional-Integral-Derivative controllers

Mousavi

Alfi

2015

Applied Soft Computing

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“…For instance, in [38], the PSO is introduced for wind turbine converters, in [39,40] for photovoltaic systems, in [41] for neural networks training, in [42] for DC/DC converter, in [43][44][45] for energy management, in [46] for Unmanned Aerial Vehicle (UAV) management and control, in [47] for clustering, and so on. The results shown in all these works confirm that an optimization through the PSO can lead to valuable advantages regarding the performance of approaches based on a fuzzy controller.…”

Section: Introductionmentioning

confidence: 99%

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

2017

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Abstract:Energy efficiency is a fundamental requirement for a wireless protocol to be suitable for use within the Internet of Things. New technologies are emerging aiming at an energy-efficient communication. Among them, Bluetooth Low Energy is an appealing solution. Recently, the specifications of Bluetooth 5 have been presented with the purpose to offer significant enhancements compared to the earlier versions of the protocol. Bluetooth 5 comes with new communication modes that differ in range, speed, and energy consumption. This paper proposes a fuzzy-based solution to cope with the selection of the communication mode, among those introduced with Bluetooth 5, that allows the best energy efficiency. This communication mode, used by mobile devices, is dynamically regulated by varying the transmission power, returned as the output of a Fuzzy Logic Controller (FLC). A Particle Swarm Optimization (PSO) algorithm is presented to achieve the optimal parameters of the proposed FLC, i.e., optimizing the triangular membership functions, by varying their range, to reach the best results concerning the battery life of mobile devices. The proposed FLC is based on triangular membership functions because they represent a good trade-off between computation cost and efficiency. The paper presents a detailed description of the FLC design, a logical analysis of the PSO algorithm for the derivation of best performance conditions values, and experimental assessments, obtained through testbed scenarios.

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Optimal fuzzy controller parameters using PSO for speed control of Quasi-Z Source DC/DC converter fed drive

Cited by 34 publications

References 39 publications

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

A memetic algorithm applied to trajectory control by tuning of Fractional Order Proportional-Integral-Derivative controllers

Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things

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