Performances Comparison of The Bees Algorithm and Genetic Algorithm for PID Controller Tuning

Şen, Muhammed Arif; Bakırcıoğlu, Veli; Kalyoncu, Mete

doi:10.1145/3036932.3036951

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…These parameters are generally determined by trial-and-error methods based on experience, taking into account the computing load and time. 44 The BA requires a number of parameters to be set as given Table 4. The general flow-chart of this study and the pseudo code for the BA are showed in Figure 2.…”

Section: Optimization Of the Bamentioning

confidence: 99%

Heuristic optimization of impeller sidewall gaps-based on the bees algorithm for a centrifugal blood pump by CFD

et al. 2021

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Optimization studies on blood pumps that require complex designs are gradually increasing in number. The essential design criteria of centrifugal blood pump are minimum shear stress with maximal efficiency. The geometry design of impeller sidewall gaps (blade tip clearance, axial gap, radial gap) is highly effective with regard to these two criteria. Therefore, unlike methods such as trial and error, the optimal dimensions of these gaps should be adjusted via a heuristic method, giving more effective results. In this study, the optimal gaps that can ensure these two design criteria with The Bees Algorithm (BA), which is a population-based heuristic method, are investigated. Firstly, a Computational Fluid Dynamics (CFD) analysis of sample pump models, which are selected according to the orthogonal array and pre-designed with different gaps, are performed. The dimensions of the gaps are optimized through this mathematical model. The simulation results for the improved pump model are nearly identical to those predicted by the BA. The improved pump model, as designed with the optimal gap dimensions so obtained, is able to meet the design criteria better than all existing sample pumps. Thanks to the optimal gap dimensions, it has been observed that compared to average values, it has provided a 42% reduction in aWSS and a 20% increase in efficiency. Moreover, original an approach to the design of impeller sidewall gaps was developed. The results show that computational costs have been significantly reduced by using the BA in blood pump geometry design.

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Section: Optimization Of the Bamentioning

confidence: 99%

Heuristic optimization of impeller sidewall gaps-based on the bees algorithm for a centrifugal blood pump by CFD

et al. 2021

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“…The paper [15] comparing both Genetic Algorithm (GA) and Bees Algorithm in tuning PID parameters. In [16,17] Genetic Algorithm are used to find controller parameters but searcher of [18] used Bees Algorithm to get best selection for parameters.…”

Section: There Are Many Different Controllers Algorithms and Design Tmentioning

confidence: 99%

Design of Interval Type-2 Fuzzy Logic Controllers Based on Several Evolutionary Optimization Algorithms for Inverted Pendulum System

Ghaleb¹,

Oglah²

2020

IRJIET

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This paper compared the performance between type-1 and type-2 of fuzzy logic controller for inverted pendulum system as a controlling plant. The parameters of each controller were tuned with four of evolutionary optimization algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Social Spider Optimization (SSO). The comparisons carried out between the controllers of fuzzy type-1and fuzzy type-2 as well as between several optimization algorithms with fuzzy typ-2 itself. The results of comparisons proved that the fuzzy type-2 controller with SSO has been achieved the best time response characteristics and the least tuning time.

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“…This way consumes significant effort and time; therefore, many evolutionary optimization algorithms are widely common used as: as Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), social spider optimization (SSO), Genetic Algorithm (GA), Bees Algorithm. Paper [15] compared both the Genetic Algorithm (GA) and Bees Algorithm in tuning PID parameters. In [16,17] Genetic Algorithm is used to find controller parameters, but searcher of [18] used the Bees Algorithm to get the best selection for parameters.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Fuzzy Logic Controller for Inverted Pendulum System Based on Evolutionary Optimization Algorithms

Ghaliba¹,

Oglah²

2020

ETJ

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The inverted pendulum is a standard classical problem in the branch of control and systems. If a cart is bushed by force then its position and angle of the pendulum will be changed. Several controllers may employed, keeping the pendulum arm upright by controlling at the cart location. In this search paper, the fuzzy-like PID (FPID) controller has been used to control the inverted pendulum, and the parameters of the controller are tuned with several evolutionary optimization algorithms like a genetic algorithm (GA), ant colony optimization (ACO), and social spider optimization (SSO.) The result of tuned FPID with evolutionary optimization is compared with conventional PID, and it shows that FPID with SSO has been given the best result.

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Performances Comparison of The Bees Algorithm and Genetic Algorithm for PID Controller Tuning

Cited by 9 publications

References 11 publications

Heuristic optimization of impeller sidewall gaps-based on the bees algorithm for a centrifugal blood pump by CFD

Heuristic optimization of impeller sidewall gaps-based on the bees algorithm for a centrifugal blood pump by CFD

Design of Interval Type-2 Fuzzy Logic Controllers Based on Several Evolutionary Optimization Algorithms for Inverted Pendulum System

Design and Implementation of a Fuzzy Logic Controller for Inverted Pendulum System Based on Evolutionary Optimization Algorithms

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