Performance of EAs for four-bar linkage synthesis

Acharyya, Sreangsu; Mandal, Madhab Chandra

doi:10.1016/j.mechmachtheory.2009.03.003

Cited by 160 publications

(153 citation statements)

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“…The first case was presented by Acharyya and Mandal (2009). The authors of this paper considered the synthesis with timing defined by data given in tab 1 tab 1 = (0, 0, 0.5236), (1.9098, 5.878, 1.0472), (6.9098, 9.511, 1.5708), (13.09, 9.511, 2.0944), (18.09, 5.878, 2.618), (20, 0, 3.1416) The input geometric constraints were:…”

Section: Casementioning

confidence: 99%

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Reduced number of design parameters in optimum path synthesis with timing of four-bar linkage

Buśkiewicz

2018

jtam

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The paper presents the method for the optimal synthesis of four-link mechanism generating open/closed paths with time prescription. Although the method is suitable for both closed and open paths, it enables decreasing the number of design parameters describing dimensions, orientation and position of a path generator. Compared to the methods presented in the references, this is a one-phase synthesis method; although the number of design parameters is reduced, the method does not require affine transformations to be performed on the synthesised mechanism. The effectiveness of the method is discussed based on examples of three paths, with two taken from the literature.

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Section: Casementioning

confidence: 99%

“…The method error δ = 2.767, and the absolute Euclidian error E = 2.10037. Three EAs namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) were applied separately in (Acharyya and Mandal, 2009). The best solution obtained using DE is presented in Table 1.…”

Section: Casementioning

confidence: 99%

Reduced number of design parameters in optimum path synthesis with timing of four-bar linkage

Buśkiewicz

2018

jtam

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“…Figure 2 shows four bar mechanism in general coordinate system [16,26]. The design procedure of a four-bar linkage starts with the vector loop equation referring to Figure 2.…”

Section: Kinematics Of Four Bar Mechanismmentioning

confidence: 99%

Matlab�s GA and Optimization Toolbox: A Fourbar Mechanism Application

Dülger¹,

Erdoğan²,

Kütük³

2014

Int J Intell Syst Appl Eng

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This study presents an optimization approach for synthesis of planar mechanisms. A four bar mechanism is chosen for an application example. This mechanism is studied with the constraints assigned. Genetic Algorithm (GA) is applied during optimization study. GA in Optimization Toolbox is then compared with nonlinear constrained numerical optimization command; fmincon in Matlab©. Different case studies are performed by considering different target points. These mechanisms are drawn using Excel© spread sheet to see their animations. An optimization example is presented here. Performances of both algorithms are then compared in terms of coupler curves precision points. Their use in designing a four bar mechanism is explored for its further use.

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“…In [1], the path synthesis of a four-bar mechanism (FBM) to track more than five points in the coupler link is solved by using three different evolutionary algorithms DOI: 10.14736/kyb-2014- with a new refinement technique. In that work, the DE shows faster convergence to the optimal result and a smaller error of adjustment to target points, than the genetic algorithm (GA) and the particle swarm optimization (PSO).…”

Section: Introductionmentioning

confidence: 99%