A comparison of swarm intelligence algorithms for structural engineering optimization

Parpinelli, Rafael Stubs; Teodoro, Fábio R.; Lopes, Heitor Silvério

doi:10.1002/nme.4295

Cited by 26 publications

(9 citation statements)

References 43 publications

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“…In view of the group performance of swarm of bees, fish, birds and other animals, the idea of PSO is established (Hassanzadeh and Mobayen, 2008b; Hassanzadeh et al, 2008). The PSO algorithm is a stochastic evolutionary computational technique according to the movement of the social groups seeking the greatest fecund feeding position (Parpinelli et al, 2012). PSO algorithm is based on the rule that all of the answers are proposed as particles in the swarm.…”

Section: Resultsmentioning

confidence: 99%

Robust global second-order sliding mode control with adaptive parameter-tuning law for perturbed dynamical systems

Mobayen

Tchier

2017

Transactions of the Institute of Measurement and Control

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This paper offers an adaptive global second-order sliding surface for perturbed dynamical systems with matched and unmatched external disturbances. Based on the composite nonlinear feedback theory, a nonlinear function Ψ( x1) is employed in the switching surface to adjust the damping ratio of the controlled system. Initially, using a constant gain matrix, a small value of the damping ratio is achieved presenting a fast performance. As the system state converges to the origin, the damping ratio of the closed-loop system is increased that yields fast settling time and a low overshoot. A novel smooth and chattering-free controller is proposed to fulfill the removal of the reaching mode and the existence of the sliding behavior around the surface from the beginning. The adaptive gain tuning controller reduces the required information for the upper bound of disturbances. Moreover, the selection of the constant parameters μ1 and τ1 for the control law is turned into a cost function and solved by a particle swarm optimization method. Several criteria are derived to assure the robust stability of the uncertain dynamical system. Some simulations are offered to demonstrate the effectiveness of the planned technique.

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Section: Resultsmentioning

confidence: 99%

Robust global second-order sliding mode control with adaptive parameter-tuning law for perturbed dynamical systems

Mobayen

Tchier

2017

Transactions of the Institute of Measurement and Control

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“…Unfortunately, those computational methods often suffer from numerical instability and premature convergence due to their inefficient search capabilities and high complexity. Recently, swarm intelligence (SI) algorithms have been proven to be a competitive approach to deal with such difficult problems [21][22][23][24]. Generally speaking, SI algorithms are inspired by nature or population-based.…”

Section: Methodsmentioning

confidence: 99%

A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems

Zhu

Wang

et al. 2021

Mathematics

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Path-planning for uninhabited combat air vehicles (UCAV) is a typically complicated global optimization problem. It seeks a superior flight path in a complex battlefield environment, taking into various constraints. Many swarm intelligence (SI) algorithms have recently gained remarkable attention due to their capability to address complex optimization problems. However, different SI algorithms present various performances for UCAV path-planning since each algorithm has its own strengths and weaknesses. Therefore, this study provides an overview of different SI algorithms for UCAV path-planning research. In the experiment, twelve algorithms that published in major journals and conference proceedings are surveyed and then applied to UCAV path-planning. Moreover, to demonstrate the performance of different algorithms in further, we design different scales of problem cases for those comparative algorithms. The experimental results show that UCAV can find the safe path to avoid the threats efficiently based on most SI algorithms. In particular, the Spider Monkey Optimization is more effective and robust than other algorithms in handling the UCAV path-planning problem. The analysis from different perspectives contributes to highlight trends and open issues in the field of UCAVs.

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“…Thus, PSO is a good option to solve the posture optimization problem. Besides, the effectiveness of PSO in engineering optimization problems has been verified by many researchers [15,29,34,35].…”

Section: Posture Optimization Algorithm Based On the Skin Modelmentioning

confidence: 95%

Posture Optimization Algorithm for Large Structure Assemblies Based on Skin Model

Zhang

Sherar

et al. 2018

Mathematical Problems in Engineering

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Geometric deviations inevitably occur in product manufacturing and seriously affect the assembly quality and product functionality. Assembly simulations on the basis of computer-aided design (CAD) package could imitate the assembly process and thus find out the design deficiencies and detect the assemblability of the components. Although lots of researches have been done on the prediction of assembly variation considering the geometric errors, most of them only simplify the geometric variation as orientation and position deviation rather than the manufacturing deformation. However, in machinery manufacturing, even if the manufacturing defects are limited, they could propagate and accumulate through components and lead to a noncompliant assembly. Recently, many point-based models have been applied to assembly simulation; however they are mainly interested in simulating the resulting positions of the assembled parts and lack the consideration of the postprocessing after positioning. This paper enriches the complete assembly simulation process based on skin model and presents a simple and effective posture evaluation and optimization method. The studied approach includes a software algorithm applied to evaluate the contact state of the assembly parts and a mathematical model based on the particle swarm optimization to acquire the optimal assembly posture. To verify the efficiency and feasibility of the proposed method, a case study on the aircraft wing box scaling model assembly is performed.

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A comparison of swarm intelligence algorithms for structural engineering optimization

Cited by 26 publications

References 43 publications

Robust global second-order sliding mode control with adaptive parameter-tuning law for perturbed dynamical systems

Robust global second-order sliding mode control with adaptive parameter-tuning law for perturbed dynamical systems

A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems

Posture Optimization Algorithm for Large Structure Assemblies Based on Skin Model

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