Detection of delamination in laminated composites with limited measurements combining PCA and dynamic QPSO

Rao, A. Rama Mohan; Lakshmi, K.; S, Krishna Kumar

doi:10.1016/j.advengsoft.2015.04.005

Cited by 47 publications

(13 citation statements)

References 49 publications

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“…35 At present, QPSO has been successfully applied in processing constraints, optimization problems, multi-objective optimization problems, neural network training, and clustering problems. 36–38…”

Section: Quantum-behaved Pso and Sqpmentioning

confidence: 99%

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Feng

Yang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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Focusing on the long-distance rapid cooperative rendezvous of two spacecraft under finite continuous thrust, this paper proposes a practical strategy for space operation using multiple specific-direction thrusts. Based on the orbital dynamic theory and Pontryagin’s maximum principle, the dynamic equations and optimal control equations for radial, circumferential, and normal thrust are determined. The optimization method is a hybrid algorithm. The initial costate variables for the fuel-optimal rapid cooperative rendezvous problem are obtained using quantum particle swarm optimization and subsequently set as the initial values in the sequence quadratic programming to search for the exact convergent solution. The elliptical and near-circular mission orbital rendezvous for spacecraft with multiple specific-direction thrusts are simulated and optimized. Numerical examples verifying the proposed method are provided. The results facilitate easier realization of rapid spacecraft maneuvering under continuous thrust conditions.

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Section: Quantum-behaved Pso and Sqpmentioning

confidence: 99%

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Feng

Yang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…One way of solving this problem is by formulating the entire reconstruction of input force as well as structural system parameters as an optimization problem and solve this to obtain system parameters and force acting on the structure. Here, we use the recently developed meta-heuristic algorithm called the dynamic QPSO algorithm (Rao et al., 2015) for solving the optimization problem.…”

Section: System Identification Along With Input Dynamic Force Recomentioning

confidence: 99%

“…The dynamic hybrid quantum particle swarm optimizer (DHQPSO), which is a vastly improved version of the basic quantum particle swarm optimization (QPSO) algorithm developed recently by the authors (Rao et al., 2015) is used in the present work for identification of structural parameters as well as the dynamic input force acting on the structure. The DHQPSO algorithm uses multiple sub-swarms with a small number of particles instead of one single swarm and a new dynamic neighborhood topology to further improve the diversification features of the algorithm.…”

Section: System Identification Along With Input Dynamic Force Recomentioning

confidence: 99%

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Dynamic force reconstruction techniques from incomplete measurements

Jayalakshmi

Lakshmi

Rao

2018

Journal of Vibration and Control

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We present two time-domain algorithms derived from the popular Newmark’s time integration algorithm, to reconstruct the input force excitation from the vibration measurements. While the first method uses a direct formulation of the time integration algorithm, the second one uses a regularization tool to solve the associated inverse problem. A modified regularization technique is employed to improve the accuracy of the identification problem. Numerical studies with limited measurements, with measurement noise, multiple load identification etc., are presented to investigate the practical applicability of the two methods. Studies have clearly favored the inverse algorithm with modified regularization technique. Finally modeling errors associated with force reconstruction are investigated and a technique is proposed to identify the system parameters simultaneously while reconstructing the input dynamic force, using a recently developed quantum particle swarm optimization algorithm developed by the authors. The numerical simulation studies presented clearly indicate that the force, as well as the system parameters, can be identified accurately using the proposed algorithm.

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“…PSO was one of the most frequently used one. [45][46][47][48][49][50][51][52] Other incorporated algorithms included GA, [53][54][55][56][57] gravitational search algorithm, [58][59][60] back-propagation (BP) neural network algorithm, 61 and so on.…”

Section: Qieamentioning

confidence: 99%

Quantum-inspired hybrid algorithm for integrated process planning and scheduling

Liu

Wen

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Process planning and job shop scheduling problems are the two classical but crucial activities in manufacturing system. With the approach of integrated process planning and scheduling, the two actual activities are combined to conduct operation selection and operation sequencing with the constraints of practical job shop status. In this article, a quantuminspired hybrid algorithm with the objective of minimum makespan is proposed, aiming to solve integrated process planning and scheduling problems in dynamic manufacturing systems. A hybrid-coding representation is suggested, which is a three-layer structure in numerical representation and Q-bit representation adopted from quantum-inspired evolutionary algorithm. Based on the hybrid-coding representation, customized converting and repairing rules and methods are presented to generate feasible individuals. Q-gate rotation and group leader optimization algorithm are integrated systematically for the population evolution to accelerate the convergence speed of the proposed algorithm. In order to increase the diversity of population, a chaotic map called logistic map is introduced, bringing the stochastic initial individuals. Experiments show that the proposed hybrid algorithm can generate outstanding outcomes for integrated process planning and scheduling instances.

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Detection of delamination in laminated composites with limited measurements combining PCA and dynamic QPSO

Cited by 47 publications

References 49 publications

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Dynamic force reconstruction techniques from incomplete measurements

Quantum-inspired hybrid algorithm for integrated process planning and scheduling

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