Multi-parameter and multi-objective optimisation of articulated monorail vehicle system dynamics using genetic algorithm

Jiang, Yongzhi; Wu, Pingbo; Zeng, Jing; Zhang, Yingsheng; Zhang, Yunchang; Wang, Shuai

doi:10.1080/00423114.2019.1566557

Cited by 54 publications

(25 citation statements)

References 19 publications

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“…It can be applied to optimize both constrained and unconstrained types of problems. Recently, GA is applied in many famous applications of heart diagnosis system [42], nonlinear electric circuit models [43], nonlinear astrophysics based singular system [44], Painlevé equation-II based nonlinear optic models [45], prediction model of air blast [46], Thomas Fermi model [47], and monorail vehicle system [48]. These potential applications of GA inspired the authors to solve the singular pantograph differential model to attain the decision variables of MWNNs.…”

Section: B Optimization Process: Gaipamentioning

confidence: 99%

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

et al. 2021

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The aim of this study is to design a layer structure of feed-forward artificial neural networks using the Morlet wavelet activation function for solving a class of pantograph differential Lane-Emden models. The Lane-Emden pantograph differential equation is one of the important kind of singular functional differential model. The numerical solutions of the singular pantograph differential model are presented by the approximation capability of the Morlet wavelet neural networks (MWNNs) accomplished with the strength of global and local search terminologies of genetic algorithm (GA) and interior-point algorithm (IPA), i.e., MWNN-GAIPA. Three different problems of the singular pantograph differential models have been numerically solved by using the optimization procedures of MWNN-GAIPA. The correctness of the designed MWNN-GAIPA is observed by comparing the obtained results with the exact solutions. The analysis for 3, 6 and 60 neurons are also presented to check the stability and performance of the designed scheme. Moreover, different statistical analysis using forty number of trials is presented to check the convergence and accuracy of the proposed MWNN-GAIPA scheme.

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Section: B Optimization Process: Gaipamentioning

confidence: 99%

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

et al. 2021

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“…The traditional modeling method for vehicle system are the multi rigid body dynamic method and vehiclebridge coupling dynamic method. [31][32][33][34][35][36] The dynamic models of the two method are shown in Figure 7:…”

Section: Simulation Process Of the Vehicle-bridge Coupling Dynamicsmentioning

confidence: 99%

“…It can analyze not only rigid-body systems with multi-degrees of freedom, but also some complex rigid-flexible coupling systems. It is widely used in the machinery, automobiles, railway vehicles, aerospace, monorail, robots, and so on 31.…”

mentioning

confidence: 99%

Intelligent batch process method for analyzing the effect of the suspension parameters on the vibration of the suspended monorail

Jiang

Zeng

et al. 2014

Advances in Mechanical Engineering

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As for the batch process, it is needed to carry out a unique simulation for each group of parameters. The simplest method to achieve this goal is to uses the Simulink as the integration space. It cannot solve some complicated dynamic model set up in dynamic software. This paper introduces an intelligent batch program to enable the model solved in the dynamic software during the simulation. This paper also put forward the road equation for the suspended monorail, which has not been introduced before. The results of multi rigid body dynamics and vehicle bridge coupling dynamics are compared in this paper. It proves that the bridge vibration has little effect on the vehicle system. Through the batch process method, the effect of different parameters on the vehicle system could be obtained.

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“…Kozłowski et al established a full-size dynamic simulation model of a suspension-type PRT system vehicle, verified the model with a physical model (1 : 4), and pointed out that the design parameters of the vehicle should be optimized in order to reduce the vibration and slip of the vehicle passing through a bend [12]. Jiang et al proposed a dynamic optimization model of articulated monorail vehicles based on the genetic algorithm, optimized the suspension parameters of monorail vehicles, and improved the ride comfort [13]. He et al established an improved trainbridge interaction model, investigated the dynamic performance of the suspended monorail vehicle on the circle curve bridge, and found that the rational allocation of shock absorbers could effectively suppress the vibration of the vehicle [14].…”

Section: Introductionmentioning

confidence: 96%

Analysis and Optimization of Driving Attitude and Oscillation Characteristics of Suspension-Type Small Rail Vehicles

Liu

Yue

Lin

et al. 2020

Shock and Vibration

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Suspension-type small rail personal rapid transit systems are widely concerned due to their high efficiency and reliability. The increasing demands for ride comfort have put forward higher requirements for vehicle stationarity. In the study, with a single-bogie vehicle as the research object, a dynamic equation and a simulation model are firstly established to calculate the attitude angle and lateral velocity of the vehicle. Then, with the small amplitude and fast attenuation of the attitude angle and lateral velocity in a straight line and a bend as optimization objectives, the simulation model is optimized in terms of a series of variables, including the bogie with or without the supporting wheel, the supporting wheel tread, the driving wheel tread, the guide wheel tread, and the changes of the center of mass of the vehicle. Then, the problem of severe vehicle pitch with the double-bogie structure is solved. Finally, the simulation results and the optimization scheme are experimentally verified. The above optimization measures can significantly improve the driving stationarity of suspension-type small rail vehicles and enhance ride comfort.

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Multi-parameter and multi-objective optimisation of articulated monorail vehicle system dynamics using genetic algorithm

Cited by 54 publications

References 19 publications

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

Design of Morlet Wavelet Neural Network for Solving a Class of Singular Pantograph Nonlinear Differential Models

Intelligent batch process method for analyzing the effect of the suspension parameters on the vibration of the suspended monorail

Analysis and Optimization of Driving Attitude and Oscillation Characteristics of Suspension-Type Small Rail Vehicles

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