Optimisation of motion cueing position based on adaptive chaos PSO algorithm

被引：1

作者：

Kong X.-T. ^{[1
]}

Zhu Y.-C. ^{[1
]}

Di Y.-Q. ^{[1
]}

Cui H.-H. ^{[1
]}

机构：

[1] Department of Electrics and Optics Engineering, Mechanical Engineering College, Shijiazhuang

来源：

International Journal of Reasoning-based Intelligent Systems | 2016年 / 8卷 / 1-2期

关键词：

ACPSO; Adaptive chaos particle swarm optimisation; MCP; Motion cueing algorithm; Motion cueing position; Simulator;

D O I：

10.1504/IJRIS.2016.080059

中图分类号：

学科分类号：

摘要：

In most simulators, such as flight simulator, to keep the trainers in a high level sensation fidelity, the best motion cueing position needs to be solved firstly. We make analyses to the problem and proposed a model for the problem. Then we figure out the principle and target of the choosing of optimal motion cueing position. Considering the analyses above, we propose an improved adaptive chaos particle swarm optimisation (ACPSO) algorithm. By making the inertial factor adjust adaptively and combining the chaos algorithm with PSO algorithm, the searching range is more flexible and the particles' movement more simultaneous. The changes above realise the simultaneous progressing of global searching and local searching of solutions. Furthermore, local optimal is avoided by this means and the constraint information of the problem is utilised to improve the optimisation effect. Experiment results show that the ACPSO algorithm improves the overall optimisation effect of the optimal position problem, and the optimal motion cueing position make the simulator trainer have a more realistic sensation and maintain the safety of the platform. Copyright © 2016 Inderscience Enterprises Ltd.

引用

页码：15 / 22

页数：7

共 17 条

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