首页> 外文会议>Mechatronics, 2009. ICM 2009 >Application of neuro-genetic techniques in solving Industrial Crane kinematic control problem
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Application of neuro-genetic techniques in solving Industrial Crane kinematic control problem

机译:神经遗传学技术在解决工业起重机运动控制问题中的应用

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This work presents a solution to solve industrial cranes kinematic control problem also called automatic travel control (ATC) [10]. Aspects such as optimal trajectory reference calculation considering: process cycle time and distance travelled minimization, improvements in mechanical transmission systems useful life, prohibited areas and obstacles in the crane workspace, etc., and load position control with close tracking of trajectory reference avoiding excessive load swinging angles too, are analyzed and tackled applying intelligent control techniques based on genetic algorithms and neural networks. The use of numerical and Hardware in the Loop (HiL) simulations, together with rapid prototyping advanced tools make quick changes and fast iterations between conceptual, preliminary, detailed, prototyping and validation design stages possible, allowing to reduce embedded control system development time and also increasing industrial crane overall quality.
机译:这项工作提出了解决工业起重机运动学控制问题的解决方案,也称为自动行进控制(ATC)[10]。考虑以下方面的最佳轨迹参考计算:使过程周期时间和行进距离最小化,机械传动系统使用寿命的改善,起重机工作空间中的禁区和障碍物等,以及通过密切跟踪轨迹参考避免过度负载的负载位置控制还使用基于遗传算法和神经网络的智能控制技术来分析和解决摆动角度。使用数值和硬件在环(HiL)仿真以及快速原型开发高级工具,可以在概念,初步,详细,原型设计和验证设计阶段之间进行快速更改和快速迭代,从而减少嵌入式控制系统的开发时间,并且提高工业起重机的整体质量。

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