基于改进无模型自适应控制的挖掘机无人作业方法
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TP273

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广西科技重大专项(桂科AA22067064);柳州市科技计划项目(2022AAB0101).


Improved model-free adaptive control based unmanned excavator operation scheme
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    摘要:

    针对挖掘机无人作业, 考虑挖掘机工作装置液压系统的强非线性、参数不确定性、时变载荷和高能耗问题, 提出一种改进的全格式动态线性化无模型自适应控制方法. 首先, 通过分析驱动空间与任务空间的映射关系, 将挖掘机铲斗齿尖的轨迹跟踪问题转化为液压缸活塞杆伸缩量跟踪问题; 其次, 为了保证轨迹的连续性和平顺性、降低计算复杂程度、减少系统在启动和停止时的不稳定性, 利用5次NURBS曲线插值方法对挖掘轨迹进行规划; 进一步, 设计改进的全格式动态线性化无模型自适应控制算法实现挖掘机无人作业, 为减少能量消耗在输入准则函数中引入能量函数的惩罚项, 在确保良好跟踪精度的同时实现最优能耗; 最后, 对所提方法进行实例仿真, 验证该方法的可行性和优越性.

    Abstract:

    This paper proposes an improved model-free adaptive control scheme for the unmanned operation of excavators, taking into account that the hydraulic system of excavators has strong nonlinearity, parameter uncertainty, time-varying load and high energy consumption of the excavator during operation. Firstly, the trajectory tracking problem of the bucket tooth tip of the excavator is transformed into a hydraulic cylinder piston rod expansion and contraction tracking problem by analyzing the mapping relationship between the drive space and the task space. Then, a quintic five times NURBS curve interpolation method is used to ensure the continuity and smoothness of the trajectory, reduce computational complexity and minimise system instability during startup and shutdown. Furthermore, the improved full-format dynamic linearized model-free adaptive control algorithm is designed to realize the unmanned operation of the excavator, and in order to reduce the energy consumption, a penalty term of the energy function is introduced into the input criterion function to realize the optimal energy consumption while ensuring the good tracking accuracy. Finally, an example simulation of the proposed scheme is carried out to verify its feasibility and superiority.

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陈阔,刘畅,骆曦,等.基于改进无模型自适应控制的挖掘机无人作业方法[J].控制与决策,2025,40(3):785-793

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  • 收稿日期:2024-04-03
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  • 在线发布日期: 2025-02-11
  • 出版日期: 2025-03-20
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