北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2024, Vol. 47 ›› Issue (5): 135-143.

• 研究报告 • 上一篇    下一篇

基于干扰观测器的无人自行车非奇异终端滑模控制研究

黄用华1,2,梁子彦2,郭磊3,庄未1,2,骆泽众2   

  1. 1. 北京邮电大学
    2. 桂林电子科技大学
    3. 北京邮电大学 自动化学院
  • 收稿日期:2023-08-19 修回日期:2023-10-25 出版日期:2024-10-28 发布日期:2024-11-10
  • 通讯作者: 庄未 E-mail:zhuangweibupt@sohu.com
  • 基金资助:
    挂接式自平衡两节自行车失稳评测的理论及应用研究;基于动力性和转向性的自平衡自行车车轮驱动力分配研究;自行车骑行“操作-感知”逆向映射关系及其在平衡感知康复医学上的应用;一种平衡感知能力测度的新方法及其应用;双轮驱动自平衡自行车车轮驱动力分配的原理及方法研究

Balance Control of an Unmanned Bicycle Based on Linear Extended Observer and Non-singular Terminal sliding Mode Control

  • Received:2023-08-19 Revised:2023-10-25 Online:2024-10-28 Published:2024-11-10

摘要: 为了实现对无人自行车在不同地形地况、不同负载状态、不同车速场景下的鲁棒控制,结合线性扩张状态观测器(LESO)和非奇异终端滑模控制(NSTSMC)方法设计鲁棒控制器,并搭建物理样机实验平台对其性能进行验证。考虑无人自行车的线性变参数(LPV)模型,通过前馈补偿消除车把动态对车体侧向倾角的耦合;将系统内部参数摄动和外部扰动统一为集总干扰,引入线性扩张状态观测器构造一个只包含车体侧向倾角的改进LPV模型。构造一种非奇异终端滑模面函数,并利用改进的LPV模型设计出控制器的等效控制项和非线性控制项。数值仿真和物理样机实验结果表明:无人自行车能够在花岗岩路面、柏油路面、水泥路面、草坪路面四种不同场地下实现自平衡运动,其侧向倾角均可稳定在[-0.006,0.006](rad)范围内;并且对16.5kg以内的质量负载、1.2m/s-2.4m/s的变化车速以及越过减速带时产生的脉冲干扰具有较强的鲁棒性。

关键词: 无人自行车, 平衡控制, 线性变参数模型, 线性扩张状态观测器, 非奇异终端滑模

Abstract: In order to realize the robust control of unmanned bicycle under different terrain conditions, different load conditions and different speed scenarios, a robust controller was designed by combining Linear Expanding State Observer (LESO) and Non-singular Terminal Sliding Mode Control (NSTSMC) method, and a physical prototype experiment platform was built to verify its performance. Considering the linear variable parameter (LPV) model of the unmanned bicycle, The coupling between the steering angle dynamics and the lean angle is eliminated by feed-forward compensation; the internal uncertainties and external disturbances of the system are combined into lumped disturbances, and a linear extended state observer is introduced to construct an improved LPV model that only includes the lean angle. A non-singular terminal sliding surface is chosen, and the equivalent control and nonlinear control of the controller are designed by using the improved LPV model. The results of numerical simulation and physical prototype experiments show that the unmanned bicycle can realize self-balancing motion on four different grounds: granite road, asphalt road, cement road and lawn. Its lean angle can be stabilized at [-0.006,0.006](rad) range; it also has strong robustness for the mass load within 16.5kg, the changing vehicle speed of 1.2m/s-2.4m/s, and the pulse interference generated when crossing the speed bump.

Key words: Unmanned bicycle, Balance control, Linear variable parameter, Linear extended state observer, Non-singular terminal sliding mode control

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