基于双层模型预测控制的双轮足机器人运动控制

杨利辉; 关海杰; 韩奋凯; 曲俊海

doi:10.12382/bgxb.2025.0666

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基于双层模型预测控制的双轮足机器人运动控制

更新时间：2026-04-24

- 基于双层模型预测控制的双轮足机器人运动控制
- Motion Control of Wheeled Bipedal Robot Based on Double-layer MPC
- 兵工学报 2026年47卷第1期页码：250666
- 作者机构：
  
  北方自动控制技术研究所，山西太原 030006
- 作者简介：
  
  *通信作者邮箱：2403500515@qq.com
- 基金信息：
- DOI：10.12382/bgxb.2025.0666
  中图分类号： TP242.6
- 收稿：2025-07-17，
  
  网络首发：2026-02-11，
  
  纸质出版：2026-01-31
- 稿件说明：
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杨利辉, 关海杰, 韩奋凯, 等. 基于双层模型预测控制的双轮足机器人运动控制[J]. 兵工学报, 2026,47(1):250666.

YANG Lihui, GUAN Haijie, HAN Fenkai, et al. Motion Control of Wheeled Bipedal Robot Based on Double-layer MPC[J]. Acta Armamentarii, 2026, 47(1): 250666.
杨利辉, 关海杰, 韩奋凯, 等. 基于双层模型预测控制的双轮足机器人运动控制[J]. 兵工学报, 2026,47(1):250666. DOI： 10.12382/bgxb.2025.0666.

YANG Lihui, GUAN Haijie, HAN Fenkai, et al. Motion Control of Wheeled Bipedal Robot Based on Double-layer MPC[J]. Acta Armamentarii, 2026, 47(1): 250666. DOI： 10.12382/bgxb.2025.0666.

摘要

为实现双轮足机器人运动灵活的特性，将双轮足机器人运动控制问题解耦为路径跟踪和姿态跟踪两部分，并针对性地提出一种双层模型预测控制（Model Predictive Control

MPC）算法。在世界坐标系下，基于差速转向模型设计路径跟踪控制器，并结合比例控制器生成轮毂电机扭矩指令。在机器人本体坐标系下，基于单刚体动力学模型构建姿态跟踪控制器，并借助虚功原理计算生成关节电机扭矩指令。研究结果表明，所提算法采用双层MPC的框架，在不损失模型精度的情况下，降低了模型维度和计算复杂度。通过数值仿真、Gazebo仿真实验以及实物实验验证了新算法的可行性和有效性，相较于对比算法，新算法减少了66. 14%的算法复杂度，在高度跟踪、侧倾角跟踪和俯仰角跟踪方面误差分别减小了53. 85%、62. 08%和14. 92%，新算法在路径与姿态跟踪方面均具有更优的性能。

Abstract

To achieve the flexible motion characteristics of wheeled bipedal robots

this paper decouples the motion control of such robots into path tracking and attitude tracking

and proposes a double-layer model predictive control (MPC) algorithm to address the issues above. In the world coordinate system

a path tracking controller is designed based on the differential steering model

and the proportional controllers are integrated to the torque commands for the hub motors. In the robot's body coordinate system

a attitude tracking controller is constructed using the single-rigid-body dynamics model

and the virtual work principle is employed to compute the torque commands for the joint motors. The proposed algorithm adopts a double-layer MPC framework

which reduces the model dimensionality and computational complexity without sacrificing model accuracy. The feasibility and effectiveness of the proposed algorithm are verified through numerical simulation

Gazebo simulation experiment

and physical experiment. Compared with comparative algorithms

the proposed algorithm reduces the algorithmic complexity by 66. 14% . In terms of altitude tracking

roll angle tracking

and pitch angle tracking

the errors are reduced by 53. 85%

62. 08%

and 14. 92%

respectively. The proposed algorithm exhibits superior performance in both path tracking and attitude tracking.

关键词

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references

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