基于前馈补偿的轮腿式机动平台姿态自适应控制

doi:10.12382/bgxb.2022.1103

摘要/Abstract

摘要：

在通过复杂路面障碍时,轮腿式机动平台的轮端负载较大,且地面对轮胎的外力会突然变化,会显著降低机身姿态的控制精度,并容易导致轮胎脱离地面失稳等问题。为提高平台的地形适应能力和稳定性,提出一种基于前馈补偿的平台姿态自适应控制策略。构建平台的逆运动学模型和动力学模型,考虑轮-地接触点垂向支撑力和纵向驱动力实现轮-地接触状态的实时估计,结合腿部高度观测器和轮-地接触状态估计器获得腿部垂向补偿高度,兼顾平台车轮运动稳定性和姿态自适应控制精度。考虑平台机身动量和角动量,利用二次规划算法优化的轮端虚拟驱动力求解前馈补偿力矩,以实现平台的运动精确控制。仿真结果表明,该方法可以有效提高轮腿式机动平台在崎岖路面环境下的姿态自适应控制精度和轮胎驱动稳定性,为在复杂工况下轮腿式机动平台执行侦察等任务奠定基础。

关键词: 轮腿式机动平台, 前馈补偿, 轮-地接触, 实时估计, 姿态控制

Abstract:

When passing through complex obstacles, a wheel-legged mobile platform bears a relatively large load on the wheel end, and the external force acting on the tire from the ground undergoes sudden changes. This significantly reduces the precision of the platform's attitude control and can lead to tire instability and loss of contact with the ground. To improve the terrain adaptation and stability, an adaptive attitude control strategy for the platform based on feedforward compensation is proposed. Considering the vertical support force and longitudinal driving force at the wheel-ground contact point, the inverse kinematic model and dynamic model of the platform are constructed. And the real-time estimation of the wheel-ground contact state is achieved, and the leg height observer and wheel-ground contact state are combined to perform feedforward compensation to adjust the leg's vertical height, balancing the platform's wheel motion stability and adaptive attitude control accuracy. Furthermore, considering the momentum and angular momentum of the platform, the virtual driving force at the wheel end is optimized by the quadratic programming algorithm to solve the feedforward compensation torque and thus enable the precise control of platform motion. The simulation results show that the proposed method can improve the adaptive attitude control accuracy and tire driving stability of the wheeled-legged mobile platform, laying the foundation for its performing reconnaissance and other tasks in complex working conditions.

Key words: wheel-legged mobile platform, feedforward compensation, wheel-ground contact, real-time estimation, attitude control

中图分类号:

TJ301

刘辉, 刘宝帅, 廖登廷, 韩立金, 崔山. 基于前馈补偿的轮腿式机动平台姿态自适应控制[J]. 兵工学报, 2023, 44(9): 2756-2767.

LIU Hui, LIU Baoshuai, LIAO Dengting, HAN Lijin, CUI Shan. Adaptive Attitude Control of Wheel-legged Mobile Platform Based on Feedforward Compensation[J]. Acta Armamentarii, 2023, 44(9): 2756-2767.

图/表 17

图1 轮腿式机动平台整体构型

Fig.1 Overall architecture of wheel-legged mobile platform

表1 轮腿式机动平台关键参数

Table 1 Key parameters of wheel-legged mobile platform

类别	参数	数值
	平台质量m/kg	50
	负载质量m_l/kg	10
	自由度n	18
结构参数	外廓长L_b/mm	850
	外廓宽L_w/mm	350
	大腿长度L₁/mm	300
	小腿长度L₂/mm	290
	轮胎半径R_w/mm
关节电机	额定扭矩τ_jm,rate/(N·m)	48
	峰值扭矩τ_jm,max/(N·m)	144
轮边电机	额定扭矩τ_wm,rate/(N·m)	8.3
	峰值扭矩τ_wm,max/(N·m)	24.8

图2 轮腿式机动平台坐标系和运动空间定义

Fig.2 Definitions of the coordinates and motion space of wheel-legged mobile platform

图3 基于前馈补偿的姿态自适应控制策略

Fig.3 Adaptive attitude control strategy based on feedforward compensation

图4 左前腿坐标系定义

Fig.4 Definition of the front-left leg coordinates

图5 车身姿态实时补偿算法

Fig.5 Real-time compensation algorithm for vehicle attitude

图6 轮腿式机动平台整体质心虚拟模型

Fig.6 Virtual model of the center of mass of wheel-legged mobile platform

图7 轮腿式机动平台运行及工况示意图

Fig.7 Schematic diagram of the operation and working conditions of wheel-legged mobile platform

图8 轮腿式机动平台仿真运动过程

Fig.8 Wheel-legged mobile platform in motion

图9 车身质心姿态角度结果

Fig.9 Simulation results of attitude angle of the platform CoM

图10 平台质心纵向速度与位置仿真结果

Fig.10 Simulation results of longitudinal velocity and position of the platform CoM

图11 平台质心垂向速度与位置仿真结果

Fig.11 Simulation results of vertical velocity and position of the platform CoM

图12 轮腿式机动平台左/右前腿关节运动角度与力矩结果

Fig.12 Joint angles and torques of the front-left and front-right legs of the wheel-legged mobile platform

图13 轮腿作动机构的轮-地接触指令结果对比

Fig.13 Comparison of wheel-ground contact command results of different legs

图14 轮腿式机动平台轮-地接触力仿真实验结果

Fig.14 The simulation results of the wheel-ground contact force of wheel-legged mobile platform

表2 仿真结果对比

Table 2 Comparison of simulation results

姿态角	误差	带前馈补偿策略	无前馈补偿策略
俯仰角	最大误差	-0.862°	-0.954°
	平均误差	-0.276°	-0.316°
侧倾角	最大误差	0.369°	0.369°
	平均误差	0.102°	0.102°

图15 二次规划算法求解时间

Fig.15 Computing time with QP algorithm

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