This article seeks to develop the dynamic model of a mobile robot for controlling purposes while the effects of uncertainties and longitudinal and lateral slip are assumed. The rise in the number of state variables and considering the effects of nonlinear parameters due to slip modeling can complicate the control procedure of wheeled mobile manipulators. In addition, the existence of uncertainties as well as holonomic and nonholonomic constraints would increase this complexity even more. On the one side, as wheels are considered to slip, unwanted movements due to slippage affect the movement of the manipulator and the manipulator may not be able to track the desired path. On the other side, the movement of weighted links of the manipulator constantly changes the normal forces of the wheels. As traction forces are dependent on these normal forces, the path tracked by the platform would be affected. Given these conditions, employing a robust control methodology and developing an optimal algorithm to reduce the effects of uncertainties and wheels slip seems mandatory. To this aim, a sliding mode control (SMC) strategy is formulated in this study. Furthermore, the suggested algorithm is optimized using a state-dependent Riccati equation to reduce the consumed torque and increase the accuracy of the system. Simulations are conducted, and the presented algorithm is also checked with the experimental setup of a Scout robot. Simulation results show that the optimal sliding mode control (OSMC) successfully decreases sudden jumps due to slippage in the system. In addition, the consumed power of wheels and arm for SMC decreases from 9.15 and 1.02 N·m to, respectively, 1.46 and 0.54 N·m for OSMC.

中文翻译：

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考虑不确定性和车轮打滑影响的移动机械手优化控制策略设计及其应用

本文旨在开发用于控制目的的移动机器人的动态模型，同时假设不确定性以及纵向和横向滑动的影响。状态变量数量的增加和考虑到由于滑移建模引起的非线性参数的影响，会使​​轮式移动机械手的控制过程复杂化。此外，不确定性以及完整和非完整约束的存在将进一步增加这种复杂性。一方面，由于车轮被认为是打滑，由于打滑引起的不必要的运动会影响机械手的运动，并且机械手可能无法跟踪所需的路径。另一方面，机械手的配重连杆的运动不断改变车轮的法向力。由于牵引力取决于这些法向力，平台跟踪的路径将受到影响。鉴于这些条件，采用稳健的控制方法并开发最佳算法来减少不确定性和车轮打滑的影响似乎是强制性的。为此，本研究制定了一种滑模控制 (SMC) 策略。此外，建议的算法使用状态相关的 Riccati 方程进行优化，以减少消耗的扭矩并提高系统的精度。进行了模拟，并且还使用 Scout 机器人的实验装置检查了所提出的算法。仿真结果表明，最优滑模控制 (OSMC) 成功地减少了由于系统滑移引起的突然跳跃。此外，SMC 的车轮和臂的消耗功率分别从 9.15 和 1.02 N·m 降低到 OSMC 的 1.46 和 0.54 N·m。