In this study, a novel control strategy that combines a fuzzy system and the sliding mode controller is proposed for improving stability and achieving high-accuracy control in service robots. Based on the kinematic and dynamic models of a 4-degrees of freedom manipulator, and the observed tracking error using a low-cost inertial sensor, the proposed fuzzy sliding mode controller (FSMC(IMU)) is designed to generate appropriate torques at robot joints. The FSMC(IMU) controller parameters are adjusted through a fuzzy rule that determines the state of the system. The error in trajectory tracking is reduced through this. The gain value K can be finely adjusted by fuzzy control by observing the degree of vibration after entering the sliding mode surface. The larger the observed vibration value, the faster the fuzzy controller follows the given input trajectory by selecting a smaller gain value K and reducing jitter due to the sliding mode control’s discontinuous switch characteristics. When the degree of error is small, it achieves faster and more accurate control performance than when the observer is not used. The stability of the FSMC(IMU) system is verified via disturbance experiments. The experimental data are compared with the conventional sliding mode controller and proportional-derivative control. The experimental results demonstrate that the proposed FSMC(IMU) controller is stable, fast, and highly accurate in controlling service robots.

在这项研究中，提出了一种结合模糊系统和滑模控制器的新型控制策略，以提高服务机器人的稳定性并实现高精度控制。基于 4 自由度机械手的运动学和动力学模型，以及使用低成本惯性传感器观察到的跟踪误差，设计了模糊滑模控制器 (FSMC(IMU)) 以在机器人关节处产生适当的扭矩. FSMC(IMU) 控制器参数通过确定系统状态的模糊规则进行调整。由此减少了轨迹跟踪的误差。通过观察进入滑模面后的振动程度，可以通过模糊控制对增益值K进行微调。观测到的振动值越大，由于滑模控制的不连续开关特性，模糊控制器通过选择较小的增益值 K 并减少抖动，从而更快地遵循给定的输入轨迹。当误差程度较小时，它比不使用观测器时获得更快、更准确的控制性能。FSMC(IMU)系统的稳定性通过扰动实验得到验证。将实验数据与传统的滑模控制器和比例微分控制进行了比较。实验结果表明，所提出的 FSMC(IMU) 控制器在控制服务机器人方面稳定、快速且准确。与不使用观测器时相比，它实现了更快、更准确的控制性能。FSMC(IMU)系统的稳定性通过扰动实验得到验证。将实验数据与传统的滑模控制器和比例微分控制进行了比较。实验结果表明，所提出的 FSMC(IMU) 控制器在控制服务机器人方面稳定、快速且准确。与不使用观测器时相比，它实现了更快、更准确的控制性能。FSMC(IMU)系统的稳定性通过扰动实验得到验证。将实验数据与传统的滑模控制器和比例微分控制进行了比较。实验结果表明，所提出的 FSMC(IMU) 控制器在控制服务机器人方面稳定、快速且准确。