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Adaptive fuzzy balance controller for two-wheeled robot

机译:两轮机器人的自适应模糊平衡控制器

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摘要

An adaptive fuzzy sliding-mode balance controller (AFSMBC) for a two-wheeled robot is developed in this study. In the proposed balance controller, a novel sliding surface is adopted as the input variable of fuzzy system to outstanding its merit of insensitivity to uncertainties. In the fuzzy membership function, the translation width is utilized to reduce the chattering phenomena. Moreover, consider the parametric variation, external disturbance and nonlinear friction for the practical wheeled robot motions, the transient and unmodelled uncertainty will be occurred. An adaptive tuner, which is derived in the sense of Lyapunov stability theorem, is added into the fuzzy controller to reduce the accumulated error and to ascend the stability. The hardware of whole control system includes a microcontroller, gyroscope, accelerometer, and two autonomous motors. The effectiveness is verified by simulated and experimental results, and the performance is compared with conventional PD control scheme for the same wheeled robot.
机译:本研究开发了一种适用于两轮机器人的自适应模糊滑模平衡控制器(AFSMBC)。在提出的平衡控制器中,采用新颖的滑动面作为模糊系统的输入变量,以突出其对不确定性不敏感的优点。在模糊隶属函数中,利用平移宽度来减少颤动现象。此外,考虑到轮式机器人实际运动的参数变化,外部干扰和非线性摩擦,将出现瞬态和未建模的不确定性。在Lyapunov稳定性定理的意义上得出的自适应调谐器被添加到模糊控制器中,以减少累积误差并提高稳定性。整个控制系统的硬件包括一个微控制器,陀螺仪,加速度计和两个自动电动机。仿真和实验结果验证了其有效性,并将其性能与相同轮式机器人的常规PD控制方案进行了比较。

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