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Intelligent controllers for velocity tracking of two wheeled inverted pendulum mobile robot

机译:用于两轮倒立摆式移动机器人速度跟踪的智能控制器

摘要

Velocity tracking is one of the important objectives of vehicle, machines and mobile robots. A two wheeled inverted pendulum (TWIP) is a class of mobile robot that is open loop unstable with high nonlinearities which makes it difficult to control its velocity because of its nature of pitch falling if left unattended. In this work, three soft computing techniques were proposed to track a desired velocity of the TWIP. Fuzzy Logic Control (FLC), Neural Network Inverse Model control (NN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) were designed and simulated on the TWIP model. All the three controllers have shown practically good performance in tracking the desired speed and keeping the robot in upright position and ANFIS has shown slightly better performance than FLC, while NN consumes more energy.
机译:速度跟踪是车辆,机器和移动机器人的重要目标之一。两轮倒立摆锤(TWIP)是一类具有高非线性度的开环不稳定的移动机器人,由于无人看管时俯仰下降的特性,因此很难控制其速度。在这项工作中,提出了三种软计算技术来跟踪TWIP的所需速度。在TWIP模型上设计并仿真了模糊逻辑控制(FLC),神经网络逆模型控制(NN)和自适应神经模糊推理系统(ANFIS)。这三个控制器在跟踪所需速度并将机器人保持直立位置方面均表现出了良好的性能,而ANFIS的性能优于FLC,而NN消耗的能量更多。

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