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Adaptive Neuro-Fuzzy Control for trajectory tracking of a wheeled Mobile Robot

机译:适应性神经模糊控制轮式移动机器人的轨迹跟踪

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This paper presents a technique for autonomous mobile robot control. In recent day, computational intelligent techniques, such as artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro-fuzzy inference system (ANFIS), are mainly considered as applicable techniques from modeling point of view. ANFIS has taken the integrate performance of neural network and fuzzy inference system. In this architecture different error coordinates x_e, y_e, θ_e, are given as input to the adaptive fuzzy controller and output from the controller is steering angle and linear velocity for the mobile robot. Simulation experiments using MATLAB and labview demonstrate that the proposed ANFIS controller can be effectively applied to control the mobile robot safely and reach to target objects.
机译:本文提出了一种自主移动机器人控制的技术。近期,计算智能技术,如人工神经网络(ANN),模糊推理系统(FIS)和自适应神经模糊推理系统(ANFIS)主要被认为是从建模的角度来看的应用技术。 ANFIS已采用神经网络和模糊推理系统的性能。在该体系结构中,不同误差坐标X_E,Y_E,θ_e被给出作为自适应模糊控制器的输入,并且从控制器输出是移动机器人的转向角和线性速度。使用MATLAB和LabVIEW的仿真实验表明,所提出的ANFIS控制器可以有效地应用于安全地控制移动机器人并达到目标物体。

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