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Position and Tilt Control of Two-Wheeled Robot (TWR): A Neuro-Fuzzy Approach

机译:两轮机器人的位置和倾斜控制(TWR):一种神经模糊的方法

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摘要

This paper presents a fuzzy based adaptive control approach for stabilization of Two wheeled robot (TWR) system. The TWR consists of a robot chassis mounted on two movable wheels. The objective is to stabilize the proposed system within desired time, minimum overshoot and at desired location. The data samples collected from simulation results of fuzzy controllers were used for training, tuning and optimisation of an adaptive neuro fuzzy inference system (ANFIS) controller. A Matlab Simulink model of the system has been built using Newton's second law of motion. The effect of shape and number of membership functions on training error of ANFIS has also been analysed. The designing of fuzzy rules for both fuzzy and ANFIS controller were carried out using gbell shape memberships. Simulations were performed which compared and validated the performance of both the controllers.
机译:本文介绍了一种基于模糊的自适应控制方法,可稳定两个轮式机器人(TWR)系统。 TWR由安装在两个可移动轮上的机器人底盘组成。 目的是在所需时间内稳定所提出的系统,最低过冲和所需位置。 从模糊控制器的仿真结果收集的数据样本用于自适应神经模糊推理系统(ANFIS)控制器的训练,调整和优化。 系统的Matlab Simulink模型已经使用牛顿的第二次运动法建立。 还分析了隶属函数的形状和数量对ANFI训练误差的影响。 使用GBELL形状成员资格进行模糊和ANFIS控制器的模糊规则。 进行模拟,其比较和验证了控制器的性能。

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