Fuzzy logic control of a mobile robot

Kim Received May 27; Accepted Aug 2. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles.

Fuzzy logic control of a mobile robot

Byung-Jae Choi bjchoi daegu. Abstract Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system.

Fuzzy logic control of a mobile robot

In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system.

In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity.

This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system. Introduction Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a good model to verify the performance of a proposed controller for such a system, which is inherently a nonlinear.

An inverted pendulum type mobile robot system adds mobility to the utilization of a mechanical function that balances the inverted pendulum system[ 1 ]. Furthermore, it is similar to the control scheme of a biped robot which is modelled after the human form and is supported by two feet. Segway type mobile robots operate based on the dynamics of the inverted pendulum system.

They are capable of forward, backward, and turning motions, and these are the only possible movements of the body. Unlike scooters whose two interdependent wheels are in series, Segway mobile robots have two wheels connected in a parallel configuration.

Introduction

Thus, Segway mobile robots allow the construction of a mobile platform that can travel smoothly to a small area by reducing the migration area. However, a mobile robot employing an inverted pendulum mechanism as its mobile platform requires an additional controller design to maintain the balance of the body, as its balancing ability is generally not good under excessive disturbances.

In this paper, we propose the design of a fuzzy logic control system for the position and balance control of an inverted pendulum type Segway mobile robot.

We first introduce a dynamic model of the Segway mobile robot and analyze it. We then design two fuzzy logic control systems based on our analysis. Their usefulness is verified by simulation examples.

Based on the skew symmetry property of the rule table for the fuzzy logic control system, we also present a possibility for a reduction in the computational complexity and the simplification of the design of the fuzzy logic control system.

[BINGSNIPMIX-3

The remainder of the paper is organized as follows. In Section 2, we describe the introduction of the dynamic model of the Segway mobile robot. The design of two fuzzy logic control systems for the Segway mobile robot is presented in Section 3.

In Section 4, we present the results of simulation examples and explain their relevance. Concluding remarks are given in Section 5. Dynamics of Segway Mobile Robot Segway type mobile robots are composed of two wheels and a pole between them. The angle of the pole is measured by a gyro, tilt or acceleration sensor, and is maintained at zero degrees.

In this section, we introduce the dynamics of the Segway type mobile robot which is an inverted pendulum type mobile robot. Schematics of this robot are shown in Figure 1.

The main parameters used in Figure 1 are presented in Table 1.

As shown in Figure 1the mobile robot can be divided into two parts. The wheel part and the pole part, which consists of a pole and a driving motor to support the body over the wheel and maintain the balance of the robot.

We first introduce equations associated with the wheel part of the robot, which is shown in Figure 1 b. The following equations of motion are derived from the moment of inertia of the wheel of the driving shaft and the reaction forces of the horizontal and vertical axes of the pole:In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system.

We first introduce a dynamic model of the Segway mobile robot and then analyze the system. Boards and CEOs are more tech-savvy than they once were, but they still don't always know the best questions to ask CIOs.

With the push for digital transformation they need to be armed with the right questions at the right time. Welcome to Addicting Games, the largest source of the best free online games including funny games, flash games, arcade games, dress-up games, internet .

거친 노면에서 움직이는 이동로봇을 제어하는 퍼지논리 시스템을 설계하라 [해답] 로봇의 입력으로는 노면의 경사와 지형으로 하고 출력으로는 로봇의 속도로 가정할 것이다. Adaptive fuzzy logic-based sliding mode control for a nonholonomic mobile robot in the presence of dynamic uncertainties Ming Yue, Shuang Wang, and Yongshun Zhang Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

The overall objective of this course is to add value to your first degree and previous relevant experience by developing a focused, integrated and critically aware understanding of underlying theory and current policy and practice in the field of control.

Fuzzy control system - Wikipedia