Mechatronics And Automation Engineering - Proceedings Of The 2016 International Conference (Icmae2016)

Proceedings of the International Conference on Mechatronics and Automation Engineering (ICMAE2016)

Jianhua Zhang

• Publisher: WSPC
• Year: 2017
• eBook ISBN: 9789813208544
• Topic: Technology & Engineering
• Subtopic: Automation in Engineering
• Index: Technology & Engineering

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The 2016 International Conference on Mechatronics and Automation Engineering (ICMAE2016) have been successfully held in Xiamen, China, on April 22nd – 24th.

The conference received well over more than 200 submissions, however, only 64 articles were selected and recommended to be included in this proceedings, which organized into 4 main areas, namely, Industrial Automation and Control System, Intelligent Mechatronics and Robotics, Mechanical Engineering and Electrical Engineering and Computer Science.

The conference provides the opportunity to showcase state of art research and development in Mechatronics and Automation Engineering from researchers and developers from around the world under one roof to compare notes and establish collaborative relationships.

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Contents: Industrial Automation and Control System;Intelligent Mechatronics and Robotics;Mechanical Engineering;Electrical Engineering and Computer Science; -->
--> Readership: Researchers, academics, professionals and graduate students in social science. -->
Industrial Automation, Control System, Mechanical Engineering, Intelligent Mechatronics and Robotics, Electrical Engineering and Computer Science

• This proceedings collected together R&D funded and undertaken by Chinese researcher in industrial automation and control system, intelligent
• Printed version of about 30 copies will be POD to meet the order from conference participants and authors alike
• Additional copies will be printed for marketing to include in their library package

Chapter 1

Industrial Automation
and Control System

Position Control of Switched Reluctance Planar Motor Based on Fuzzy Control

Hua-Cai Lu^*, Guang-Zheng Ruan and Teng-Fei Dou

College of Electrical Engineering, Anhui Polytechnic University,
Wuhu, 241000, China

*E-mail: [email protected]

The switched reluctance planar motor (SRPM) has numerous advantages such as having a simple structure, reliable operation, easy controls and having a wide range of applications. However, the nonlinear characteristics of the motor results in electromagnetic thrust ripple and non-linear distortion are serious problems which result in difficult motor position control. This paper suppresses the electromagnetic thrust ripple by force distribution function and uses the fuzzy PID method to control motor position. The results demonstrate that the fuzzy PID control strategy has a faster dynamic response, smaller overshoot and improved dynamic performance as compared to the classical PID control strategy, thus the results provide a foundation for further studies on SRPM.

Keywords: Plane Motors; Switched Reluctance; Fuzzy Pid; Position Control.

1. Introduction

Switched Reluctance Planar Motor (SRPM) is a new type of motor, which has been developed and has been widely used in social production and life for the past few years [1]. Large thrust fluctuation of the motor itself and serious current issues such as nonlinear distortion, have brought difficulties to motor tracking control. Some scholars suggested that auto-disturbance rejection control to solve problems in the motor position control [2, 3], but the parameters not easily adjust of the method brings difficult to control strategy. PID controller is the most widely used method technique in industrial applications, but its not easy setting of parameters is its weakness [4, 5]. This article attempts the fuzzy PID controller. It suppresses the electromagnetism thrust force undulation through the force distribution function, and use the fuzzy PID controller carries on the position control to the electrical machinery. The research results are as the basis for further study of SRPM.

2. Establish the Mathematical Model

As the X and Y directions of the switched reluctance motor are the same, the electromagnetic properties of the X axis are analyzed in here. Eq. (1) describes the X-axis three phase rotor voltage:

(1)

where U_s is the voltage applied to the phase s of SRPM, i_s is the current applied to the phase s of the stator, L_s is the inductor applied to the phase s of the motor. L_s is described as Eq. (2):

(2)

where N is the number of windings, p is the polar distance, q is the groove width, z is the air gap. In Eq. (2), k is 0 when s describes a-phase, k is 2; when s describes b-phase, k is 4 when s describes c-phase.

Due to SRPM is a nonlinear model, the model is described by

(3)

where f_e is the electromechanical force, M is the mass, B is the friction, f_l is external load force. Ignoring leakage inductance, the electromagnetic force can be expressed as

(4)

where L_Δ is (L_max – L_min)/2, and L_max is Maximum inductance, L_min is minimum inductance.

3. Controller Design

3.1. PID control system

Eq. (5) shows that the SRPM of X, Y axis motion is a second-order system. Controller for second order systems can be designed according to the conventional PID controller design steps. Ignoring the friction force of the rail, the motor open-loop transfer function is

(5)

where K is 1000. In order to increasing the fast response of the system and reducing the system error, the system uses double closed loop design. The inner loop adopts proportional negative feedback, and the outer loop takes fuzzy PID controller. The concrete structure is shown in Figure 1. Assuming that the H (f^*, x) is used for the distribution of the multi phase excitation, the open-loop transfer function of the motor can be further expressed as

(6)

and system closed loop transfer function is

(7)

where K_p, K_i, K_d are respectively the proportional, integral, differential parameters of the PID controller. K₁ is the forward channel coefficient, K₂ is negative feedback coefficient. Eq. (7) shows that the system is a typical two order system. By adjusting the PID parameters, the system can be stable.

Fig. 1 The X axis position control block diagram

3.2. Fuzzy PID control system

Fuzzy PID control system is to have the system error E and the System Error change E_c the input of the fuzzy controller, and the PID controller coefficient K_i, K_d and K_p as the output of the fuzzy controller. After setting up fuzzy control rule library, the output of fuzzy controller is adjusted ...

Table of contents

• Cover
• Halftitle
• Title Page
• Copyright
• Contents
• Preface
• Committees
• Chapter 1 Industrial Automation and Control System
• Chapter 2 Intelligent Mechatronics and Robotics
• Chapter 3 Mechanical Engineering
• Chapter 4 Electrical Engineering and Computer Science
• Author Index