Parameters Tuning Approach for Proportion Integration Differentiation Controller of Magnetorheological Fluids Brake Based on Improved Fruit Fly Optimization Algorithm

Xinhua Liu,Yao Shi,Jing Xu

doi:10.3390/sym9070109

Abstract

In order to improve the response performance of a proportion integration differentiation (PID) controller for magnetorheological fluids (MRF) brake and to reduce the braking fluctuation rate, an improved fruit fly optimization algorithm for PID controller parameters tuning of MRF brake is proposed. A data acquisition system for MRF brake is designed and the transfer function of MRF brake is identified. Moreover, an improved fruit fly optimization algorithm (IFOA) through integration of PID control strategy and cloud model algorithm is proposed to design a PID controller for MRF brake. Finally, the simulation and experiment are carried out. The results show that IFOA, with a faster response output and no overshoot, is superior to the conventional PID and fruit fly optimization algorithm (FOA) PID controller.

Highlights

As a new type of intelligent brake, magnetorheological fluids (MRF) brake uses MRF as a working medium, and its brake torque can be controlled by an external magnetic field [1,2,3]
Genetic algorithms and neural networks were used to tune the proportion integration differentiation (PID) parameters, and the results showed that the controller with a combination of these algorithms was better than the conventional controllers [16,17,18]
The improved fruit fly optimization algorithm (IFOA) and the fly optimization algorithm (FOA) have the same parameters setting: the object to carry out simulation analysis

Summary

Introduction

As a new type of intelligent brake, magnetorheological fluids (MRF) brake uses MRF as a working medium, and its brake torque can be controlled by an external magnetic field [1,2,3]. Due to the well rheological properties of MRF, the control system of MRF brake is characterized by a simple structure, low power and fast response. With the passage of working time, the performance of MRF is changing [4]; it may result in worse control effects and lower level stabilization. The control technology with high accuracy, good stability and fast response for MRF brake has been an active area of research recently. There are many factors that influence the effect of PID control, among which selection of the three parameters P, I and D is one of the most important factors [6,7]. Parameter selection is a combinatorial optimization problem, and the result directly determines the effect of PID control; parameters tuning would play an important role in evaluating the performance of a PID controller

Results

Discussion

Conclusion