Chattering reduction in sliding mode control of quadcopters using neural networks

被引：11

作者：

Cibiraj, N. ^{[1
]}

Varatharajan, M. ^{[1
]}

机构：

[1] Thiagarajar Coll Engn, Dept Elect & Elect Engn, Madurai 625015, Tamil Nadu, India

来源：

FIRST INTERNATIONAL CONFERENCE ON POWER ENGINEERING COMPUTING AND CONTROL (PECCON-2017 ) | 2017年 / 117卷

关键词：

Quadcopters; Sliding mode control; Chattering; Gain Scheduling; Fuzzy Logic; Neural Networks;

D O I：

10.1016/j.egypro.2017.05.207

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is based on the attitude control of a quadcopter with external disturbances. Sliding mode control (SMC) is a robust control method suitable for control of quadcopter. But its robustness comes at the cost of high frequency switching called chattering. An Adaptive Neural Gain Scheduling Sliding Mode Control (ANGS-SMC) technique is proposed to solve the chattering problem. Control gain of SMC is adapted using feed forward neural network. Performance of the designed controller is compared by simulation in MATLAB. (C) 2017 The Authors. Published by Elsevier Ltd.

引用

页码：885 / 892

页数：8

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