JOURNAL ARTICLE

Command filter-based fuzzy adaptive nonlinear sensor-fault tolerant control for a quadrotor unmanned aerial vehicle

Chaofang HuZelong ZhangXianpeng ZhouNa Wang

Year: 2019 Journal:   Transactions of the Institute of Measurement and Control Vol: 42 (2)Pages: 198-213   Publisher: SAGE Publishing

Abstract

In this paper, a novel asymptotic fuzzy adaptive nonlinear fault tolerant control (FTC) scheme is presented for the under-actuated dynamics of a quadrotor unmanned aerial vehicle (UAV) subject to diverse sensor faults. The proposed FTC approach can deal with both additive sensor faults (bias, drift, loss of accuracy) and multiplicative sensor fault (loss of effectiveness). The overall dynamics is separated into position loop and attitude loop for FTC controllers design. Combining uncertain parameters and external disturbances, the four types of faults occurring in velocity sensors and Euler angle rate sensors are transformed equivalently into the unknown nonlinear function vectors and uncertain control gains. Fuzzy logic systems are used to approximate the lumped nonlinear functions, and adaptive parameters are estimated online. Nussbaum technique is introduced to deal with the unknown control gains. For both control loops, FTC controllers are designed via command filter-based backstepping approach, in which sliding mode control is introduced to establish asymptotic stability. All tracking error signals of the closed-loop control system are proved to converge to zero asymptotically. Finally, simulation comparisons with other methods demonstrate the effectiveness of the proposed FTC approach for quadrotor UAV with sensor faults.

Keywords:
Control theory (sociology) Backstepping Fuzzy logic Nonlinear system Filter (signal processing) Controller (irrigation) Fault tolerance Computer science Fault (geology) Control engineering Engineering Adaptive control Control (management) Artificial intelligence

Metrics

17
Cited By
1.16
FWCI (Field Weighted Citation Impact)
41
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Control Systems Design
Physical Sciences →  Engineering →  Control and Systems Engineering

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