Active versus passive fault-tolerant control of a redundant multirotor UAV

Saied, Majd; Lussier, Benjamin; Fantoni, Isabelle; Shraim, Hassan; Francis, Clovis

doi:10.1017/aer.2019.149

Cited by 32 publications

(10 citation statements)

References 23 publications

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“…Many of these works have been just theoretical or limited to safe simulations. There are linear time-invariant models, parameter-varying models [6], and even non-linear models to this approach. Even in the past few years, Kalman Filter [1], adaptive control [7], sliding mode control [6,8], and PMI filter-based solutions [9] are being studied with little to no implementation on real flights.…”

Section: A Simulations and Real-flight Tests For Fdimentioning

confidence: 99%

Multivariate Data Analysis for Motor Failure Detection and Isolation in A Multicopter UAV Using Real-Flight Attitude Signals

Ashe¹,

Goli²,

Kandath³

et al. 2023

Preprint

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<p>Reconfigurable aerial platforms such as multicopter unmanned aerial vehicles (UAVs) allow the design of fail-safe systems because of inherent redundancy in actuators and sensors to maintain stability with a reduction in flight performance. The methods based on univariate and multivariate time series analysis of just the attitude signals can pave the way for model-free systems that can be generalized across a class of UAVs like multicopters. In this paper, we present a critical analysis of real-flight attitude time-series signals and investigate them for data-driven motor fault and failure detection and isolation (FDI), specifically for multicopters configurations like quadcopters and hexacopters. We analyze flight data for different scenarios of outdoor flights, healthy and faulty, hovering and cruising, loss of efficiency, and single-rotor failure of every motor. We tested it for small to medium-sized multicopters. The failure detection and classification are performed without relying on analytical system modeling or the knowledge of the controller.</p> <p>Thus, we perform three major assessments: vector auto-regression (VAR) using residual variance, time-frequency analysis, and dimensionality analysis of the recorded variables to support the classification framework. To the author's best knowledge, this is the first attempt at providing an algorithmic foundation that works on existing hardware and flight controllers using streaming flight attitude data rather than simulations. This allows us to implement these online methods in real-time on multicopters, which drastically increases levels of safety and scalability of unmanned flights in drone applications.</p>

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Section: A Simulations and Real-flight Tests For Fdimentioning

confidence: 99%

Multivariate Data Analysis for Motor Failure Detection and Isolation in A Multicopter UAV Using Real-Flight Attitude Signals

Ashe¹,

Goli²,

Kandath³

et al. 2023

Preprint

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“…A sliding mode control (SMC), developed in the work of Adir et al, 42 has been chosen to stabilize the system for its characteristics of robustness to disturbances and uncertainty. In addition, according to the works of Li et al, 43 Wang et al, 44 and Saied et al 45 the SMC can be used as a passive fault-tolerant control since it can maintain the stability of the system under certain faults. It is important to note that the proposed work is not dedicated to analyzing the controller, but the FD method.…”

Section: Fd Of An Octorotor Uavmentioning

confidence: 99%

“…The dynamics of the octorotor UAV can be separated into two subsystems: the translational part and the rotational part, as it can be seen in ( 44) and (45). It is well known that the attitude dynamics is much faster than the translational one.…”

Section: Lpv Model Of the Octorotormentioning

confidence: 99%

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Gómez-Peñate

López‐Estrada

Valencia‐Palomo

et al. 2020

Intl J Robust & Nonlinear

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This article proposes an approach for the estimation of states, actuator, and sensor faults in nonlinear systems represented by a polytopic linear parameter varying (LPV) system with inexact scheduling parameters. In the traditional LPV approaches, the scheduling variables are considered to be perfectly known.However, in practical applications, their measurement may contain precision and calibration errors or noise that can affect the performance of the diagnostic systems. Therefore, this work proposes the design of a proportional multiple-integral sliding mode observer for fault diagnosis (FD) that copes with LPV systems with inexact scheduling parameters. Due to the introduction of some nonlinear functions, the proposed observer is a nonlinear parameter varying system for which stability and robustness performance are formulated using the Lyapunov technique and a H ∞ performance criterion. It is shown that the design conditions boil down to a set of linear matrix inequalities whose solution allows computing the observer gain matrix along with the tunable parameters of the nonlinear functions. Results obtained using the simulator of an octocopter-type unmanned aerial vehicle are used to demonstrate the applicability and performance of the proposed FD scheme. K E Y W O R D Sfault diagnosis, linear matrix inequalities, nonlinear parameter varying systems, proportional multiple-integral sliding mode observer INTRODUCTIONModern control systems are prone to faults, which can damage the systems themselves or the environments in which they operate. For this reason, fault diagnosis (FD) algorithms become essential, since they enable fault-tolerant actions that minimize the effect of faults and improve the overall system's reliability and safety. An FD algorithm can be seen as a two-step process in which at first the fault is detected, that is, a Boolean logic value about the presence of a fault is provided, 8420

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“…In recent decades, with the challenge of increasing demand for reliability and safety of various industrial control processes, Fault Diagnosis (FD) and Fault Tolerant Control (FTC) has attracted more and more attention. More precisely, the FTC system is a control system that can accommodate system component faults and is able to maintain system stability and performance despite the presence of faults [1]- [4]. Indeed, real-world physical systems are generally nonlinear in nature.…”

Section: Introductionmentioning

confidence: 99%

Adaptive PID Fault-Tolerant Tracking Controller for Takagi-Sugeno Fuzzy Systems with Actuator Faults: Application to Single-Link Flexible Joint Robot

Elouni

Hamdi

Rabaoui

et al. 2022

IJRCS

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This paper considers the problem of Fault Tolerant Tracking Control (FTTC) strategy design for nonlinear systems using Takagi-Sugeno (T-S) fuzzy models with measurable premise variables affected by actuator faults subject to unknown bounded disturbances (UBD). Firstly, the Adaptive Fuzzy Observer (AFO) is proposed to estimate the faults. Based on the information provided by this observer, an active fault tolerant tracking controller described by an adaptive Proportional-Integral-Derivative (PID) structure has been developed to compensate for the actuator fault effects and to guarantee the trajectory tracking of desired outputs to the reference model despite the presence of actuator faults. The stability and the trajectory tracking performances of the proposed approach are analyzed based on the Lyapunov theory. Sufficient conditions can be obtained and solved for the design of the controller, and the observer gains using Linear Matrix Inequalities (LMIs). Finally, the effectiveness of the proposed technique is illustrated by using a single-link flexible joint robot.

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Active versus passive fault-tolerant control of a redundant multirotor UAV

Cited by 32 publications

References 23 publications

Multivariate Data Analysis for Motor Failure Detection and Isolation in A Multicopter UAV Using Real-Flight Attitude Signals

Multivariate Data Analysis for Motor Failure Detection and Isolation in A Multicopter UAV Using Real-Flight Attitude Signals

Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters

Adaptive PID Fault-Tolerant Tracking Controller for Takagi-Sugeno Fuzzy Systems with Actuator Faults: Application to Single-Link Flexible Joint Robot

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