Motor Failure Tolerant Control System With Self Diagnostics for Unmanned Multirotors

Ambroziak, Leszek; Simha, Ashutosh; Pawłuszewicz, Ewa; Kotta, Ülle; Bożko, Arkadiusz; Kondratiuk, Mirosław

doi:10.1109/mmar.2019.8864726

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…Adjusting the center of mass of the quadcopter has also been studied as a proposal solution to keep hovering or safely land the quadcopter in case of failure of one motor (Ambroziak et al, 2019;Muhamad, Nasir, Kari, & Ali, 2017). In Ambroziak et al (2019), authors proposed an onboard failure detection method based on gyroscopic (IMU) measurements in addition to the re-configuration procedure of the PID control system and shifting the plant center of mass, if necessary, in case of partial or complete failure in a single rotor of the quadcopter. However, such methods are able to successfully control the drone in experimental environment, additional mechanical equipment is needed for altering the mass structure of the drone during the flight.…”

Section: Drone Controlmentioning

confidence: 99%

Remote Run-Time Failure Detection and Recovery Control For Quadcopters

Shahsavari

Rabah

Immonen

et al. 2022

JID

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We propose an adaptive run-time failure recovery control system for quadcopter drones, based on remote real-time processing of measurement data streams. Particularly, the measured RPM values of the quadcopter motors are transmitted to a remote machine which hosts failure detection algorithms and performs recovery procedure. The proposed control system consists of three distinct parts: (1) A set of computationally simple PID controllers locally onboard the drone, (2) a set of computationally more demanding remotely hosted algorithms for real-time drone state detection, and (3) a digital twin co-execution software platform — the ModelConductor-eXtended — for two-way signal data exchange between the former two. The local on-board control system is responsible for maneuvering the drone in all conditions: path tracking under normal operation and safe landing in a failure state. The remote control system, on the other hand, is responsible for detecting the state of the drone and communicating the corresponding control commands and controller parameters to the drone in real time. The proposed control system concept is demonstrated via simulations in which a drone is represented by the widely studied Quad-Sim six degrees-of-freedom Simulink model. Results show that the trained failure detection binary classifier achieves a high level of performance with F1-score of 96.03%. Additionally, time analysis shows that the proposed remote control system, with average execution time of 0.49 milliseconds and total latency of 6.92 milliseconds in two-way data communication link, meets the real-time constraints of the problem. The potential practical applications for the presented approach are in drone operation in complex environments such as factories (indoor) or forests (outdoor).

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Section: Drone Controlmentioning

confidence: 99%

Remote Run-Time Failure Detection and Recovery Control For Quadcopters

Shahsavari

Rabah

Immonen

et al. 2022

JID

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“…In the mentioned statement, the UAV is a critical component, and its ability to confidently and safely perform airspace missions is necessary. One of the most important issues that has been developed and studied intensively is fault tolerant control systems (FTCS) dedicated to different types of unmanned aircraft [ 8 , 9 , 10 , 11 ], which must be accurately mathematically modeled before implementation [ 12 , 13 ]. FTCM can be divided into active and passive kinds.…”

Section: Introductionmentioning

confidence: 99%

Multirotor Motor Failure Detection with Piezo Sensor

Ambroziak

Ołdziej

Koszewnik

2023

Sensors

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Failure detection of Unmanned Aerial Vehicle (UAV) motors and propulsion systems is the most important step in the implementation of active fault-tolerant control systems. This will increase the reliability of unmanned systems and increase the level of safety, especially in civil and commercial applications. The following paper presents a method of motor failure detection in the multirotor UAV using piezo bars. The results of a real flight, in which the failure of the propulsion system caused the crash of a hybrid VTOL UAV, were presented and analyzed. The conclusions drawn from this flight led to the development of a lightweight, simple and reliable sensor that can detect a failure of the UAV propulsion system. The article presents the outcomes of laboratory tests concerning measurements made with a piezo sensor. An extensive analysis of the obtained results of vibrations recorded on a flying platform arm with a propulsion system is presented, and a methodology for using this type of data to detect failures is proposed. The article presents the possibility of using a piezoelectric sensor to record vibrations on the basis of which it is possible to detect a failure of the UAV propulsion system.

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“…In recent years, robotics researchers have shown an increasing interest in autonomy of mobile vehicles. The autonomy of robots is mainly associated with obstacle detection and avoidance systems (Gao et al, 2019;Rulin, 2017), precise navigation systems (Romaniuk et al, 2016;Bakkali et al, 2007), new control methods allowing adaptation to failures (Ambroziak et al, 2019;Lanzon et al, 2014), cooperation of a few objects, and formation and swarm motion (Ambroziak et al, 2015;Kownacki et al, 2019). Mentioned topics relate to tasks carried out by mobile robots in indoor and outdoor conditions.…”

Section: Introductionmentioning

confidence: 99%

Efficient Non-Odometry Method for Environment Mapping and Localisation of Mobile Robots

Adamowicz

Ambroziak

Kondratiuk

2021

Acta Mechanica Et Automatica

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The paper presents the simple algorithm of simultaneous localisation and mapping (SLAM) without odometry information. The proposed algorithm is based only on scanning laser range finder. The theoretical foundations of the proposed method are presented. The most important element of the work is the experimental research. The research underlying the paper encompasses several tests, which were carried out to build the environment map to be navigated by the mobile robot in conjunction with the trajectory planning algorithm and obstacle avoidance.

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Motor Failure Tolerant Control System With Self Diagnostics for Unmanned Multirotors

Cited by 6 publications

References 14 publications

Remote Run-Time Failure Detection and Recovery Control For Quadcopters

Remote Run-Time Failure Detection and Recovery Control For Quadcopters

Multirotor Motor Failure Detection with Piezo Sensor

Efficient Non-Odometry Method for Environment Mapping and Localisation of Mobile Robots

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