567 research outputs found
Fault Diagnosis and Fault-Tolerant Control of Unmanned Aerial Vehicles
With the increasing demand for unmanned aerial vehicles (UAVs) in both military and civilian applications, critical safety issues need to be specially considered in order to make better and wider use of them. UAVs are usually employed to work in hazardous and complex environments, which may seriously threaten the safety and reliability of UAVs. Therefore, the safety and reliability of UAVs are becoming imperative for development of advanced intelligent control systems. The key challenge now is the lack of fully autonomous and reliable control techniques in face of different operation conditions and sophisticated environments. Further development of unmanned aerial vehicle (UAV) control systems is required to be reliable in the presence of system component faults and to be insensitive to model uncertainties and external environmental disturbances.
This thesis research aims to design and develop novel control schemes for UAVs with consideration of all the factors that may threaten their safety and reliability. A novel adaptive sliding mode control (SMC) strategy is proposed to accommodate model uncertainties and actuator faults for an unmanned quadrotor helicopter. Compared with the existing adaptive SMC strategies in the literature, the proposed adaptive scheme can tolerate larger actuator faults without stimulating control chattering due to the use of adaptation parameters in both continuous and discontinuous control parts. Furthermore, a fuzzy logic-based boundary layer and a nonlinear disturbance observer are synthesized to further improve the capability of the designed control scheme for tolerating model uncertainties, actuator faults, and unknown external disturbances while preventing overestimation of the adaptive control parameters and suppressing the control chattering effect. Then, a cost-effective fault estimation scheme with a parallel bank of recurrent neural networks (RNNs) is proposed to accurately estimate actuator fault magnitude and an active fault-tolerant control (FTC) framework is established for a closed-loop quadrotor helicopter system. Finally, a reconfigurable control allocation approach is combined with adaptive SMC to achieve the capability of tolerating complete actuator failures with application to a modified octorotor helicopter. The significance of this proposed control scheme is that the stability of the closed-loop system is theoretically guaranteed in the presence of both single and simultaneous actuator faults
Model Predictive Control for Micro Aerial Vehicles: A Survey
This paper presents a review of the design and application of model
predictive control strategies for Micro Aerial Vehicles and specifically
multirotor configurations such as quadrotors. The diverse set of works in the
domain is organized based on the control law being optimized over linear or
nonlinear dynamics, the integration of state and input constraints, possible
fault-tolerant design, if reinforcement learning methods have been utilized and
if the controller refers to free-flight or other tasks such as physical
interaction or load transportation. A selected set of comparison results are
also presented and serve to provide insight for the selection between linear
and nonlinear schemes, the tuning of the prediction horizon, the importance of
disturbance observer-based offset-free tracking and the intrinsic robustness of
such methods to parameter uncertainty. Furthermore, an overview of recent
research trends on the combined application of modern deep reinforcement
learning techniques and model predictive control for multirotor vehicles is
presented. Finally, this review concludes with explicit discussion regarding
selected open-source software packages that deliver off-the-shelf model
predictive control functionality applicable to a wide variety of Micro Aerial
Vehicle configurations
A Contribution to the Design of Highly Redundant Compliant Aerial Manipulation Systems
Es ist vorhersehbar, dass die Luftmanipulatoren in den nĂ€chsten Jahrzehnten fĂŒr viele Aufgaben eingesetzt werden, die entweder zu gefĂ€hrlich oder zu teuer sind, um sie mit herkömmlichen Methoden zu bewĂ€ltigen. In dieser Arbeit wird eine neuartige Lösung fĂŒr die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform fĂŒr die DurchfĂŒhrung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewĂ€hrleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem kĂŒnstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz fĂŒr die Drohne erzielt. AuĂerdem wird die MotorsĂ€ttigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. FĂŒr die Beobachtung der externen KrĂ€fte und Drehmomente werden zwei Filter vorgestellt. Dies ist notwendig, um ein nachgiebiges Verhalten des Endeffektors durch die achsenselektive Impedanzregelung zu erreichen. Unter Ausnutzung der Redundanz des vorgestellten Luftmanipulators wird ein Regler entworfen, der nicht nur die Referenz der Endeffektor-Bewegung verfolgt, sondern auch priorisierte sekundĂ€re Aufgaben ausfĂŒhrt. Die Wirksamkeit der vorgestellten Lösungen wird durch umfangreiche Tests ĂŒberprĂŒft, und das vorgestellte Steuerungssystem wird als sehr vielseitig und effektiv bewertet.:1 Introduction
2 Fundamentals
3 System Design and Modeling
4 Reconfigurable Control Allocation
5 Fault Diagnostics For Free Flight
6 Force and Torque Observer
7 Trajectory Generation
8 Hybrid Task Priority Control
9 System Integration and Performance Evaluation
10 ConclusionIn the following decades, aerial manipulators are expected to be deployed in scenarios that are either too dangerous for human beings or too expensive to be accomplished by traditional methods. This thesis presents a novel solution for the overall control of highly redundant aerial manipulation systems. The results are applied to a reference configuration established as a universal platform for performing various aerial manipulation tasks. The platform consists of an omnidirectional multirotor UAV and a serial manipulator. To ensure modular control design, two computationally efficient algorithms are studied to allocate the virtual input to actuator commands. Fault tolerance of the aerial vehicle is achieved by integrating a diagnostic module based on an artificial neural network and the reconfigurable control allocation into the control loop. Besides, the risk of input saturation of individual rotors is minimized by predicting and reconfiguring the speed and acceleration responses. Two filter-based observers are presented to provide the knowledge of external forces and torques, which is necessary to achieve compliant behavior of the end-effector through an axis-selective impedance control in the outer loop. Exploiting the redundancy of the proposed aerial manipulator, the author has designed a control law to achieve the desired end-effector motion and execute secondary tasks in order of priority. The effectiveness of the proposed designs is verified with extensive tests generated by following Monte Carlo method, and the presented control scheme is proved to be versatile and effective.:1 Introduction
2 Fundamentals
3 System Design and Modeling
4 Reconfigurable Control Allocation
5 Fault Diagnostics For Free Flight
6 Force and Torque Observer
7 Trajectory Generation
8 Hybrid Task Priority Control
9 System Integration and Performance Evaluation
10 Conclusio
Unified incremental nonlinear controller for the transition control of a hybrid dual-axis tilting rotor quad-plane
Overactuated Tilt Rotor Unmanned Aerial Vehicles are renowned for exceptional
wind resistance and a broad operational range, which poses complex control
challenges due to non-affine dynamics. Traditional solutions employ multi-state
switched logic controllers for transitions. Our study introduces a novel
unified incremental nonlinear controller for overactuated dual-axis tilting
rotor quad-planes, seamlessly managing pitch, roll, and physical actuator
commands. The control allocation problem is addressed using a SQP iterative
optimization algorithm, well-suited for nonlinear actuator effectiveness in
thrust vectoring vehicles. The controller design integrates desired roll and
pitch angle inputs. These desired attitude angles are autonomously managed by
the controller and then conveyed to the vehicle during slow airspeed phases,
when the vehicle maintains its 6 DOF. We incorporate an AoA protection logic to
prevent wing stall and a yaw rate reference model for coordinated turns. Flight
tests confirm the controller's effectiveness in transitioning from hovering to
forward flight, achieving desired vertical and lateral accelerations, and
reverting to hovering
Hybrid active force control for fixed based rotorcraft
Disturbances are considered major challenges faced in the deployment of rotorcraft unmanned aerial vehicle (UAV) systems. Among different types of rotorcraft systems, the twin-rotor helicopter and quadrotor models are considered the most versatile flying machines nowadays due to their range of applications in the civilian and military sectors. However, these systems are multivariate and highly non-linear, making them difficult to be accurately controlled. Their performance could be further compromised when they are operated in the presence of disturbances or uncertainties. This dissertation presents an innovative hybrid control scheme for rotorcraft systems to improve disturbance rejection capability while maintaining system stability, based on a technique called active force control (AFC) via simulation and experimental works. A detailed dynamic model of each aerial system was derived based on the EulerâLagrange and Newton-Euler methods, taking into account various assumptions and conditions. As a result of the derived models, a proportional-integral-derivative (PID) controller was designed to achieve the required altitude and attitude motions. Due to the PID's inability to reject applied disturbances, the AFC strategy was incorporated with the designed PID controller, to be known as the PID-AFC scheme. To estimate control parameters automatically, a number of artificial intelligence algorithms were employed in this study, namely the iterative learning algorithm and fuzzy logic. Intelligent rules of these AI algorithms were designed and embedded into the AFC loop, identified as intelligent active force control (IAFC)-based methods. This involved, PID-iterative learning active force control (PID-ILAFC) and PID-fuzzy logic active force control (PID-FLAFC) schemes. To test the performance and robustness of these proposed hybrid control systems, several disturbance models were introduced, namely the sinusoidal wave, pulsating, and Dryden wind gust model disturbances. Integral square error was selected as the index performance to compare between the proposed control schemes. In this study, the effectiveness of the PID-ILAFC strategy in connection with the body jerk performance was investigated in the presence of applied disturbance. In terms of experimental work, hardware-in-the-loop (HIL) experimental tests were conducted for a fixed-base rotorcraft UAV system to investigate how effective are the proposed hybrid PID-ILAFC schemes in disturbance rejection. Simulated results, in time domains, reveal the efficacy of the proposed hybrid IAFC-based control methods in the cancellation of different applied disturbances, while preserving the stability of the rotorcraft system, as compared to the conventional PID controller. In most of the cases, the simulated results show a reduction of more than 55% in settling time. In terms of body jerk performance, it was improved by around 65%, for twin-rotor helicopter system, and by a 45%, for quadrotor system. To achieve the best possible performance, results recommend using the full output signal produced by the AFC strategy according to the sensitivity analysis. The HIL experimental tests results demonstrate that the PID-ILAFC method can improve the disturbance rejection capability when compared to other control systems and show good agreement with the simulated counterpart. However, the selection of the appropriate learning parameters and initial conditions is viewed as a crucial step toward this improved performance
Integrated approaches to handle UAV actuator fault
Unmanned AerialVehicles (UAV) has historically shown to be unreliable when
compared to their manned counterparts. Part of the reason is they may not be
able to a ord the redundancies required to handle faults from system or cost
constraints. This research explores instances when actuator fault handling may
be improved with integrated approaches for small UAVs which have limited
actuator redundancy.
The research started with examining the possibility of handling the case where
no actuator redundancy remains post fault. Two fault recovery schemes, combing
control allocation and hardware means, for a Quad Rotor UAV with no redundancy
upon fault event are developed to enable safe emergency landing.
Inspired by the integrated approach, a proposed integrated actuator control
scheme is developed, and shown to reduce the magnitude of the error dynamics
when input saturation faults occur. Geometrical insights to the proposed actuator
scheme are obtained. Simulations using an Aerosonde UAV model with the
proposed scheme showed significant improvements to the fault tolerant stuck
fault range and improved guidance tracking performance.
While much research literature has previously been focused on the controller
to handle actuator faults, fault tolerant guidance schemes may also be utilized to
accommodate the fault. One possible advantage of using fault tolerant guidance
is that it may consider the fault degradation e ects on the overall mission.
A fault tolerant guidance reconfiguration method is developed for a path following
mission. The method provides an additional degree of freedom in design,
which allows more flexibility to the designer to meet mission requirements.
This research has provided fresh insights into the handling UAV extremal
actuator faults through integrated approaches. The impact of this work is to expand
on the possibilities a practitioner may have for improving the fault handling
capabilities of a UAV
Safe and accurate MAV Control, navigation and manipulation
This work focuses on the problem of precise, aggressive and safe Micro Aerial Vehicle (MAV) navigation as well as deployment in applications which require physical interaction with the environment. To address these issues, we propose three different MAV model based control algorithms that rely on the concept of receding horizon control. As a starting point, we present a computationally cheap algorithm which utilizes an approximate linear model of the system around hover and is thus maximally accurate for slow reference maneuvers. Aiming at overcoming the limitations of the linear model parameterisation, we present an extension to the first controller which relies on the true nonlinear dynamics of the system. This approach, even though computationally more intense, ensures that the control model is always valid and allows tracking of full state aggressive trajectories. The last controller addresses the topic of aerial manipulation in which the versatility of
aerial vehicles is combined with the manipulation capabilities of robotic arms. The proposed method relies on the formulation of a hybrid nonlinear MAV-arm
model which also takes into account the effects of contact with the environment. Finally, in order to enable safe operation despite the potential loss of an
actuator, we propose a supervisory algorithm which estimates the health status of each motor. We further showcase how this can be used in conjunction with
the nonlinear controllers described above for fault tolerant MAV flight. While all the developed algorithms are formulated and tested using our specific MAV platforms (consisting of underactuated hexacopters for the free flight experiments, hexacopter-delta arm system for the manipulation experiments),
we further discuss how these can be applied to other underactuated/overactuated MAVs and robotic arm platforms. The same applies to the fault tolerant
control where we discuss different stabilisation techniques depending on the capabilities of the available hardware. Even though the primary focus of this work is on feedback control, we thoroughly describe the custom hardware platforms used for the experimental evaluation, the state estimation algorithms which provide the basis for control
as well as the parameter identification required for the formulation of the various control models.
We showcase all the developed algorithms in experimental scenarios designed to highlight the corresponding strengths and weaknesses as well as show that the proposed methods can run in realtime on commercially available hardware.Open Acces
Optimal fault-tolerant flight control for aircraft with actuation impairments
Current trends towards greater complexity and automation are leaving modern
technological systems increasingly vulnerable to faults. Without proper action, a
minor error may lead to devastating consequences. In flight control, where the
controllability and dynamic stability of the aircraft primarily rely on the control
surfaces and engine thrust, faults in these effectors result in a higher extent of risk for
these aspects. Moreover, the operation of automatic flight control would be suddenly
disturbed. To address this problem, different methodologies of designing optimal
flight controllers are presented in this thesis. For multiple-input multiple-output
(MIMO) systems, the feedback optimal control is a prominent technique that solves
a multi-objective cost function, which includes, for instance, tracking requirements
and control energy minimisation.
The first proposed method is based on a linear quadratic regulator (LQR) control
law augmented with a fault-compensation scheme. This fault-tolerant system handles
the situation in an adaptive way by solving the optimisation cost function and
considering fault information, while assuming an effective fault detection system is
available. The developed scheme was tested in a six-degrees-of-freedom nonlinear
environment to validate the linear-based controller. Results showed that this fault
tolerant control (FTC) strategy managed to handle high magnitudes of the actuatorâs
loss of effciency faults. Although the rise time of aircraft response became slower,
overshoot and settling errors were minimised, and the stability of the aircraft was
maintained.
Another FTC approach has been developed utilising the features of controller
robustness against the system parametric uncertainties, without the need for reconfiguration
or adaptation. Two types of control laws were established under this scheme,
the
Hâ
and ”-synthesis controllers. Both were tested in a nonlinear environment
for three points in the flight envelope: ascending, cruising, and descending. The
Hâ
controller maintained the requirements in the intact case; while in fault, it yielded
non-robust high-frequency control surface deflections. The ”-synthesis, on the other
hand, managed to handle the constraints of the system and accommodate faults
reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of
the actuators in the design process. To accommodate lock-in-place faults, a new
control effort redistribution scheme was proposed using the fuzzy logic technique,
assuming faults are provided by a fault detection system. The results of simulation
testing on a Boeing 747 multi-effector model showed that the system managed to
handle these faults and maintain good tracking and stability performance, with some
acceptable degradation in particular fault scenarios. The limitations of the controller
to handle a high degree of faults were also presented
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