Fault tolerant control of multi-rotor unmanned aerial vehicles using sliding mode based schemes

This thesis investigates fault-tolerant control (FTC) for the specific application of small multirotor unmanned aerial vehicles (Unmanned Aerial Vehicle (UAV)s). The fault-tolerant controllers in this thesis are based on the combination of sliding mode control with control allocation where the control signals are distributed based on motors' health level. This alleviates the need to reconfigure the overall structure of the controllers. The thesis considered both the over actuated (sufficient redundancy) and under-actuated UAVs. Three multirotor UAVs have been considered in this thesis which includes a quadrotor (4 rotors), an Octocopter (8 rotors) and a spherical UAV. The non-linear mathematical models for each of the UAVs are presented. One of the main contributions of this thesis is the hardware implementation of the sliding mode Fault Tolerant Control (FTC) scheme on an open-source autopilot microcontroller called Pixhawk for a quadrotor UAV. The controller was developed in Simulink and implemented on the microcontroller using the Matlab/Simulink support packages. A gimbal- based test rig was developed and built to offer a safe test bed for testing control designs. Actual flight tests were done which showed sound responses during fault-free and faulty scenarios. This work represents one of successful implementation work of sliding mode FTC in the literature. Another key contribution of this thesis is the development of the mathematical model of a unique spherical UAV with highly redundant control inputs. The use of novel 8 flaps and 2 rotors configuration of the spherical UAV considered in this thesis provides a unique fault tolerant capability, especially when combined with the sliding mode-based FTC scheme. A key development in the later chapters of the thesis considers fault-tolerant control strategy when no redundancy is available. Unlike many works which consider FTC on quadrotors in the literature (which can only handle faults), the proposed schemes in the later chapters also include cases when failures also occur converting the system to an under actuated system. In one chapter, a bespoke Linear Parameter Varying (LPV) based controller is developed for a reduced attitude dynamics system by exploiting non-standard equation of motions which relates to position acceleration and load factor dynamics. This is unique as compared to the typical Euler angle control (roll, pitch and yaw angle control). In the last chapter, a fault-tolerant control scheme which can handle both the over and under actuated system is presented. The scheme considers an octocopter and can be used in fault-free, faulty and failure conditions up to two remaining motors. The scheme exploits the differential flatness property, another unique property of multirotor UAVs. This allows both inner loop and outer loop controller to be designed using sliding mode (as opposed to many sliding mode FTC in the literature, which only considers sliding mode for the inner loop control)

Detection and Isolation of Faults and Cyberattacks in Nonlinear Cyber-Physical Systems using Neural Networks

The theory of Cyber-physical systems (CPSs) has applications in critical infrastructures such as smart grids, manufacturing systems, transportation systems, and autonomous systems such as Unmanned Aerial Vehicles(UAVs). In the CPS, there is a coordination between communication, computation, and control. The communication link in CPS can be subjected to malicious cyberattacks. On the other hand, the physical system in CPS can be faced with different faults such as sensor, actuator, and component faults. Therefore, two significant and challenging problems in CPS can be the detection of faults and cyberattacks. These two threats are intrinsically distinctive and need different strategies to deal with when they occur. This research mainly focuses on providing a methodology to detect and isolate faults and cyberattacks. This work considers false data injection and replay attacks as security threats. Two different adaptive neural network-based detection methods are proposed in this thesis. These adaptive neural networks are able to detect, isolate, and estimate false data injection, and replay attacks. Another contribution of this thesis is to provide a scheme for isolating faults and cyberattacks (false data injection and replay attacks) by using virtual sensors on the plant side, which makes the simultaneous detection of faults and false data injection cyberattacks possible. A nonlinear model of a quadrotor is considered the case study, and the performance of the neural network-based schemes is evaluated through various numerical simulation scenarios

Automatic Flight Control Systems

The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

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

Diagnosis of Icing and Actuator Faults in UAVs Using LPV Unknown Input Observers

This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions. The developed theory is supported by simulations illustrating the diagnosis of actuator faults and icing in a small UAV. The obtained results validate the effectiveness of the proposed approach

Dual observer based adaptive controller for hybrid drones

A biplane quadrotor (hybrid vehicle) benefits from rotary-wing and fixed-wing structures. We design a dual observer-based autonomous trajectory tracking controller for the biplane quadrotor. Extended state observer (ESO) is designed for the state estimation, and based on this estimation, a Backstepping controller (BSC), Integral Terminal Sliding Mode Controller (ITSMC), and Hybrid Controller (HC) that is a combination of ITSMC + BSC are designed for the trajectory tracking. Further, a Nonlinear disturbance observer (DO) is designed and combined with ESO based controller to estimate external disturbances. In this simulation study, These ESO-based controllers with and without DO are applied for trajectory tracking, and results are evaluated. An ESO-based Adaptive Backstepping Controller (ABSC) and Adaptive Hybrid controller (AHC) with DO are designed, and performance is evaluated to handle the mass change during the flight despite wind gusts. Simulation results reveal the effectiveness of ESO-based HC with DO compared to ESO-based BSC and ITSMC with DO. Furthermore, an ESO-based AHC with DO is more efficient than an ESO-based ABSC with DO.Web of Science71art. no. 4

Robust adaptive sampled-data control design for MIMO systems: Applications in cyber-physical security

This dissertation extends the L1 adaptive control theory to sampled-data (SD) framework. Multi-input multi-output non-square (underactuated) systems are considered with different sampling rates for inputs and outputs. The sampled-data framework allows to address non-minimum phase systems, subject to less restrictive assumptions as compared to continuous time framework. It is shown that the closed-loop system can recover the response of a continuous-time reference system as the sampling time of the SD controller tends to zero. In this thesis, the L1 sampled data adaptive controller is integrated with the Simplex fault-tolerant architecture for resilient control of cyber-physical systems (CPSs). Detection and mitigation of zero-dynamics attacks are addressed and validated in flight tests of a quadrotor in Intelligent Robotics Laboratory of UIUC. The experiments show that the multirate L1 controller can e effectively detect stealthy zero-dynamics attacks and recover the stability of the perturbed system, where the single-rate conventional L1 adaptive controller fails. From the perspective of applications, the dissertation considers navigation and control of autonomous vehicles and proposes a two-loop framework, in which the high-level reference commands are limited by a saturation function, while the low-level controller tracks the reference by compensating for disturbances and uncertainties. A class of nested, uncertain, multi-input multi-output (MIMO) systems subject to reference command saturation, possibly with non-minimum phase zeros, is considered. Robust stability and performance of the overall closed-loop system with command saturation and multirate L1 adaptive controller are analyzed. Finally, a systematic analysis and synthesis method is proposed for the optimal design of filters in the L1 adaptive output-feedback structure, where the lowpass filter is the key to the trade-off between the performance and robustness of the closed-loop system. An optimization problem is formulated using the constraint on the input time-delay margin and a cost-function based on mixed L1/H2-norm performance measure. The optimization problem can be efficiently solved using linear/quadratic programming. We note that the framework of this dissertation and the multi-loop problem formulation of navigation and control of autonomous systems provide suitable synthesis and analysis tools for autonomous cyber-physical systems (CPSs), including self-driving cars, unmanned aerial vehicles (UAVs), and industrial/medical robots, to name just a few. The SD design facilitates the implementation of control laws on digital computers in CPSs, where the input/output signals are available at discrete time instances with different sampling rates

Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation