Fault tolerant control of a quadrotor using L-1 adaptive control

Purpose – The growing use of small unmanned rotorcraft in civilian applications means that safe operation is increasingly important. The purpose of this paper is to investigate the fault tolerant properties to faults in the actuators of an L1 adaptive controller for a quadrotor vehicle. Design/methodology/approach – L1 adaptive control provides fast adaptation along with decoupling between adaptation and robustness. This makes the approach a suitable candidate for fault tolerant control of quadrotor and other multirotor vehicles. In the paper, the design of an L1 adaptive controller is presented. The controller is compared to a fixed-gain LQR controller. Findings – The L1 adaptive controller is shown to have improved performance when subject to actuator faults, and a higher range of actuator fault tolerance. Research limitations/implications – The control scheme is tested in simulation of a simple model that ignores aerodynamic and gyroscopic effects. Hence for further work, testing with a more complete model is recommended followed by implementation on an actual platform and flight test. The effect of sensor noise should also be considered along with investigation into the influence of wind disturbances and tolerance to sensor failures. Furthermore, quadrotors cannot tolerate total failure of a rotor without loss of control of one of the degrees of freedom, this aspect requires further investigation. Practical implications – Applying the L1 adaptive controller to a hexrotor or octorotor would increase the reliability of such vehicles without recourse to methods that require fault detection schemes and control reallocation as well as providing tolerance to a total loss of a rotor. Social implications – In order for quadrotors and other similar unmanned air vehicles to undertake many proposed roles, a high level of safety is required. Hence the controllers should be fault tolerant. Originality/value – Fault tolerance to partial actuator/effector faults is demonstrated using an L1 adaptive controller

Adaptive and Optimal Motion Control of Multi-UAV Systems

This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

Investigations of Model-Free Sliding Mode Control Algorithms including Application to Autonomous Quadrotor Flight

Sliding mode control is a robust nonlinear control algorithm that has been used to implement tracking controllers for unmanned aircraft systems that are robust to modeling uncertainty and exogenous disturbances, thereby providing excellent performance for autonomous operation. A significant advance in the application of sliding mode control for unmanned aircraft systems would be adaptation of a model-free sliding mode control algorithm, since the most complex and time-consuming aspect of implementation of sliding mode control is the derivation of the control law with incorporation of the system model, a process required to be performed for each individual application of sliding mode control. The performance of four different model-free sliding mode control algorithms was compared in simulation using a variety of aerial system models and real-world disturbances (e.g. the effects of discretization and state estimation). The two best performing algorithms were shown to exhibit very similar behavior. These two algorithms were implemented on a quadrotor (both in simulation and using real-world hardware) and the performance was compared to a traditional PID-based controller using the same state estimation algorithm and control setup. Simulation results show the model-free sliding mode control algorithms exhibit similar performance to PID controllers without the tedious tuning process. Comparison between the two model-free sliding mode control algorithms showed very similar performance as measured by the quadratic means of tracking errors. Flight testing showed that while a model-free sliding mode control algorithm is capable of controlling realworld hardware, further characterization and significant improvements are required before it is a viable alternative to conventional control algorithms. Large tracking errors were observed for both the model-free sliding mode control and PID based flight controllers and the performance was characterized as unacceptable for most applications. The poor performance of both controllers suggests tracking errors could be attributed to errors in state estimation, which effectively introduce unknown dynamics into the feedback loop. Further testing with improved state estimation would allow for more conclusions to be drawn about the performance characteristics of the model-free sliding mode control algorithms

Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance

Robust Adaptive Output Tracking for Quadrotor Helicopters

Quadrotor helicopters are drawing considerable attention both for their mobility and their potential to perform multiple tasks in complete autonomy. Moreover, the numerous limitations characterizing these aircraft, such as their underactuation, make quadrotors ideal testbeds for innovative theoretical approaches to the problem of controlling autonomous mechanical systems. In this chapter, we propose a robust model reference adaptive control architecture and design an autopilot for quadrotors, which guarantees satisfactory output tracking despite uncertainties in the vehicle’s mass, matrix of inertia, and location of the center of mass. The feasibility of our results is supported by a detailed analysis of the quadrotor’s equations of motion. Specifically, considering the vehicle’s equations of motion as a time-varying nonlinear dynamical system and avoiding the common assumption that the vehicle’s Euler angles are small at all times, we prove that the proposed autopilot guarantees satisfactory output tracking and verifies sufficient conditions for a weak form of controllability of the closed-loop system known as strong accessibility. A numerical example illustrates the applicability of the theoretical results presented and clearly shows how the proposed autopilot outperforms in strong wind conditions autopilots designed using a commonly employed proportional-derivative control law and a conventional model reference adaptive control law

Modeling and nonlinear adaptive control of an aerial manipulation system

Autonomous aerial robots have become an essential part of many civilian and military applications. The workspace and agility of these vehicles motivated great research interest resulting in various studies addressing their control architectures and mechanical configurations. Increasing autonomy enabled them to perform tasks such as surveillance, inspection and remote sensing in hazardous and challenging environments. The ongoing research promises further contributions to the society, in both theory and practice. To furthermore extend their vast applications, aerial robots are equipped with the tools to enable physical interaction with the environment. These tasks represent a great challenge due to the technological limitations as well as the lack of sophisticated methods necessary for the control of the system to perform desired operations in an efficient and stable manner. Modeling and control problem of an aerial manipulation is still an open research topic with many studies addressing these issues from different perspectives. This thesis deals with the nonlinear adaptive control of an aerial manipulation system (AMS). The system consists of a quadrotor equipped with a 2 degrees of freedom (DOF) manipulator. The complete modeling of the system is done using the Euler-Lagrange method. A hierarchical nonlinear control structure which consists of outer and inner control loops has been utilized. Model Reference Adaptive Controller (MRAC) is designed for the outer loop where the required command signals are generated to force the quadrotor to move on a reference trajectory in the presence of mass uncertainties and reaction forces coming from the manipulator. For the inner loop, the attitude dynamics of the quadrotor and the joint dynamics of the 2-DOF robotic arm are considered as a fully actuated 5-DOF unified part of the AMS. Nonlinear adaptive control has been utilized for the low-level controller where the changes in inertias have been considered. The proposed controller is tested on a high fidelity AMS model in the presence of uncertainties, wind disturbances and measurement noise, and satisfactory trajectory tracking performance with improved robustness is achieved

L1\mathcal{L}_1Quad: L1\mathcal{L}_1 Adaptive Augmentation of Geometric Control for Agile Quadrotors with Performance Guarantees

Quadrotors that can operate safely in the presence of imperfect model knowledge and external disturbances are crucial in safety-critical applications. We present L1Quad, a control architecture for quadrotors based on the L1 adaptive control. L1Quad enables safe tubes centered around a desired trajectory that the quadrotor is always guaranteed to remain inside. Our design applies to both the rotational and the translational dynamics of the quadrotor. We lump various types of uncertainties and disturbances as unknown nonlinear (time- and state-dependent) forces and moments. Without assuming or enforcing parametric structures, L1Quad can accurately estimate and compensate for these unknown forces and moments. Extensive experimental results demonstrate that L1Quad is able to significantly outperform baseline controllers under a variety of uncertainties with consistently small tracking errors.Comment: The first two authors contributed equally to this wor

Quadrotor Simulator for Control De-velopment – Application to Autono-mous Landing

In this thesis is studied the landing problem of a VTOL UAV and a 3D sim-ulation environment is built to safely develop control for a quadrotor, resorting to 3D modelling and simulation software. In a time where the development of unmanned vehicles is a trend and it is technologically in growth, the emergent difficulties are challenging when it comes to aviation. In this field, it is useful a tool for researchers to have at their disposal to conduct experiments without putting their real systems to real threat. Also, the landing of UAV’s is currently one of the most serious cases of study with a lot of investigation going on to solve the problems associated with it. In this sense, some problematics are contemplated. Based on a quadrotor in a X8 configuration – 4 frames and 8 propellers –, are applied linear and nonlinear control design techniques with the intent to sta-bilize and control the quadrotor and a 3D simulator is developed

Nonlinear adaptive control of an aerial manipulation system

This paper presents the nonlinear adaptive control of a quadrotor endowed with a 2 degrees of freedom (DOF) manipulator. By considering the quadrotor and the robot arm as a combined system, complete modeling of the aerial manipulation system (AMS) has been presented using the Euler-Lagrange method. A hierarchical nonlinear control scheme which consists of outer and inner control loops has been utilized. Model Reference Adaptive Controller (MRAC) is designed for the outer loop where the required command signals are generated to force the quadrotor to move on a reference trajectory in the presence of uncertainties and reaction forces coming from the manipulator. For the inner loop, the attitude dynamics of the quadrotor and the dynamics of the 2-DOF robotic arm are considered as a fully actuated 5-DOF unified part of the AMS. Nonlinear adaptive control has been utilized for the low-level controller where the changes in inertias and the masses have been tackled along with the reaction forces acting on the attitude part of the AMS. The proposed technique has been validated through simulations in two different scenarios