Accurate Tracking of Aggressive Quadrotor Trajectories using Incremental Nonlinear Dynamic Inversion and Differential Flatness

Autonomous unmanned aerial vehicles (UAVs) that can execute aggressive (i.e., high-speed and high-acceleration) maneuvers have attracted significant attention in the past few years. This paper focuses on accurate tracking of aggressive quadcopter trajectories. We propose a novel control law for tracking of position and yaw angle and their derivatives of up to fourth order, specifically, velocity, acceleration, jerk, and snap along with yaw rate and yaw acceleration. Jerk and snap are tracked using feedforward inputs for angular rate and angular acceleration based on the differential flatness of the quadcopter dynamics. Snap tracking requires direct control of body torque, which we achieve using closed-loop motor speed control based on measurements from optical encoders attached to the motors. The controller utilizes incremental nonlinear dynamic inversion (INDI) for robust tracking of linear and angular accelerations despite external disturbances, such as aerodynamic drag forces. Hence, prior modeling of aerodynamic effects is not required. We rigorously analyze the proposed control law through response analysis, and we demonstrate it in experiments. The controller enables a quadcopter UAV to track complex 3D trajectories, reaching speeds up to 12.9 m/s and accelerations up to 2.1g, while keeping the root-mean-square tracking error down to 6.6 cm, in a flight volume that is roughly 18 m by 7 m and 3 m tall. We also demonstrate the robustness of the controller by attaching a drag plate to the UAV in flight tests and by pulling on the UAV with a rope during hover.Comment: To be published in IEEE Transactions on Control Systems Technology. Revision: new set of experiments at increased speed (up to 12.9 m/s), updated controller design using quaternion representation, new video available at https://youtu.be/K15lNBAKDC

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

Fault Tolerant Super Twisting Sliding Mode Control of a Quadrotor UAV Using Control Allocation

In this study, a fault-tolerant super-twisting sliding mode controller with a control allocation system for a quadrotor aircraft is proposed. Super twisting sliding mode control is a robust control technique that handles a system with a relative degree equal to one. A super-twisting sliding mode controller is proposed because of its robustness to uncertainties and perturbations. It increases accuracy and reduces chattering. A control allocation algorithm is developed to cope with the actuator fault. Firstly, a nonlinear model of the quadrotor unmanned aerial vehicle (UAV) is presented. Then, the controller design and type of the actuator fault are explained. The control allocation algorithm is used to optimize the trajectory tracking performance of the quadrotor in the presence of an actuator fault. A control allocation algorithm is an effective approach to implementing fault-tolerant control. When actuator faults are identified, they can be modeled as changes in the B matrix of constraints. Various simulations have been made for situations with and without actuator failure. In normal conditions, the quadrotor can accurately track altitude, roll, pitch and yaw references. In faulty conditions, the quadrotor can follow the references with a small error. Simulations prove the effectiveness of the control allocation algorithm, which stabilizes the quadrotor in case of an actuator fault. Overall, this paper presents a novel fault-tolerant controller design for quadrotor aircraft that effectively addresses actuator faults using a super-twisting sliding mode controller and control allocation algorithm

A Fully Autonomous Search and Rescue System Using Quadrotor UAV

In order to deal with critical missions a growing interest has been shown to the UAVs design. Flying robots are now used fire protection, surveillance and search & rescue (SAR) operations. In this paper, a fully autonomous system for SAR operations using quadrotor UAV is designed. In order to scan the damaged area, speeds up the searching process and detect any possible survivals a new search strategy that combines the standard search strategies with the probability of detection is developed. Furthermore the autopilot is designed using an optimal backstepping controller and this enables the tracking of the reference path with high accuracy and maximizes the flying time. Finally a comparison between the applied strategies is made using a study case of survivals search operation. The obtained results confirmed the efficiency of the designed system

Observer-based fuzzy tracking control for an unmanned aerial vehicle with communication constraints

We investigate the trajectory tracking problem of underactuated aerial vehicles with unknown mass in the presence of unknown non-vanishing disturbances using an event-triggered approach, while considering the constraint that the derivative of the reference trajectory is not available. In contrast to existing references where the derivative of the reference trajectory is needed, here we first introduce a high-gain observer to estimate the unknown derivative solely from the reference trajectory. A disturbance observer is designed to compensate for non-vanishing disturbances, such as wind, etc. Fuzzy logic systems are used to approximate the model uncertainty arising from the unknown mass of the vehicle, and then we derive a thrust command law that follows from a desired stabilizing force. Additionally, unlike traditional fixed and relative threshold strategies that rely solely on control signals, we develop a new time-varying eventtriggered mechanism linked to the performance of the controlled system, taking into account factors such as tracking errors, to develop angular velocity commands, enhancing tracking accuracy while efficiently conserving communication resources, especially in the absence of Zeno behavior. We present simulation results to demonstrate the efficacy of the proposed approach and validate the theoretical findings.</p

A Survey of path following control strategies for UAVs focused on quadrotors

The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.Peer ReviewedPostprint (author's final draft

Low Speed Flap-bounding in Ornithopters and its Inspiration on the Energy Efficient Flight of Quadrotors

Flap-bounding, a form of intermittent flight, is often exhibited by small birds over their entire range of flight speeds. The purpose of flap-bounding is unclear during low to medium speed (2 - 8 m/s) flight from a mechanical-power perspective: aerodynamic models suggest continuous flapping would require less power output and lower cost of transport. This thesis works towards the understanding of the advantages of flap-bounding and tries to employ the underlining principle to design quadrotor maneuver to improve power efficiency. To explore the functional significance of flap-bounding at low speeds, I measured body trajectory and kinematics of wings and tail of zebra finch (Taeniopygia guttata, N=2) during flights in a laboratory between two perches. The flights consist of three phases: initial, descending and ascending. Zebra finch first accelerated using continuous flapping, then descended, featuring intermittent bounds. The flight was completed by ascending using nearly-continuous flapping. When exiting bounds in descending phase, they achieved higher than pre-bound forward velocity by swinging body forward similar to pendulum motion with conserved mechanical energy. Takeoffs of black-capped chickadees (Poecile atricapillus, N=3) in the wild was recorded and I found similar kinematics. Our modeling of power output indicates finch achieves higher velocity (13%) with lower cost of transport (9%) when descending, compared with continuous flapping in previously-studied pigeons. To apply the findings to the design of quadrotor motion, a mimicking maneuver was developed that consisted of five phases: projectile drop, drop transition, pendulum swing, rise transition and projectile rise. The quadrotor outputs small amount (4 N) of thrust during projectile drop phase and ramps up the thrust while increasing body pitch angle during the drop transition phase until the thrust enables the quadrotor to advance in pendulum-like motion in the pendulum swing phase. As the quadrotor reaches the symmetric point with respect to the vertical axis of the pendulum motion, it engages in reducing the thrust and pitch angle during the rise transition phase until the thrust is lowered to the same level as the beginning of the maneuver and the body angle of attack minimized (0.2 deg) in the projectile rise phase. The trajectory of the maneuver was optimized to yield minimum cost of transport. The quadrotor moves forward by tracking the cycle of the optimized trajectory repeatedly. Due to the aggressive nature of the maneuver, we developed new algorithms using onboard sensors to determine the estimated position and attitude. By employing nonlinear controller, we showed that cost of transport of the flap-bounding inspired maneuver is lower (28%) than conventional constant forward flight, which makes it the preferable strategy in high speed flight (≥15 m/s)

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