Design, Development and Implementation of Intelligent Algorithms to Increase Autonomy of Quadrotor Unmanned Missions

This thesis presents the development and implementation of intelligent algorithms to increase autonomy of unmanned missions for quadrotor type UAVs. A six-degree-of freedom dynamic model of a quadrotor is developed in Matlab/Simulink in order to support the design of control algorithms previous to real-time implementation. A dynamic inversion based control architecture is developed to minimize nonlinearities and improve robustness when the system is driven outside bounds of nominal design. The design and the implementation of the control laws are described. An immunity-based architecture is introduced for monitoring quadrotor health and its capabilities for detecting abnormal conditions are successfully demonstrated through flight testing. A vision-based navigation scheme is developed to enhance the quadrotor autonomy under GPS denied environments. An optical flow sensor and a laser range finder are used within an Extended Kalman Filter for position estimation and its estimation performance is analyzed by comparing against measurements from a GPS module. Flight testing results are presented where the performances are analyzed, showing a substantial increase of controllability and tracking when the developed algorithms are used under dynamically changing environments. Healthy flights, flights with failures, flight with GPS-denied navigation and post-failure recovery are presented

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

Development of Robust Control Laws for Disturbance Rejection in Rotorcraft UAVs

Inherent stability inside the flight envelope must be guaranteed in order to safely introduce private and commercial UAV systems into the national airspace. The rejection of unknown external wind disturbances offers a challenging task due to the limited available information about the unpredictable and turbulent characteristics of the wind. This thesis focuses on the design, development and implementation of robust control algorithms for disturbance rejection in rotorcraft UAVs. The main focus is the rejection of external disturbances caused by wind influences. Four control algorithms are developed in an effort to mitigate wind effects: baseline nonlinear dynamic inversion (NLDI), a wind rejection extension for the NLDI, NLDI with adaptive artificial neural networks (ANN) augmentation, and NLDI with L1 adaptive control augmentation. A simulation environment is applied to evaluate the performance of these control algorithms under external wind conditions using a Monte Carlo analysis. Outdoor flight test results are presented for the implementation of the baseline NLDI, NLDI augmented with adaptive ANN and NLDI augmented with L1 adaptive control algorithms in a DJI F330 Flamewheel quadrotor UAV system. A set of metrics is applied to compare and evaluate the overall performance of the developed control algorithms under external wind disturbances. The obtained results show that the extended NLDI exhibits undesired characteristics while the augmentation of the baseline NLDI control law with adaptive ANN and L1 output-feedback adaptive control improve the robustness of the translational and rotational dynamics of a rotorcraft UAV in the presence of wind disturbances

Stochastic Real-time Optimal Control for Bearing-only Trajectory Planning

A method is presented to simultaneously solve the optimal control problem and the optimal estimation problem for a bearing-only sensor. For bearing-only systems that require a minimum level of certainty in position relative to a source for mission accomplishment, some amount of maneuver is required to measure range. Traditional methods of trajectory optimization and optimal estimation minimize an information metric. This paper proposes constraining the final value of the information states with known time propagation dynamics relative to a given trajectory which allows for attainment of the required level of information with minimal deviation from a general performance index that can be tailored to a specific vehicle. The proposed method does not suffer from compression of the information metric into a scalar, and provides a route that will attain a particular target estimate quality while maneuvering to a desired relative point or set. An algorithm is created to apply the method in real-time, iteratively estimating target position with an Unscented Kalman Filter and updating the trajectory with an efficient pseudospectral method. Methods and tools required for hardware implementation are presented that apply to any real-time optimal control (RTOC) system. The algorithm is validated with both simulation and flight test, autonomously landing a quadrotor on a wire

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)

Towards autonomy of a quadrotor UAV

As the potential of unmanned aerial vehicles rapidly increases, there is a growing interest in rotary vehicles as well as fixed wing. The quadrotor is small agile rotary vehicle controlled by variable speed prop rotors. With no need for a swash plate the vehicle is low cost as well as dynamically simple. In order to achieve autonomous flight, any potential control algorithm must include trajectory generation and trajectory following. Trajectory generation can be done using direct or indirect methods. Indirect methods provide an optimal solution but are hard to solve for anything other than the simplest of cases. Direct methods in comparison are often sub-optimal but can be applied to a wider range of problems. Trajectory optimization is typically performed within the control space, however, by posing the problem in the output space, the problem can be simplified. Differential flatness is a property of some dynamical systems which allows dynamic inversion and hence, output space optimization. Trajectory following can be achieved through any number of linear control techniques, this is demonstrated whereby a single trajectory is followed using LQR, this scheme is limited however, as the vehicle is unable to adapt to environmental changes. Model based predictive control guarantees constraint satisfaction at every time step, this however is time consuming and therefore, a combined controller is proposed benefiting from the adaptable nature of MBPC and the robustness and simplicity of LQR control. There are numerous direct methods for trajectory optimization both in the output and control space. Taranenko’s direct method has a number of benefits over other techniques, including the use of a virtual argument, which separates the optimal path and the speed problem. This enables the algorithm to solve the optimal time problem, the optimal fuel problem or a combination of the two, without a deviation from the optimal path. In order to implement such a control scheme, the issues of feedback, communication and control action computation, require consideration. This work discusses the issues with instrumentation and communication encountered when developing the control system and provides open loop test results. This work also extends the proposed control schemes to consider the problem of multiple vehicle flight rendezvous. Specifically the problem of rendezvous when there is no communication link, limited visibility and no agreed rendezvous point. Using Taranenko’s direct method multiple vehicle rendezvous is simulated.EThOS - Electronic Theses Online ServiceGBUnited Kingdo