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

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Adaptive backstepping controller design of quadrotor biplane for payload delivery

Performance of the UAVs for a particular application can be enhanced by hybrid design, where take-off, hover, and landing happen like rotary-wing UAVs, and flies like fixed-wing UAVs. A backstepping controller and an adaptive backstepping controller are designed for trajectory tracking and payload delivery in a medical emergency or medical substance delivery like vaccine delivery in the presence of wind gust. Simulation results show that the backstepping controller effectively tracks the trajectory during the entire flight envelope, including take-off, hovering, the transition phase, level flight mode, and landing. A comparison between Backstepping, Integral Terminal Sliding Mode (ITSMC) and Adaptive Backstepping controllers for payload delivery show that the adaptive backstepping controller effectively tracks the altitude and attitude. ITSMC is capable of tracking the desired trajectory for a change in the mass but has sluggish response. The backstepping controller generates a steady-state error in altitude during the mass change in biplane-quadrotor.The publication of this article was funded by Qatar National Library.Scopu

Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types of missions they can accomplish autonomously. This paper proposes a deep reinforcement learning (DRL) controller to handle the nonlinear attitude control problem, enabling extended flight envelopes for fixed-wing UAVs. A proof-of-concept controller using the proximal policy optimization (PPO) algorithm is developed, and is shown to be capable of stabilizing a fixed-wing UAV from a large set of initial conditions to reference roll, pitch and airspeed values. The training process is outlined and key factors for its progression rate are considered, with the most important factor found to be limiting the number of variables in the observation vector, and including values for several previous time steps for these variables. The trained reinforcement learning (RL) controller is compared to a proportional-integral-derivative (PID) controller, and is found to converge in more cases than the PID controller, with comparable performance. Furthermore, the RL controller is shown to generalize well to unseen disturbances in the form of wind and turbulence, even in severe disturbance conditions.Comment: 11 pages, 3 figures, 2019 International Conference on Unmanned Aircraft Systems (ICUAS

Lyapunov-based fault tolerant control of quadrotor unmanned aerial vehicles

This thesis presents the theoretical development, simulation study and flight tests of a Lyapunov-based control approach for the Fault Tolerant Control (FTC) of a quadrotor unmanned aerial vehicle (UAV). Based on the derivation of nonlinear model of the dynamics of the quadrotor UAV, a Lyapunov-based control approach with fixed controller gains is proposed and firstly demonstrated through simulations of the quadrotor UAV for handling system parameter uncertainties. Secondly, this proposed Lyapunov-based approach with the selected controller gains is applied as a fault tolerant controller in the framework of a passive Fault Tolerant Control System (FTCS), for handling less severe faults occurring in the quadrotor UAV. Thirdly, the proposed new controller by Lyapunov-based adaptive control method for fault tolerant control of the quadrotor UAV is proposed to handle more severe faults. Finally, the Lyapunov-based control method has been implemented to the test bed, Qball-X4 Unmanned Aerial Vehicle, and the acceptable performances on altitude control have been achieved. In the thesis, simulation and flight testing results demonstrate that the FTCS with the Lyapunov-based approach has certain robustness for most of partial losses. However, the FTCS with Lyapunov-based adaptive control approach has advantages in accommodating more severe faults for, which may not be addressed by the Lyapunov-based approac

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

Fractional Order Fault Tolerant Control - A Survey

In this paper, a comprehensive review of recent advances and trends regarding Fractional Order Fault Tolerant Control (FOFTC) design is presented. This novel robust control approach has been emerging in the last decade and is still gathering great research efforts mainly because of its promising results and outcomes. The purpose of this study is to provide a useful overview for researchers interested in developing this interesting solution for plants that are subject to faults and disturbances with an obligation for a maintained performance level. Throughout the paper, the various works related to FOFTC in literature are categorized first by considering their research objective between fault detection with diagnosis and fault tolerance with accommodation, and second by considering the nature of the studied plants depending on whether they are modelized by integer order or fractional order models. One of the main drawbacks of these approaches lies in the increase in complexity associated with introducing the fractional operators, their approximation and especially during the stability analysis. A discussion on the main disadvantages and challenges that face this novel fractional order robust control research field is given in conjunction with motivations for its future development. This study provides a simulation example for the application of a FOFTC against actuator faults in a Boeing 747 civil transport aircraft is provided to illustrate the efficiency of such robust control strategies

Two-layer adaptive augmentation for incremental backstepping flight control of transport aircraft in uncertain conditions

Presence of uncertainties caused by unforeseen malfunctions in actuation system or changes in aircraft behaviour could lead to aircraft loss-of-control during flight. The paper presents Two-Layer Adaptive augmentation for Incremental Backstepping (TLA-IBKS) control algorithm designed for a large transport aircraft. IBKS uses angular accelerations and current control deflections to reduce the dependency on the aircraft model. However, it requires knowledge of control effectiveness. The proposed technique is capable to detect possible failures for an overactuated system. At the first layer, the system performs monitoring of a combined effectiveness and detects possible failures via an innovation process. If a problem is detected the algorithm initiates the second-layer algorithm for adaptation of effectiveness of individual control effectors. Filippov generalization for nonlinear differential equations with discontinuous right-hand sides is utilized to develop Lyapunov based tuning function adaptive law for the second layer adaptation and to prove uniform asymptotic stability of the resultant closed-loop system. Conducted simulation manifests that if the input-affine property of the IBKS is violated, e.g., in severe conditions with a combination of multiple failures, the IBKS can lose stability. Meanwhile, the proposed TLA-IBKS algorithm demonstrates improved stability and tracking performance