Adaptive sliding-mode-backstepping trajectory tracking control of underactuated airships

The problem of trajectory tracking control for an underactuated stratospheric airship with model parameter uncertainties and wind disturbances is addressed in the paper. An adaptive backstepping sliding-mode controller is designed from the airship nonlinear dynamics model. The proposed controller has a two-level structure for trajectory guidance, tracking and stability, and the developed controller, based on nonlinear adaptive sliding-mode backstepping method, provides airship attitude and velocity control for the entire flight process. Furthermore, an active set based weighted least square algorithm is applied to find the optimal control surface inputs and the thruster commands under constraints of actuator saturation. The closed-loop system of trajectory tracking control plant is proved to be globally asymptotically stable by using Lyapunov theory. By comparing with traditional backstepping control and PID design, the results obtained demonstrate the capacity of the airship to execute a realistic trajectory tracking mission under two cases of lateral- and roll- underactuations, even in the presence of aerodynamic coefficient uncertainties, and wind disturbances

Backstepping sliding-mode control of stratospheric airships using disturbance-observer

In the presence of unknown disturbances and model parameter uncertainties, this paper develop a nonlinear backstepping sliding-mode controller (BSMC) for trajectory tracking control of a stratospheric airship using a disturbance-observer (DO). Compared with the conventional sliding mode surface (SMS) constructed by a linear combination of the errors, the new SMS manifold is selected as the last back-step error to improve independence of the adjustment of the controller gains. Furthermore, a nonlinear disturbance-observer is designed to process unknown disturbance inputs and improve the BSMC performances. The closed-loop system of trajectory tracking control plant is proved to be globally asymptotically stable by using Lyapunov theory. By comparing with traditional backstepping control and SMC design, the results obtained demonstrate the capacity of the airship to execute a realistic trajectory tracking mission, even in the presence of unknown disturbances, and aerodynamic coefficient uncertaintie

Multi-Layered Optimal Navigation System For Quadrotors UAV

Purpose This paper aims to propose a new multi-layered optimal navigation system that jointly optimizes the energy consumption, improves the robustness and raises the performance of a quadrotor unmanned aerial vehicle (UAV). Design/methodology/approach The proposed system is designed as a multi-layered system. First, the control architecture layer links the input and the output spaces via quaternion-based differential flatness equations. Then, the trajectory generation layer determines the optimal reference path and avoids obstacles to secure the UAV from collisions. Finally, the control layer allows the quadrotor to track the generated path and guarantees the stability using a double loop non-linear optimal backstepping controller (OBS). Findings All the obtained results are confirmed using several scenarios in different situations to prove the accuracy, energy optimization and the robustness of the designed system. Practical implications The proposed controllers are easily implementable on-board and are computationally efficient. Originality/value The originality of this research is the design of a multi-layered optimal navigation system for quadrotor UAV. The proposed control architecture presents a direct relation between the states and their derivatives, which then simplifies the trajectory generation problem. Furthermore, the derived differentially flat equations allow optimization to occur within the output space as opposed to the control space. This is beneficial because constraints such as obstacle avoidance occur in the output space; hence, the computation time for constraint handling is reduced. For the OBS, the novelty is that all controller parameters are derived using the multi-objective genetic algorithm (MO-GA) that optimizes all the quadrotor state’s cost functions jointly

Design of Flight Control Laws for a Novel Stratospheric Dual-Aircraft Platform

Dual-aircraft platform (DAP) is a novel concept that features two glider-like unmanned aerial systems (UAS) tethered via a thin adjustable cable allowing them to sail back-and-forth, without propulsion, using vertical wind shear. DAP offers the potential of a low-cost atmospheric satellite. This thesis presents the results of an initiative to demonstrate this novel flight concept through modeling, simulation, and flight testing at Embry-Riddle Aeronautical University (ERAU). A realistic simulation environment, described herein, was developed to support the development and testing of flight control systems. This environment includes nonlinear aerodynamic models for the aircraft, a multi-element cable dynamics model, propeller-motor thrust model, control surface actuator models, and permits time-varying wind profiles. This simulator offers both pilot-in-the-loop control and autonomous sailing flight control, and X-Plane interface to provide visualization cues. An intensive flight test program, described herein, was conducted to support the validation of the DAP concept. MAXA Pro 4m gliders were assembled, instrumented, and flight tested in an effort to physically demonstrate the sailing mode of flight. The flight test program described here focuses on the capability to sail with one aircraft (i.e., fly without propulsion) while towing (i.e., pulling) a moving truck as an intermediate step towards the more complex scenario of sailing with two connected aircraft. Two vital elements of the flight software are implemented and analyzed herein. The accuracy of wind estimation techniques is evaluated using flight testing. The robustness of an L1 adaptive controller is evaluated within the flight simulation environment by comparing its performance with a conventional controller

Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

Trajectory tracking is a critical element for the better functionality of autonomous vehicles. The main objective of this research study was to implement and analyze L1 adaptive control laws for autonomous flight under normal and upset flight conditions. The West Virginia University (WVU) Unmanned Aerial Vehicle flight simulation environment was used for this purpose. A comparison study between the L1 adaptive controller and a baseline conventional controller, which relies on position, proportional, and integral compensation, has been performed for a reduced size jet aircraft, the WVU YF-22. Special attention was given to the performance of the proposed control laws in the presence of abnormal conditions. The abnormal conditions considered are locked actuators (stabilator, aileron, and rudder) and excessive turbulence. Several levels of abnormal condition severity have been considered. The performance of the control laws was assessed over different-shape commanded trajectories. A set of comprehensive evaluation metrics was defined and used to analyze the performance of autonomous flight control laws in terms of control activity and trajectory tracking errors. The developed L1 adaptive control laws are supported by theoretical stability guarantees. The simulation results show that L1 adaptive output feedback controller achieves better trajectory tracking with lower level of control actuation as compared to the baseline linear controller under nominal and abnormal conditions