Path following of an underactuated AUV based on fuzzy backstepping sliding mode control

This paper addresses the path following problem of an underactuated autonomous underwater vehicle (AUV) with the aim of dealing with parameter uncertainties and current disturbances. An adaptive robust control system was proposed by employing fuzzy logic, backstepping and sliding mode control theory. Fuzzy logic theory is adopted to approximate unknown system function, and the controller was designed by combining sliding mode control with backstepping thought. Firstly, the longitudinal speed was controlled, then the yaw angle was made as input of path following error to design the calm function and the change rate of path parameters. The controller stability was proved by Lyapunov stable theory. Simulation and outfield tests were conducted and the results showed that the controller is of excellent adaptability and robustness in the presence of parameter uncertainties and external disturbances. It is also shown to be able to avoid the chattering of AUV actuator

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The control strategy uses sliding mode with a backstepping control to perform the position and attitude tracking control. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed control strategy for the quadrotor UAV

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

Instrumentation and control of a target fixed-wing drone for launch and capture

This work was developed within the scope of the CAPTURE project, in which a collaborative network was intended to be built in which a quadcopter drone would help a fixed-wing drone perform landing and takeoff maneuvers. The study of small fixed-wing unmanned aerial vehicles (UAVs) were presented, as well as their attitude control, instrumentation, and trajectory tracking. One of the goals of this dissertation was to model a real vehicle, specifically the Easy Glider 4. All the work was developed based on this vehicle, for which it was necessary to use the XFLR software to obtain its aerodynamic response and thus obtain a more accurate model and, consequently, its control. The main challenges of this dissertation were related to obtaining the full dynamic model (with the aerodynamic coefficients included), the control techniques that would be used to deal with their nonlinearities, and their integration with a path following algorithm. Two types of attitude controllers were developed: a linear controller based on PI and a nonlinear controller based on the backstepping technique. An external loop was then added to make the UAV follow a specific path. Two different techniques were implemented: a path following algorithm that would make the vehicle follow a vector field around the intended trajectory and an adaptive algorithm capable of dealing with uncertainties in the environment, such as wind with unknown direction and intensity.Este trabalho é desenvolvido no âmbito do projecto CAPTURE , em que se pretende construir uma rede colaborativa em que um drone quadricóptero ajude um drone de asa fixa a realizar manobras de aterragem e descolagem. Será apresentado o estudo e modelação de pequenos veículos não tripulados de asa fixa (UAV), bem como o seu controlo de atitude, instrumentação e seguimento de trajetória. Um dos objectivos desta dissertação é a modelação de um veículo real, mais especificamente o Easy glider 4. Todo o trabalho será desenvolvido com base neste veículo, para isso, é necessário utilizar o software XFLR para obter sua resposta aerodinâmica e assim obter uma modelação mais precisa e, consequentemente, o seu controlo. Devido à complexidade da dinâmica do UAV, os principais desafios desta dissertação estão relacionados com a obtenção do modelo dinâmico, às técnicas de controlo que serão utilizadas para lidar com suas não linearidades e a sua integração com um algoritmo de path following. Serão desenvolvidos dois tipos de controladores de atitude: Um controlador linear baseado no PID e um controlador não linear baseado na técnica de backstepping. Um loop externo é então adicionado para que o UAV siga um determinado caminho. Serão implementadas duas ténicas diferentes: Um algoritmo de path following que fará o veículo seguir um campo vectorial em volta da trajetória pretendida e um algoritmo adaptativo capaz de lidar com incertezas do meio ambiente, tais como vento com direção e amplitude desconhecidas

Multi-mode Flight Sliding Mode Control System for a Quadrotor

There is a wide range of applications for unmanned aerial vehicles that requires the capability of having several and robust flight controllers available. This paper presents the main framework of a multimode flight control system for a quadrotor based on the super twisting control algorithm. The design stages for the four flight control modes encompassing manual, altitude, GPS fixed and autonomous mode are presented. The stability proof for each flight mode is carried out by means of Lyapunov functions while the stability analysis for the complete system, when a transition from one mode to another occurs, is demonstrated using the switching nonlinear systems theory. The performance of the proposed framework is demonstrated in a simulation study taking into account external disturbances

Nonlinear Backstepping Control Design for Coupled Nonlinear Systems under External Disturbances

A nonlinear backstepping control is proposed for the coupled normal form of nonlinear systems. The proposed method is designed by combining the sliding-mode control and backstepping control with a disturbance observer (DOB). The key idea behind the proposed method is that the linear terms of state variables of the second subsystem are lumped into the virtual input in the first subsystem. A DOB is developed to estimate the external disturbances. Auxiliary state variables are used to avoid amplification of the measurement noise in the DOB. For output tracking and unmatched disturbance cancellation in the first subsystem, the desired virtual input is derived via the backstepping procedure. The actual input in the second subsystem is developed to guarantee the convergence of the virtual input to the desired virtual input by using a sliding-mode control. The stability of the closed-loop is verified by using the input-to-state stable (ISS) property. The performance of the proposed method is validated via numerical simulations and an application to a vehicle system based on CarSim platform.This research was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education under Grant NRF-2016R1C1B1014831 and the Research Program, Development of High Voltage Brake System for Response to Safety Regulations of Micro eMobility (20003066), funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea)

Dynamic modeling and control of a Quadrotor using linear and nonlinear approaches

With the huge advancements in miniature sensors, actuators and processors depending mainly on the Micro and Nano-Electro-Mechanical-Systems (MEMS/NEMS), many researches are now focusing on developing miniature flying vehicles to be used in both research and commercial applications. This thesis work presents a detailed mathematical model for a Vertical Takeo ff and Landing (VTOL) type Unmanned Aerial Vehicle(UAV) known as the quadrotor. The nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method, the formulated model is detailed including aerodynamic effects and rotor dynamics that are omitted in many literature. The motion of the quadrotor can be divided into two subsystems; a rotational subsystem (attitude and heading) and a translational subsystem (altitude and x and y motion). Although the quadrotor is a 6 DOF underactuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is underactuated. The derivation of the mathematical model is followed by the development of four control approaches to control the altitude, attitude, heading and position of the quadrotor in space. The fi rst approach is based on the linear Proportional-Derivative-Integral (PID) controller. The second control approach is based on the nonlinear Sliding Mode Controller (SMC). The third developed controller is a nonlinear Backstepping controller while the fourth is a Gain Scheduling based PID controller. The parameters and gains of the forementioned controllers were tuned using Genetic Algorithm (GA) technique to improve the systems dynamic response. Simulation based experiments were conducted to evaluate and compare the performance of the four developed control techniques in terms of dynamic performance, stability and the effect of possible disturbances

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