Coordination Control of Quadrotor VTOL Aircraft in Three-Dimensional Space

This paper presents a constructive design of distributed coordination controllers for a group of N quadrotor vertical take-off and landing (VTOL) aircraft in three-dimensional space. A combination of Euler angles and unit-quaternion for the attitude representation of the aircraft is used to result in an effective control design, and to reduce singularities in the aircraft’s dynamics. The coordination control design is based on a new bounded control design technique for second-order systems and new pairwise collision avoidance functions. The pairwise collision functions are functions of both relative positions and relative velocities between the aircraft instead of only their relative positions as in the literature. To overcome the inherent underactuation of the aircraft, the roll and pitch angles of the aircraft are considered as immediate controls. Simulations illustrate the results

Tracking Control of Quadrotors

In this thesis, the tracking control problem of a 6 DOF quadrotor is considered, and different control method is proposed considering optimal control, parametric and nonparametric uncertainty, input saturation, and distributed formation control. An optimal control approach is developed for single quadrotor tracking by minimizing the cost function. For uncertainties of the dynamic system, a robust adaptive tracking controller is proposed with the special structure of the dynamics of the system. Considering the uncertainty and input constraints, a robust adaptive saturation controller is proposed with the aid of an auxiliary compensated system. Decentralized formation control method for quadrotors is presented using a leader-follower scheme using proposed optimal control method. Virtual leader is employed to drive the quadrotors to their desired formation and ultimately track the trajectory defined by the virtual leader. Sliding mode estimators have been implemented to estimate the states of the virtual leader. The control method is designed considering switching communication topologies among the quadrotors. Simulation results are provided to show the effectiveness of the proposed approaches

Sensitivity analysis of a relative navigation solution for unmanned aerial vehicles in a GNSS-denied environment

Cooperative navigation between two or more unmanned aerial vehicles (UAVs) is an important enabling technology for problems such as military reconnaissance, disaster response, and search and rescue. In many of these situations Global Navigation Satellite Systems (GNSS), such as Global Positioning System (GPS), may be unreliable or unavailable due to structural impedance or malicious signal jamming. Therefore, the task of maintaining a reliable relative navigation solution without the use of GNSS is an important need for the aforementioned missions.;To meet this need, this thesis focuses on the relative navigation between two UAVs that are operating in a GNSS-denied environment. In particular, the design and sensitivity of a navigation algorithm are presented. The navigation algorithm presented consists of an Unscented Kalman filter that fuses multiple on-board sensors to estimate the relative pose between two UAVs. These sensors include: strap-down inertial measurement units, ultra-wideband ranging radios, strap-down tri-axial magnetometers, and downward facing cameras. Through the use of a Monte Carlo simulation study, the presented algorithm\u27s performance sensitivity to various sensor payload characteristics, flight dynamics, and initial condition errors is evaluated. Additionally, a research platform that will provide for a future experimental evaluation of the algorithm presented in this thesis has been integrated and tested as part of this work

Event-based control strategy for consensus of a group of VTOL-UAVs

International audienceThis paper presents the development of a collaborative event-based control applied to the problem of consensus and formation of a group of VTOL-UAVs (Vertical Takeoff and Landing, Unmanned Aerial Vehicles). Each VTOL-UAV decides, based on the difference of its current state (linear position and velocity) and its latest broadcast state, when it has to send a new value to its neighbors. The asymptotic convergence to average consensus or desired formation is depicted via numerical simulations

Concept and Feasibility Evaluation of Distributed Sensor-Based Measurement Systems Using Formation Flying Multicopters

Unmanned aerial vehicles (UAVs) have been used for increasing research applications in atmospheric measurements. However, most current solutions for these applications are based on a single UAV with limited payload capacity. In order to address the limitations of the single UAV-based approach, this paper proposes a new concept of measurements using tandem flying multicopters as a distributed sensor platform. Key challenges of the proposed concept are identified including the relative position estimation and control in wind-perturbed outdoor environment and the precise alignment of payloads. In the proposed concept, sliding mode control is chosen as the relative position controller and a gimbal stabilization system is introduced to achieve fine payload alignment. The characterization of the position estimation sensors (including global navigation satellite system and real-time kinematics) and flight controller is carried out using different UAVs (a DJI Matrice M600 Pro Hexacopter and Tarot X4 frame based Quadcopter) under different wind levels. Based on the experimental data, the performance of the sliding mode controller and the performance of the gimbal stabilization system are evaluated in a hardware-in-the-loop simulation environment (called ELISSA). Preliminary achievable control accuracies of the relative position and attitude of subsystems in the proposed concept are estimated based on experimental result

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

Adaptive non-Linear Model Predictive Control for UAV-UGV Coordination

Unmanned Aerial Vehicles (UAV) have gained a great amount of popularity in the last years. Among the features that make them so successful are the cost, the portability, their airborne nature and their ability to perform Vertical Take-Off and Landing (VTOL). Since the different tasks that UAVs are given may require them to travel long distances, the small batteries that they are using can prove to be a problem if they have to return to the home-base to recharge. A solution can be sending a Unmanned Ground Vehicle (UGV) along with the UAVs, since they can have a much longer autonomy and provide a moving base. In particular this thesis wants to improve the landing manoeuvre in such a way that the landing will be smooth and most accurate. The first part of this work is dedicated the implementation of the Non-linear Model Predictive Control (NMPC) as the baseline controller. This controller creates an optimal control that minimizes a given cost function along the chosen prediction horizon, while respecting the model constraints. For this work the non-linear version of the algorithm was chosen given the non-linearity of the model of the UAV in question, i.e. the quadrotor. One of the main features of this controller is the dependency on the internal model of the system, which gives it its name. In the second part another complementary controller is added to the NMPC. Adaptive control is meant to deal with varying or unknown model parameters and for this reason L 1 Adaptive Control (L1AC) was chosen for the task. L1AC is a slight variation of the Model Reference Adaptive Control (MRAC), which tries to deal with errors at the input level, setting a new input counterpart to negate them. The combination of the two controllers is meant to exploit each other’s strength, while helping with the other’s weakness, to create an overall stable and well performing algorithm that allows to account for the kinematics and dynamics of the quadrotor, while being extremely robust against the potential errors of the internal model or external disturbances. The proposed method is then tested in various scenarios and validated through results on Matlab & Simulink

Distributed path planning for controlling a fleet of UAVs : application to a team of quadrotors

International audienc

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