Precise Trajectory Tracking of Multi-Rotor UAVs Using Wind Disturbance Rejection Approach

This paper discusses the resilience of the UAV quadrotor to wind disturbances. An unknown input-state observer is presented that uses the Lipschitz method to estimate the internal states and disturbances of the quadrotor and compensate for them by varying the velocities of the four rotors. The observer intends to use existing sensor measurements to estimate the unknown states of the quadrotor and reconstruct the three-dimensional wind disturbances. The estimated states and external disturbances are sent to the PD controller, which compensates for the disturbances to achieve the desired position and attitude, as well as robustness and accuracy. The Lipschitz observer was designed using the LMI approach, and the results were validated using Matlab/Simulink and using the Parrot Mambo mini quadrotor

Equilibria, Stability, and Sensitivity for the Aerial Suspended Beam Robotic System subject to Parameter Uncertainty

This work studies how parametric uncertainties affect the cooperative manipulation of a cable-suspended beam-shaped load by means of two aerial robots not explicitly communicating with each other. In particular, the work sheds light on the impact of the uncertain knowledge of the model parameters available to an established communication-less force-based controller. First, we find the closed-loop equilibrium configurations in the presence of the aforementioned uncertainties, and then we study their stability. Hence, we show the fundamental role played in the robustness of the load attitude control by the internal force induced in the manipulated object by non-vertical cables. Furthermore, we formally study the sensitivity of the attitude error to such parametric variations, and we provide a method to act on the load position error in the presence of the uncertainties. Eventually, we validate the results through an extensive set of numerical tests in a realistic simulation environment including underactuated aerial vehicles and sagging-prone cables, and through hardware experiments

Linear matrix inequality-based nonlinear adaptive robust control with application to unmanned aircraft systems

Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. ^ Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. ^ These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external disturbances such as wind gusts and turbulence. This thesis develops the ARC-LMI attitude and position controllers for an X-configuration quadrotor helicopter. The inner-loop of the autopilot controls the attitude and altitude of the quadrotor, and the outer-loop controls its position in the earth-fixed coordinate frame. Furthermore, by intelligently generating a smooth trajectory from the given reference coordinates (waypoints), the transient performance is improved. The simulation results indicate that the ARC-LMI controller design is useful for a variety of quadrotor applications, including precise trajectory tracking, autonomous waypoint navigation in the presence of disturbances, and package delivery without loss of performanc

Agile load transportation systems using aerial robots

In this dissertation, we address problems that can occur during load transport using aerial robots, i.e., small scale quadrotors. First, detailed models of such transportation system are derived. These models include nonlinear models of a quadrotor, a model of a quadrotor carrying a fixed load and a model of a quadrotor carrying a suspended load. Second, the problem of quadrotor stabilization and trajectory tracking with changes of the center of gravity of the transportation system is addressed. This problem is solved using model reference adaptive control based on output feedback linearization that compensates for dynamical changes in the center of gravity of the quadrotor. The third problem we address is a problem of a swing-free transport of suspended load using quadrotors. Flying with a suspended load can be a very challenging and sometimes hazardous task as the suspended load significantly alters the flight characteristics of the quadrotor. In order to deal with suspended load flight, we present a method based on dynamic programming which is a model based offline method. The second investigated method we use is based on the Nelder-Mead algorithm which is an optimization technique used for nonlinear unconstrained optimization problems. This method is model free and it can be used for offline or online generation of the swing-free trajectories for the suspended load. Besides the swing-free maneuvers with suspended load, load trajectory tracking is another problem we solve in this dissertation. In order to solve this problem we use a Nelder-Mead based algorithm. In addition, we use an online least square policy iteration algorithm. At the end, we propose a high level algorithm for navigation in cluttered environments considering a quadrotor with suspended load. Furthermore, distributed control of multiple quadrotors with suspended load is addressed too. The proposed hierarchical architecture presented in this doctoral dissertation is an important step towards developing the next generation of agile autonomous aerial vehicles. These control algorithms enable quadrotors to display agile maneuvers while reconfiguring in real time whenever a change in the center of gravity occurs. This enables a swing-free load transport or trajectory tracking of the load in urban environments in a decentralized fashion

Synchronization of multiple rigid body systems: a survey

The multi-agent system has been a hot topic in the past few decades owing to its lower cost, higher robustness, and higher flexibility. As a particular multi-agent system, the multiple rigid body system received a growing interest since its wide applications in transportation, aerospace, and ocean exploration. Due to the non-Euclidean configuration space of attitudes and the inherent nonlinearity of the dynamics of rigid body systems, synchronization of multiple rigid body systems is quite challenging. This paper aims to present an overview of the recent progress in synchronization of multiple rigid body systems from the view of two fundamental problems. The first problem focuses on attitude synchronization, while the second one focuses on cooperative motion control in that rotation and translation dynamics are coupled. Finally, a summary and future directions are given in the conclusion

Practical tracking control for stochastic nonlinear systems with polynomial function growth conditions

This paper mainly focuses on an output feedback practical tracking controller design for a class of stochastic nonlinear systems with polynomial function growth conditions. Mostly, there are some studies on an output feedback tracking control problem for general nonlinear systems with polynomial function growth conditions in existing achievements. Moreover, we extend it to stochastic nonlinear systems and construct an output feedback practical tracking controller based on dynamic and static phase combined, ensuring that all the states of the stochastic nonlinear system are bounded and the system tracking error can be made arbitrarily small after some large enough time. Finally, a simulation example is provided to illustrate the efficiency of the theoretical results

Neural network control design for an unmanned aerial vehicle with a suspended payload

Unmanned aerial vehicles (UAVs) demonstrate excellent manoeuvrability in cluttered environments, which makes them a suitable platform as a data collection and parcel delivering system. In this work, the attitude and position control challenges for a drone with a package connected by a wire is analysed. During the delivering task, it is very difficult to eliminate the external unpredictable disturbances. A robust neural network-based backstepping sliding mode control method is designed, which is capable of monitoring the drone's flight path and desired attitude with a suspended cable attached. The convergence of the position and attitude errors together with the Lyapunov function are employed to attest to the robustness of the nonlinear transportation platform. The proposed control system is tested with a simulation and in an outdoor environment. The simulation and open field test results for the UAV transportation platform verify the controllers' reliability