Nonlinear Dynamics and Control of Aerial Robots

Aerial robotics is one of the fastest growing industry and has a number of evolving applications. Higher agility make aerial robots ideal candidate for applications like rescue missions especially in difficult to access areas. This chapter first derives the complete nonlinear dynamics of an aerial robot consisting of a quadcopter with a two-link robot manipulator. Precise control of such an aerial robot is a challenging task due to the fact that the translational and rotational dynamics of the quadcopter are strongly coupled with the dynamics of the manipulator. We extend our previous results on the control of quadrotor UAVs to the control of aerial robots. In particular, we design a backstepping and Lyapunov-based nonlinear feedback control law that achieves point-to-point control of the areal robot. The effectiveness of this feedback control law is illustrated through a simulation example

Adaptive control of nonlinear system based on QFT application to 3-DOF flight control system

Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research UAV, because of its high load carrying capacity with a smaller number of motor and requirement of forethought motor control dynamics. Various control algorithms are investigated and designed for the motion control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover, manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper, we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT) controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S. Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on structured uncertainties associated with controller for the flight conditions theoretically. The development of simulationbased design on flight control system response, opened a new dimension for researcher to design physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid controller that is QFT based adaptive controller for all the three angles

CONTROL STRATEGY OF MULTIROTOR PLATFORM UNDER NOMINAL AND FAULT CONDITIONS USING A DUAL-LOOP CONTROL SCHEME USED FOR EARTH-BASED SPACECRAFT CONTROL TESTING

Over the last decade, autonomous Unmanned Aerial Vehicles (UAVs) have seen increased usage in industrial, defense, research, and academic applications. Specific attention is given to multirotor platforms due to their high maneuverability, utility, and accessibility. As such, multirotors are often utilized in a variety of operating conditions such as populated areas, hazardous environments, inclement weather, etc. In this study, the effectiveness of multirotor platforms, specifically quadrotors, to behave as Earth-based satellite test platforms is discussed. Additionally, due to concerns over system operations under such circumstances, it becomes critical that multirotors are capable of operation despite experiencing undesired conditions and collisions which make the platform susceptible to on-board hardware faults. Without countermeasures to account for such faults, specifically actuator faults, a multirotors will experience catastrophic failure. In this thesis, a control strategy for a quadrotor under nominal and fault conditions is proposed. The process of defining the quadrotor dynamic model is discussed in detail. A dual-loop SMC/PID control scheme is proposed to control the attitude and position states of the nominal system. Actuator faults on-board the quadrotor are interpreted as motor performance losses, specifically loss in rotor speeds. To control a faulty system, an additive control scheme is implemented in conjunction with the nominal scheme. The quadrotor platform is developed via analysis of the various subcomponents. In addition, various physical parameters of the quadrotor are determined experimentally. Simulated and experimental testing showed promising results, and provide encouragement for further refinement in the future

Robust Control of Vectored Thrust Aerial Vehicles via Variable Structure Control Methods

The popularity of Unmanned Aerial Vehicles (UAVs) has grown rapidly in many civil and military applications in the last few decades. Recent UAV applications include crop monitoring, terrain mapping and aerial photography, where one or several image sensors attached to the UAV provide important terrain information. A thrust vectoring aerial vehicle, a vehicle with the ability to change the direction of thrust generated while keeping the UAV body at a zero roll and pitch orientation, can serve well in such applications by allowing the sensors to capture stable image data without additional gimbals, reducing the payload and cost while increasing the flight endurance. Furthermore, thrust vectoring UAVs can perform fast forward flight as well as hover operations with non-zero pitch: features which can serve well in military applications. The first part of this research focuses on developing a comprehensive dynamic model and a low level attitude and position control structure for a tri-rotor UAV with thrust vectoring capability, namely the Vectored Thrust Aerial Vehicle. Nonlinear dynamics of UAVs require robust control methods to realize stable flight. Special attention needs to be given to wind gust disturbances, and parametric uncertainties. Sliding Mode Control , a type of Variable Structure Controller, has served well over the years in controlling UAVs and other dynamic systems. However, conventional Sliding Mode Control results in a high frequency switching behavior of the control signal. Furthermore, Sliding Mode Control does not focus on fast set-point regulation or tracking, which can be advantageous for UAVs and many other robotic systems. Taking these research gaps into account, this work presents an Adaptive Variable Structure Control method, which can acquire fast set-point regulation while maintaining robustness against external disturbances and uncertainties. The adaptive algorithm developed in this work is fundamentally different from current Adaptive Sliding Mode Control and other Variable Structure methods. Simulation and experimental results are provided to demonstrate the superiority of the proposed approach compared to Sliding Mode Control. The novel adaptive algorithm is applicable to many nonlinear dynamic systems including UAVs, robot arm manipulators and space robots. The same adaptive concept is then utilized to develop an Adaptive Second Order Sliding Mode Controller. Compared to existing Second Order Sliding Mode Control methods, the proposed methodology is able to produce reduced sliding manifold reach times and consume less amount of control resources: features which are particularly advantageous for systems with limited control resources. Simulations are conducted to evaluate the performance of the proposed Adaptive Second Order Sliding Mode Control algorithm

Vision-Based Autonomous Control Schemes for Quadrotor Unmanned Aerial Vehicle

This chapter deals with the development of vision-based sliding mode control strategies for a quadrotor system that would enable it to perform autonomous tasks such as take-off, landing and visual inspection of structures. The aim of this work is to provide a basic understanding of the quadrotor dynamical model, key concepts in image processing and a detailed description of the sliding mode control, a widely used robust non-linear control scheme. Extensive MATLAB simulations are presented to enhance the understanding of the controller on the quadrotor system subjected to bounded disturbances and uncertainties. The vision algorithms developed in this chapter would provide the necessary reference trajectory to the controller enabling it to exercise control over the system. This work also describes, in brief, the implementation of the developed control and vision algorithms on the DJI Matrice 100 to present real-time experimental data to the readers of this chapter