Aggressive landing maneuvers for UAVs

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.Includes bibliographical references (p. 69-70).VTOL (Vertical Take Off and Landing) vehicle landing is considered to be a critically difficult task for both land, marine, and urban operations. This thesis describes one possible control approach to enable landing of unmanned aircraft systems at all attitudes, including against walls and ceilings as a way to considerably enhance the operational capability of these vehicles. The features of the research include a novel approach to trajectory tracking, whereby the primary system outputs to be tracked are smoothly scheduled according to the state of the vehicle relative to its landing area. The proposed approach is illustrated with several experiments using a low-cost three-degree-of-freedom helicopter. We also include the design details of a testbed for the demonstration of the application of our research endeavor. The testbed is a model helicopter UAV platform that has indoor and outdoor aggressive flight capability.by Selcuk Bayraktar.S.M

Kite Generator System Periodic Motion Planning Via Virtual Constraints

International audienceThis paper presents a new control strategy for Kite Generator System (KGS). The proposed feedback strategy is based on motion planning using the virtual constraint approach and ensures exponential orbital stability of the desired trajectory. The strategy is detailed, applied and tested via numerical simulations and showed good convergence to a desired periodic motion

Unified Dynamics and Control of a Robot Manipulator Mounted on a VTOL Aircraft Platform

An innovative type of mobile manipulator, designated Manipulator on VTOL (Vertical Take-Off and Landing) Aircraft (MOVA), is proposed as a potential candidate for autonomous execution of field work in less-structured indoor and outdoor environments. Practical use of the MOVA system requires a unified controller that addresses the coupled and complex dynamics of the composite system; especially the interaction of the robotic manipulator with the aircraft airframe. Model-based controller design methods require explicit dynamics models of the MOVA system. Preliminary investigation of a two-dimensional MOVA system toward a dynamics model and controller design is presented in preparation for developing the controller of the more complex MOVA system in 3D space. Dynamics of the planar MOVA system are derived using the Lagrangian approach and then transforming the result into a form that facilitates controller design using the concept of a virtual manipulator. A MOVA end-effector trajectory tracking controller was designed with the transformed dynamics equation using the integrator back-stepping control design framework. Validity of the controller is shown via stability analysis, simulation results, and results from a physical test-bed. A systematic approach is illustrated for the derivation of the 3D MOVA system dynamics equations. The resulting dynamics equations are represented abstractly in the standard robot dynamics form and proven to have the skew-symmetric property, which is a useful property for control derivation. An open source Mathematica program was developed to achieve automatic symbolic derivation of the MOVA system dynamics. Accessory tools were also designed to create a tool-chain that starts with an Autodesk Inventor CAD drawing, generates input to the Mathematica program, and then formats the output for direct use in MATLAB and Simulink. A unified nonlinear control algorithm that controls the 3D MOVA system, including both the aircraft and the onboard manipulator, as a single entity was developed to achieve trajectory tracking of the MOVA end-effector position and attitude based on the explicit dynamics equation. Globally Uniformly Ultimately Bounded (GUUB) stability is proven for the controller using Lyapunov-type stability analysis. Physical testing was constructed in order to to demonstrate the performance of the proposed controller on a MOVA system with a two-link onboard manipulator

Prohibited Volume Avoidance for Aircraft

This thesis describes the development of a pilot override control system that prevents aircraft entering critical regions of space, known as prohibited volumes. The aim is to prevent another 9/11 style terrorist attack, as well as act as a general safety system for transport aircraft. The thesis presents the design and implementation of three core modules in the system; the trajectory generation algorithm, the trigger mechanism for the pilot override and the trajectory following element. The trajectory generation algorithm uses a direct multiple shooting strategy to provide trajectories through online computation that avoid pre-defi ned prohibited volume exclusion regions, whilst accounting for the manoeuvring capabilities of the aircraft. The trigger mechanism incorporates the logic that decides the time at which it is suitable for the override to be activated, an important consideration for ensuring that the system is not overly restrictive for a pilot. A number of methods are introduced, and for safety purposes a composite trigger that incorporates di fferent strategies is recommended. Trajectory following is best achieved via a nonlinear guidance law. The guidance logic sends commands in pitch, roll and yaw to the control surfaces of the aircraft, in order to closely follow the generated avoidance trajectory. Testing and validation is performed using a full motion simulator, with volunteers flying a representative aircraft model and attempting to penetrate prohibited volumes. The proof-of-concept system is shown to work well, provided that extreme aircraft manoeuvres are prevented near the exclusion regions. These hard manoeuvring envelope constraints allow the trajectory following controllers to follow avoidance trajectories accurately from an initial state within the bounding set. In order to move the project closer to a commercial product, operator and regulator input is necessary, particularly due to the radical nature of the pilot override system

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

Robust Control of Nonlinear Systems with applications to Aerial Manipulation and Self Driving Cars

This work considers the problem of planning and control of robots in an environment with obstacles and external disturbances. The safety of robots is harder to achieve when planning in such uncertain environments. We describe a robust control scheme that combines three key components: system identification, uncertainty propagation, and trajectory optimization. Using this control scheme we tackle three problems. First, we develop a Nonlinear Model Predictive Controller (NMPC) for articulated rigid bodies and apply it to an aerial manipulation system to grasp object mid-air. Next, we tackle the problem of obstacle avoidance under unknown external disturbances. We propose two approaches, the first approach using adaptive NMPC with open- loop uncertainty propagation and the second approach using Tube NMPC. After that, we introduce dynamic models which use Artificial Neural Networks (ANN) and combine them with NMPC to control a ground vehicle and an aerial manipulation system. Finally, we introduce a software framework for integrating the above algorithms to perform complex tasks. The software framework provides users with the ability to design systems that are robust to control and hardware failures where preventive action is taken before-hand. The framework also allows for safe testing of control and task logic in simulation before evaluating on the real robot. The software framework is applied to an aerial manipulation system to perform a package sorting task, and extensive experiments demonstrate the ability of the system to recover from failures. In addition to robust control, we present two related control problems. The first problem pertains to designing an obstacle avoidance controller for an underactuated system that is Lyapunov stable. We extend a standard gyroscopic obstacle avoidance controller to be applicable to an underactuated system. The second problem addresses the navigation of an Unmanned Ground Vehicle (UGV) on an unstructured terrain. We propose using NMPC combined with a high fidelity physics engine to generate a reference trajectory that is dynamically feasible and accounts for unsafe areas in the terrain

Adaptive Control of Systems with Quantization and Time Delays

This thesis addresses problems relating to tracking control of nonlinear systems in the presence of quantization and time delays. Motivated by the importance in areas such as networked control systems (NCSs) and digital systems, where the use of a communication network in NCS introduces several constraints to the control system, such as the occurrence of quantization and time delays. Quantization and time delays are of both practical and theoretical importance, and the study of systems where these issues arises is thus of great importance. If the system also has parameters that vary or are uncertain, this will make the control problem more complicated. Adaptive control is one tool to handle such system uncertainty. In this thesis, adaptive backstepping control schemes are proposed to handle uncertainties in the system, and to reduce the effects of quantization. Different control problems are considered where quantization is introduced in the control loop, either at the input, the state or both the input and the state. The quantization introduces difficulties in the controller design and stability analysis due to the limited information and nonlinear characteristics, such as discontinuous phenomena. In the thesis, it is analytically shown how the choice of quantization level affects the tracking performance, and how the stability of the closed-loop system equilibrium can be achieved by choosing proper design parameters. In addition, a predictor feedback control scheme is proposed to compensate for a time delay in the system, where the inputs are quantized at the same time. Experiments on a 2-degrees of freedom (DOF) helicopter system demonstrate the different developed control schemes.publishedVersio