Development of a nonlinear 6-degree of freedom miniature rotary-wing unmanned aerial vehicle software model and PID flight path controller using Mathworks Simulink simulation environment

This paper describes the development of a 6-degree of freedom (6-DOF), nonlinear, miniature rotary-wing unmanned aerial vehicle (RW UAV) simulation environment using MathWorks Simulink simulation software. In addition to the modeling process, this research also conducts flight-path controller design using Proportional-Derivative (PD) control techniques. This model's development is motivated by the desire to enable a rapid prototyping platform for design and implementation of various flight control techniques with further seamless transition to the hardware in the loop (HIL) and flight-testing. The T-Rex Align 600 remote controlled helicopter with COTS autopilot was chosen as a prototype rotary UAV platform. The development of the nonlinear simulation model is implemented starting with extensive literature review of helicopter aerodynamics and flight dynamics theory and applying the mathematical models of the helicopter components to generate helicopter inertial frame motion simulations from operator commands. The primary helicopter components modeled in this thesis include the helicopter main rotor inflow, thrust, flapping dynamics, as well as the tail rotor inflow and thrust responses. The inertial frame motions are animated using the Flight Gear Version 0.9.8 software. After obtaining simulations with verifiable results, the nonlinear model is linearized about the hovering flight condition and a linear model is extracted. Lastly, the PD controller is designed and flight path software in the loop (SIL) test results are presented and explained. The SIL tests are conducted for autonomous flight along specified rectangular and figure-8 flight paths.http://archive.org/details/developmentofnon109454586US Marine Corps (USMC) author.Approved for public release; distribution is unlimited

Design and control of quadrotors with application to autonomous flying

This thesis is about modelling, design and control of Miniature Flying Robots (MFR) with a focus on Vertical Take-Off and Landing (VTOL) systems and specifically, micro quadrotors. It introduces a mathematical model for simulation and control of such systems. It then describes a design methodology for a miniature rotorcraft. The methodology is subsequently applied to design an autonomous quadrotor named OS4. Based on the mathematical model, linear and nonlinear control techniques are used to design and simulate various controllers along this work. The dynamic model and the simulator evolved from a simple set of equations, valid only for hovering, to a complex mathematical model with more realistic aerodynamic coefficients and sensor and actuator models. Two platforms were developed during this thesis. The first one is a quadrotor-like test-bench with off-board data processing and power supply. It was used to safely and easily test control strategies. The second one, OS4, is a highly integrated quadrotor with on-board data processing and power supply. It has all the necessary sensors for autonomous operation. Five different controllers were developed. The first one, based on Lyapunov theory, was applied for attitude control. The second and the third controllers are based on PID and LQ techniques. These were compared for attitude control. The fourth and the fifth approaches use backstepping and sliding-mode concepts. They are applied to control attitude. Finally, backstepping is augmented with integral action and proposed as a single tool to design attitude, altitude and position controllers. This approach is validated through various flight experiments conducted on the OS4

Modeling the Human Visuo-Motor System for Remote-Control Operation

University of Minnesota Ph.D. dissertation. 2018. Major: Computer Science. Advisors: Nikolaos Papanikolopoulos, Berenice Mettler. 1 computer file (PDF); 172 pages.Successful operation of a teleoperated miniature rotorcraft relies on capabilities including guidance, trajectory following, feedback control, and environmental perception. For many operating scenarios fragile automation systems are unable to provide adequate performance. In contrast, human-in-the-loop systems demonstrate an ability to adapt to changing and complex environments, stability in control response, high level goal selection and planning, and the ability to perceive and process large amounts of information. Modeling the perceptual processes of the human operator provides the foundation necessary for a systems based approach to the design of control and display systems used by remotely operated vehicles. In this work we consider flight tasks for remotely controlled miniature rotorcraft operating in indoor environments. Operation of agile robotic systems in three dimensional spaces requires a detailed understanding of the perceptual aspects of the problem as well as knowledge of the task and models of the operator response. When modeling the human-in-the-loop the dynamics of the vehicle, environment, and human perception-action are tightly coupled in space and time. The dynamic response of the overall system emerges from the interplay of perception and action. The main questions to be answered in this work are: i) what approach does the human operator implement when generating a control and guidance response? ii) how is information about the vehicle and environment extracted by the human? iii) can the gaze patterns of the pilot be decoded to provide information for estimation and control? In relation to existing research this work differs by focusing on fast acting dynamic systems in multiple dimensions and investigating how the gaze can be exploited to provide action-relevant information. To study human-in-the-loop systems the development and integration of the experimental infrastructure is described. Utilizing the infrastructure, a theoretical framework for computational modeling of the human pilot’s perception-action is proposed and verified experimentally. The benefits of the human visuo-motor model are demonstrated through application examples where the perceptual and control functions of a teleoperation system are augmented to reduce workload and provide a more natural human-machine interface

A Continuous-Time Nonlinear Observer for Estimating Structure from Motion from Omnidirectional Optic Flow

Various insect species utilize certain types of self-motion to perceive structure in their local environment, a process known as active vision. This dissertation presents the development of a continuous-time formulated observer for estimating structure from motion that emulates the biological phenomenon of active vision. In an attempt to emulate the wide-field of view of compound eyes and neurophysiology of insects, the observer utilizes an omni-directional optic flow field. Exponential stability of the observer is assured provided the persistency of excitation condition is met. Persistency of excitation is assured by altering the direction of motion sufficiently quickly. An equal convergence rate on the entire viewable area can be achieved by executing certain prototypical maneuvers. Practical implementation of the observer is accomplished both in simulation and via an actual flying quadrotor testbed vehicle. Furthermore, this dissertation presents the vehicular implementation of a complimentary navigation methodology known as wide-field integration of the optic flow field. The implementation of the developed insect-inspired navigation methodologies on physical testbed vehicles utilized in this research required the development of many subsystems that comprise a control and navigation suite, including avionics development and state sensing, model development via system identification, feedback controller design, and state estimation strategies. These requisite subsystems and their development are discussed

Intelligent control of miniature holonomic vertical take-off and landing robot

This paper discusses the development of a fuzzy based controller for miniaturized unmanned aerial vehicle (UAV).This controller is designed to control the center-of-gravity (CoG) in a new configuration of coaxial miniaturized flying robot (MFR). The idea is to shift the CoG by controlling two pendulums located in perpendicular directions; each pendulum ends with a small mass. A key feature of this work is that the control algorithm represents the original nonlinear function that describes the dynamics of the proposed system. The controller model incorporates two cascaded subsystems: PD and PI fuzzy logic controllers. These two controllers regulate the attitude and the position of the flying robot, respectively. A model of the proposed controllers has been developed and evaluated in terms of stability and maneuverability. The results show that the presented control system can be used efficiently for the MFR applications

Online parameter estimation of a miniature unmanned helicopter using neural network techniques

The online aerodynamic parameter estimation of a miniature unmanned helicopter using Neural Network techniques has been presented. The simulation model for the miniature helicopter was developed using the MATLAB/ SIMULINK software tool. Three trim conditions were analyzed: hover flight, 10m/s forward flight and 20m/s forward flight. Radial Basis Function (RBF) online learning was achieved using a moving window algorithm which generated an input-output data set at each time step. RBF network online identification was achieved with good robustness to noise for all flight conditions. However, the presence of atmospheric turbulence and sensor noise had an adverse effect on network size and memory usage. The Delta Method (DM) and the Modified Delta Method (MDM) was investigated for the NN-based online estimation of aerodynamic parameters. An increasing number high confidence estimated parameters could be extracted using the MDM as the helicopter transitioned from hover to forward flight

An Investigation of Large Tilt-Rotor Hover and Low Speed Handling Qualities

A piloted simulation experiment conducted on the NASA-Ames Vertical Motion Simulator evaluated the hover and low speed handling qualities of a large tilt-rotor concept, with particular emphasis on longitudinal and lateral position control. Ten experimental test pilots evaluated different combinations of Attitude Command-Attitude Hold (ACAH) and Translational Rate Command (TRC) response types, nacelle conversion actuator authority limits and inceptor choices. Pilots performed evaluations in revised versions of the ADS-33 Hover, Lateral Reposition and Depart/Abort MTEs and moderate turbulence conditions. Level 2 handling qualities ratings were primarily recorded using ACAH response type in all three of the evaluation maneuvers. The baseline TRC conferred Level 1 handling qualities in the Hover MTE, but there was a tendency to enter into a PIO associated with nacelle actuator rate limiting when employing large, aggressive control inputs. Interestingly, increasing rate limits also led to a reduction in the handling qualities ratings. This led to the identification of a nacelle rate to rotor longitudinal flapping coupling effect that induced undesired, pitching motions proportional to the allowable amount of nacelle rate. A modification that counteracted this effect significantly improved the handling qualities. Evaluation of the different response type variants showed that inclusion of TRC response could provide Level 1 handling qualities in the Lateral Reposition maneuver by reducing coupled pitch and heave off axis responses that otherwise manifest with ACAH. Finally, evaluations in the Depart/Abort maneuver showed that uncertainty about commanded nacelle position and ensuing aircraft response, when manually controlling the nacelle, demanded high levels of attention from the pilot. Additional requirements to maintain pitch attitude within 5 deg compounded the necessary workload

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