Robust Control for Lateral and Longitudinal Channels of Small-Scale Unmanned Helicopters

Lateral and longitudinal channels are two closely related channels whose control stability influences flight performance of small-scale unmanned helicopters directly. This paper presents a robust control approach for lateral and longitudinal channels in the presence of parameter uncertainties and exogenous disturbances. The proposed control approach is performed by two steps. First, by performing system identification in frequency domain, system model of lateral and longitudinal channels can be accurately identified. Then, a robust H∞ state feedback controller is designed to stabilize the helicopter in lateral and longitudinal channels simultaneously under extraneous disturbances situation. The proposed approach takes advantages that it reduces order of the controller by preestimating some parameters (like flapping angles) without sacrificing control accuracy. Numerical results show the reliability and effectiveness of the proposed method

Tail motion model identification for control design of an unmanned helicopter

This paper explains the methodology developed to design the yaw control system (heading control system) of the α-SAC UAV. The problem of modeling and controlling the tail motion of this UAV along a desired trajectory is considered. First, the response data of the system are collected during special flight test and a linear time invariant model is extracted by identification techniques. Then, the control system is designed and implemented using a PID feedback/feedforward control method. The technique is tested in simulation and validated in the autonomous flight of the small scale helicopter.Peer ReviewedPostprint (published version

A Comparative Framework for Maneuverability and Gust Tolerance of Aerial Microsystems

Aerial microsystems have the potential of navigating low-altitude, cluttered environments such as urban corridors and building interiors. Reliable systems require both agility and tolerance to gusts. While many platform designs are under development, no framework currently exists to quantitatively assess these inherent bare airframe characteristics which are independent of closed loop controllers. This research develops a method to quantify the maneuverability and gust tolerance of vehicles using reachability and disturbance sensitivity sets. The method is applied to a stable flybar helicopter and an unstable flybarless helicopter, whose state space models were formed through system identification. Model-based static H-infinity controllers were also implemented on the vehicles and tested in the lab using fan-generated gusts. It is shown that the flybar restricts the bare airframe's ability to maneuver in translational velocity directions. As such, the flybarless helicopter proved more maneuverable and gust tolerant than the flybar helicopter. This approach was specifically applied here to compare stable and unstable helicopter platforms; however, the framework may be used to assess a broad range of aerial microsystems

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Bio-Inspired Information Extraction In 3-D Environments Using Wide-Field Integration Of Optic Flow

A control theoretic framework is introduced to analyze an information extraction approach from patterns of optic flow based on analogues to wide-field motion-sensitive interneurons in the insect visuomotor system. An algebraic model of optic flow is developed, based on a parameterization of simple 3-D environments. It is shown that estimates of proximity and speed, relative to these environments, can be extracted using weighted summations of the instantaneous patterns of optic flow. Small perturbation techniques are utilized to link weighting patterns to outputs, which are applied as feedback to facilitate stability augmentation and perform local obstacle avoidance and terrain following. Weighting patterns that provide direct linear mappings between the sensor array and actuator commands can be derived by casting the problem as a combined static state estimation and linear feedback control problem. Additive noise and environment uncertainties are incorporated into an offline procedure for determination of optimal weighting patterns. Several applications of the method are provided, with differing spatial measurement domains. Non-linear stability analysis and experimental demonstration is presented for a wheeled robot measuring optic flow in a planar ring. Local stability analysis and simulation is used to show robustness over a range of urban-like environments for a fixed-wing UAV measuring in orthogonal rings and a micro helicopter measuring over the full spherical viewing arena. Finally, the framework is used to analyze insect tangential cells with respect to the information they encode and to demonstrate how cell outputs can be appropriately amplified and combined to generate motor commands to achieve reflexive navigation behavior

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

Advanced control for miniature helicopters : modelling, design and flight test

Unmanned aerial vehicles (UAV) have been receiving unprecedented development during the past two decades. Among different types of UAVs, unmanned helicopters exhibit promising features gained from vertical-takeoff-and-landing, which make them as a versatile platform for both military and civil applications. The work reported in this thesis aims to apply advanced control techniques, in particular model predictive control (MPC), to an autonomous helicopter in order to enhance its performance and capability. First, a rapid prototyping testbed is developed to enable indoor flight testing for miniature helicopters. This testbed is able to simultaneously observe the flight state, carry out complicated algorithms and realtime control of helicopters all in a Matlab/Simulink environment, which provides a streamline process from algorithm development, simulation to flight tests. Next, the modelling and system identification for small-scale helicopters are studied. A parametric model is developed and the unknown parameters are estimated through the designed identification process. After a mathematical model of the selected helicopter is available, three MPC based control algorithms are developed focusing on different aspects in the operation of autonomous helicopters. The first algorithm is a nonlinear MPC framework. A piecewise constant scheme is used in the MPC formulation to reduce the intensive computation load. A two-level framework is suggested where the nonlinear MPC is combined with a low-level linear controller to allow its application on the systems with fast dynamics. The second algorithm solves the local path planning and the successive tracking control by using nonlinear and linear MPC, respectively. The kinematics and obstacle information are incorporated in the path planning, and the linear dynamics are used to design a flight controller. A guidance compensator dynamically links the path planner and flight controller. The third algorithm focuses on the further reduction of computational load in a MPC scheme and the trajectory tracking control in the presence of uncertainties and disturbances. An explicit nonlinear MPC is developed for helicopters to avoid online optimisation, which is then integrated with a nonlinear disturbance observer to significantly improve its robustness and disturbance attenuation. All these algorithms have been verified by flight tests for autonomous helicopters in the dedicated rapid prototyping testbed developed in this thesis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of helicopter attitude axes controlled hover flight without pilot assistance and vehicle crashes.

In this work, we show how to computerize a helicopter to fly attitude axes controlled hover flight without the assistance of a pilot and without ever crashing. We start by developing a helicopter research test bed system including all hardware, software, and means for testing and training the helicopter to fly by computer. We select a Remote Controlled helicopter with a 5 ft. diameter rotor and 2.2 hp engine. We equip the helicopter with a payload of sensors, computers, navigation and telemetry equipment, and batteries. We develop a differential GPS system with cm accuracy and a ground computerized navigation system for six degrees of freedom (6-DoF) free flight while tracking navigation commands. We design feedback control loops with yet-to-be-determined gains for the five control "knobs" available to a flying radio-controlled (RC) miniature helicopter: engine throttle, main rotor collective pitch, longitudinal cyclic pitch, lateral cyclic pitch, and tail rotor collective pitch.We develop helicopter flight equations using fundamental dynamics, helicopter momentum theory and blade element theory. The helicopter flight equations include helicopter rotor equations of motions, helicopter rotor forces and moments, helicopter trim equations, helicopter stability derivatives, and a coupled fuselage-rotor helicopter 6-DoF model. The helicopter simulation also includes helicopter engine control equations, a helicopter aerodynamic model, and finally helicopter stability and control equations. The derivation of a set of non-linear equations of motion for the main rotor is a contribution of this thesis work.After discussing the integration of hardware and software elements of our helicopter research test bed system, we perform a number of experiments and tests using the two specially built test stands. Feedback gains are derived for controlling the following: (1) engine throttle to maintain prescribed main rotor angular speed, (2) main rotor collective pitch to maintain constant elevation, (3) longitudinal cyclic pitch to maintain prescribed pitch angle, (4) lateral cyclic pitch to maintain prescribed roll angle, and (5) yaw axis to maintain prescribed compass direction. (Abstract shortened by UMI.)We design and build two special test stands for training and testing the helicopter to fly attitude axes controlled hover flight, starting with one axis at a time and progressing to multiple axes. The first test stand is built for teaching and testing controlled flight of elevation and yaw (i.e., directional control). The second test stand is built for teaching and testing any one or combination of the following attitude axes controlled flight: (1) pitch, (2) roll and (3) yaw. The subsequent development of a novel method to decouple, stabilize and teach the helicopter hover flight is a primary contribution of this thesis.The novel method included the development of a non-linear modeling technique for linearizing the RPM state equation dynamics so that a simple but accurate transfer function is derivable between the "available torque of the engine" and RPM. Specifically, the main rotor and tail rotor torques are modeled accurately with a bias term plus a nonlinear term involving the product of RPM squared times the main rotor blade pitch angle raised to the three-halves power. Application of this non-linear modeling technique resulted in a simple, representative and accurate transfer function model of the open-loop plant for the entire helicopter system so that all the feedback control laws for autonomous flight purposes could be derived easily using classical control theory. This is one of the contributions of this dissertation work

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