Design of a DDP controller for autonomous autorotative landing of RW UAV following engine failure

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, April 2016A Rotary Wing Unmanned Aerial Vehicle (RW UAV) as a platform and its payload consisting of sophisticated sensors would be costly items. Hence, a RW UAV in the 500 kg class designed to fulfil a number of missions would represent a considerable capital outlay for any customer. Therefore, in the event of an engine failure, a means should be provided to get the craft safely back on the ground without incurring damage or causing danger to the surrounding area. The aim of the study was to design a controller for autorotative landing of a RW UAV in the event of engine failure. In order to design a controller for autorotative landing, an acceleration model was used obtained from a study by Stanford University. FLTSIM helicopter flight simulation package yielded necessary RW UAV response data for the autorotation regimes. The response data was utilized in identifying the unknown parameters in the acceleration model. A Differential Dynamic Programming (DDP) control algorithm was designed to compute the main and tail rotor collective pitch and the longitudinal and lateral cyclic pitch control inputs to safely land the craft. The results obtained were compared to the FLTSIM flight simulation response data. It was noted that the mathematical model could not accurately model the pitch dynamics. The main rotor dynamics were modelled satisfactorily and which are important in autorotation because without power from the engine, the energy in main rotor is critical in a successful execution of an autorotative landing. Stanford University designed a controller for RC helicopter, XCell Tempest, which was deemed successful. However, the DDP controller was designed for autonomous autorotative landing of RW UAV weighing 560 kg, following engine failure. The DDP controller has the ability to control the RW UAV in an autorotation landing but the study should be taken further to improve certain aspects such as the pitch dynamics and which can possibly be achieved through online parameter estimation.MT 201

Survey on Flight Control Technology for Large-Scale Helicopter

A literature review of flight control technology is presented for large-scale helicopter. Challenges of large-scale helicopter flight control system (FCS) design are illustrated. Following this, various flight control methodologies are described with respect to their engineering implementation and theoretical developments, whose advantages and disadvantages are also analyzed. Then, the challenging research issues on flight control technology are identified, and future directions are highlighted

Handling Qualities Assessment of a Pilot Cueing System for Autorotation Maneuvers

This paper details the design and limited flight testing of a preliminary system for visual pilot cueing during autorotation maneuvers. The cueing system is based on a fully-autonomous, multi-phase autorotation control law that has been shown to successfully achieve autonomous autorotation landing in unmanned helicopters. To transition this control law to manned systems, it is employed within a cockpit display to drive visual markers which indicate desired collective pitch and longitudinal cyclic positions throughout the entire maneuver, from autorotation entry to touchdown. A series of simulator flight experiments performed at University of Liverpool’s HELIFLIGHT-R simulator are documented, in which pilots attempt autorotation with and without the pilot cueing system in both good and degraded visual environments. Performance of the pilot cueing system is evaluated based on both subjective pilot feedback and objective measurements of landing survivability metrics, demonstrating suitable preliminary performance of the system

Optimal aeroelastic trim for rotorcraft with constrained, non-unique trim solutions

New rotorcraft configurations are emerging, such as the optimal speed helicopter and slowed-rotor compound helicopter which, due to variable rotor speed and redundant lifting components, have non-unique trim solution spaces. The combination of controls and rotor speed that produce the best steady-flight condition is sought among all the possible solutions. This work develops the concept of optimal rotorcraft trim and explores its application to advanced rotorcraft configurations with non-unique, constrained trim solutions. The optimal trim work is based on the nonlinear programming method of the generalized reduced gradient (GRG) and is integrated into a multi-body, comprehensive aeroelastic rotorcraft code. In addition to the concept of optimal trim, two further developments are presented that allow the extension of optimal trim to rotorcraft with rotors that operate over a wide range of rotor speeds. The first is the concept of variable rotor speed trim with special application to rotors operating in steady autorotation. The technique developed herein treats rotor speed as a trim variable and uses a Newton-Raphson iterative method to drive the rotor speed to zero average torque simultaneously with other dependent trim variables. The second additional contribution of this thesis is a novel way to rapidly approximate elastic rotor blade stresses and strains in the aeroelastic trim analysis for structural constraints. For rotors that operate over large angular velocity ranges, rotor resonance and increased flapping conditions are encountered that can drive the maximum cross-sectional stress and strain to levels beyond endurance limits; such conditions must be avoided. The method developed herein captures the maximum cross-sectional stress/strain based on the trained response of an artificial neural network (ANN) surrogate as a function of 1-D beam forces and moments. The stresses/strains are computed simultaneously with the optimal trim and are used as constraints in the optimal trim solution. Finally, an optimal trim analysis is applied to a high-speed compound gyroplane configuration, which has two distinct rotor speed control methods, with the purpose of maximizing the vehicle cruise efficiency while maintaining rotor blade strain below endurance limit values.Ph.D.Committee Chair: Dimitri N. Mavris; Committee Co-Chair: Daniel P Schrage; Committee Member: David A. Peters; Committee Member: Dewey H. Hodges; Committee Member: J.V.R. Prasa

Adaptive neural fault-tolerant control of a 3-DOF model helicopter system

In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle system uncertainty and nonlinear actuator faults, a neural network disturbance observer is developed based on the radial basis function neural network. The unknown external disturbance and the unknown neural network approximation errors are treated as a compound disturbance that is estimated by another nonlinear disturbance observer. A disturbance observer-based adaptive neural fault-tolerant control scheme is then developed to track the desired system output in the presence of system uncertainty, external disturbance, and actuator faults. The stability of the whole closed-loop system is analyzed using the Lyapunov method, which guarantees the convergence of all closed-loop signals. Finally, the simulation results are presented to illustrate the effectiveness of the new control design techniques.Mou Chen, Peng Shi and Cheng-Chew Li

RETROSPECTIVE AND EXPLORATORY ANALYSES FOR ENHANCING THE SAFETY OF ROTORCRAFT OPERATIONS

From recent safety reports, the accident rates associated with helicopter operations have reached a plateau and even have an increasing trend. More attention needs to be directed to this domain, and it was suggested to expand the use of flight data recorders on board for monitoring the operation. With the expected growth of flight data records in the coming years, it is essential to conduct analyses and provide the findings to the operator for risk mitigation. In this thesis, a retrospective analysis is proposed to detect potential anomalies in the fight data for rotorcraft operations. In the study, an algorithm is developed to detect the phases of flight for segmenting the flights into homogeneous entities. The anomaly detection is then performed on the flight segments within the same flight phases, and it is implemented through a sequential approach. Aside from the retrospective analysis, the exploratory analysis aims to efficiently find the safety envelope and predict the recovery actions for a hazardous event. To facilitate the exploration of the corresponding operational space, we provide a framework consisting of surrogate modeling and the design of experiments for tackling the tasks. In the study, the autorotation, a maneuver used to land the vehicle under power loss, is treated as a used case to test and validate the proposed framework.Ph.D

A review of safe online learning for nonlinear control systems

Learning for autonomous dynamic control systems that can adapt to unforeseen environmental changes are of great interest but the realisation of a practical and safe online learning algorithm is incredibly challenging. This paper highlights some of the main approaches for safe online learning of stabilisable nonlinear control systems with a focus on safety certification for stability. We categorise a non-exhaustive list of salient techniques, with a focus on traditional control theory as opposed to reinforcement learning and approximate dynamic programming. This paper also aims to provide a simplified overview of techniques as an introduction to the field. It is the first paper to our knowledge that compares key attributes and advantages of each technique in one paper

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