Advanced flight control system study

The architecture, requirements, and system elements of an ultrareliable, advanced flight control system are described. The basic criteria are functional reliability of 10 to the minus 10 power/hour of flight and only 6 month scheduled maintenance. A distributed system architecture is described, including a multiplexed communication system, reliable bus controller, the use of skewed sensor arrays, and actuator interfaces. Test bed and flight evaluation program are proposed

Failure Diagnosis and Prognosis of Safety Critical Systems: Applications in Aerospace Industries

Many safety-critical systems such as aircraft, space crafts, and large power plants are required to operate in a reliable and efficient working condition without any performance degradation. As a result, fault diagnosis and prognosis (FDP) is a research topic of great interest in these systems. FDP systems attempt to use historical and current data of a system, which are collected from various measurements to detect faults, diagnose the types of possible failures, predict and manage failures in advance. This thesis deals with FDP of safety-critical systems. For this purpose, two critical systems including a multifunctional spoiler (MFS) and hydro-control value system are considered, and some challenging issues from the FDP are investigated. This research work consists of three general directions, i.e., monitoring, failure diagnosis, and prognosis. The proposed FDP methods are based on data-driven and model-based approaches. The main aim of the data-driven methods is to utilize measurement data from the system and forecast the remaining useful life (RUL) of the faulty components accurately and efficiently. In this regard, two dierent methods are developed. A modular FDP method based on a divide and conquer strategy is presented for the MFS system. The modular structure contains three components:1) fault diagnosis unit, 2) failure parameter estimation unit and 3) RUL unit. The fault diagnosis unit identifies types of faults based on an integration of neural network (NN) method and discrete wavelet transform (DWT) technique. Failure parameter estimation unit observes the failure parameter via a distributed neural network. Afterward, the RUL of the system is predicted by an adaptive Bayesian method. In another work, an innovative data-driven FDP method is developed for hydro-control valve systems. The idea is to use redundancy in multi-sensor data information and enhance the performance of the FDP system. Therefore, a combination of a feature selection method and support vector machine (SVM) method is applied to select proper sensors for monitoring of the hydro-valve system and isolate types of fault. Then, adaptive neuro-fuzzy inference systems (ANFIS) method is used to estimate the failure path. Similarly, an online Bayesian algorithm is implemented for forecasting RUL. Model-based methods employ high-delity physics-based model of a system for prognosis task. In this thesis, a novel model-based approach based on an integrated extended Kalman lter (EKF) and Bayesian method is introduced for the MFS system. To monitor the MFS system, a residual estimation method using EKF is performed to capture the progress of the failure. Later, a transformation is utilized to obtain a new measure to estimate the degradation path (DP). Moreover, the recursive Bayesian algorithm is invoked to predict the RUL. Finally, relative accuracy (RA) measure is utilized to assess the performance of the proposed methods

Integrated control and health management. Orbit transfer rocket engine technology program

To insure controllability of the baseline design for a 7500 pound thrust, 10:1 throttleable, dual expanded cycle, Hydrogen-Oxygen, orbit transfer rocket engine, an Integrated Controls and Health Monitoring concept was developed. This included: (1) Dynamic engine simulations using a TUTSIM derived computer code; (2) analysis of various control methods; (3) Failure Modes Analysis to identify critical sensors; (4) Survey of applicable sensors technology; and, (5) Study of Health Monitoring philosophies. The engine design was found to be controllable over the full throttling range by using 13 valves, including an oxygen turbine bypass valve to control mixture ratio, and a hydrogen turbine bypass valve, used in conjunction with the oxygen bypass to control thrust. Classic feedback control methods are proposed along with specific requirements for valves, sensors, and the controller. Expanding on the control system, a Health Monitoring system is proposed including suggested computing methods and the following recommended sensors: (1) Fiber optic and silicon bearing deflectometers; (2) Capacitive shaft displacement sensors; and (3) Hot spot thermocouple arrays. Further work is needed to refine and verify the dynamic simulations and control algorithms, to advance sensor capabilities, and to develop the Health Monitoring computational methods

On Increasing the Automation Level of Heavy-Duty Hydraulic Manipulators with Condition Monitoring of the Hydraulic System and Energy-Optimised Redundancy Resolution

Hydraulic manipulators on mobile machines are predominantly used for excavation and lifting applications at construction sites and for heavy-duty material handling in the forest industry due to their superior power-density and rugged nature. These manipulators are conventionally open-loop controlled by human operators who are sufficiently skilled to operate the machines. However, in the footsteps of pioneering original equipment manufacturers (OEMs) and to keep up with the intensifying demand for innovation, more and more mobile machine OEMs have a major interest in significantly increasing the automation level of their hydraulic manipulators and improving the operation of manipulators. In this thesis, robotic software-based functionalities in the form of modelbased condition monitoring and energy-optimal redundancy resolution which facilitate increased automation level of hydraulic manipulators are proposed.A condition monitoring system generally consists of software modules and sensors which co-operate harmonically and monitor the hydraulic system’s health in real-time based on an indirect measure of this system’s health. The premise is that when this condition monitoring system recognises that the system’s health has deteriorated past a given threshold (in other words, when a minor fault is detected, such as a slowly increasing internal leakage of the hydraulic cylinder), the condition monitoring module issues an alarm to warn the system operator of the malfunction, and the module could ideally diagnose the fault cause. In addition, when faced with severe faults, such as an external leakage or an abruptly increasing internal leakage in the hydraulic system, an alarm from the condition monitoring system ensures that the machine is quickly halted to prevent any further damage to the machine or its surroundings.The basic requirement in the design of such a condition monitoring system is to make sure that this system is robust and fault-sensitive. These properties are difficult to achieve in complex mobile hydraulic systems on hydraulic manipulators due to the modelling uncertainties affecting these systems. The modelling uncertainties affecting mobile hydraulic systems are specific compared with many other types of systems and are large because of the hydraulic system complexities, nonlinearities, discontinuities and inherently time-varying parameters. A feasible solution to this modelling uncertainty problem would be to either attenuate the effect of modelling errors on the performance of model-based condition monitoring or to develop improved non-model-based methods with increased fault-sensitivity. In this research work, the former model-based approach is taken. Adaptation of the model residual thresholds based on system operating points and reliable, load-independent system models are proposed as integral parts of the condition monitoring solution to the modelling uncertainty problem. These proposed solutions make the realisation of condition monitoring solutions more difficult on heavy-duty hydraulic manipulators compared with fixed-load manipulators, for example. These solutions are covered in detail in a subset of the research publications appended to this thesis.There is wide-spread interest from hydraulic manipulator OEMs in increasing the automation level of their hydraulic manipulators. Most often, this interest is related to semi-automation of repetitive work cycles to improve work productivity and operator workload circumstances. This robotic semi-automated approach involves resolving the kinematic redundancy of hydraulic manipulators to obtain motion references for the joint controller to enable desirable closed-loop controlled motions. Because conventional redundancy resolutions are usually sub-optimal at the hydraulic system level, a hydraulic energy-optimised, global redundancy resolution is proposed in this thesis for the first time. Kinematic redundancy is resolved energy optimally from the standpoint of the hydraulic system along a prescribed path for a typical 3-degrees-of-freedom (3-DOF) and 4-DOF hydraulic manipulator. Joint motions are also constrained based on the actuators’ position, velocity and acceleration bounds in hydraulic manipulators in the proposed solution. This kinematic redundancy resolution topic is discussed in the last two research papers. Overall, both designed manipulator features, condition monitoring and energy-optimised redundancy resolution, are believed to be essential for increasing the automation of hydraulic manipulators