Guidance and control of an autonomous underwater vehicle

Merged with duplicate record 10026.1/856 on 07.03.2017 by CS (TIS)A cooperative project between the Universities of Plymouth and Cranfield was aimed at designing and developing an autonomous underwater vehicle named Hammerhead. The work presented herein is to formulate an advance guidance and control system and to implement it in the Hammerhead. This involves the description of Hammerhead hardware from a control system perspective. In addition to the control system, an intelligent navigation scheme and a state of the art vision system is also developed. However, the development of these submodules is out of the scope of this thesis. To model an underwater vehicle, the traditional way is to acquire painstaking mathematical models based on laws of physics and then simplify and linearise the models to some operating point. One of the principal novelties of this research is the use of system identification techniques on actual vehicle data obtained from full scale in water experiments. Two new guidance mechanisms have also been formulated for cruising type vehicles. The first is a modification of the proportional navigation guidance for missiles whilst the other is a hybrid law which is a combination of several guidance strategies employed during different phases of the Right. In addition to the modelling process and guidance systems, a number of robust control methodologies have been conceived for Hammerhead. A discrete time linear quadratic Gaussian with loop transfer recovery based autopilot is formulated and integrated with the conventional and more advance guidance laws proposed. A model predictive controller (MPC) has also been devised which is constructed using artificial intelligence techniques such as genetic algorithms (GA) and fuzzy logic. A GA is employed as an online optimization routine whilst fuzzy logic has been exploited as an objective function in an MPC framework. The GA-MPC autopilot has been implemented in Hammerhead in real time and results demonstrate excellent robustness despite the presence of disturbances and ever present modelling uncertainty. To the author's knowledge, this is the first successful application of a GA in real time optimization for controller tuning in the marine sector and thus the thesis makes an extremely novel and useful contribution to control system design in general. The controllers are also integrated with the proposed guidance laws and is also considered to be an invaluable contribution to knowledge. Moreover, the autopilots are used in conjunction with a vision based altitude information sensor and simulation results demonstrate the efficacy of the controllers to cope with uncertain altitude demands.J&S MARINE LTD., QINETIQ, SUBSEA 7 AND SOUTH WEST WATER PL

Certification Considerations for Adaptive Systems

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach

EVALUATING ARTIFICIAL INTELLIGENCE METHODS FOR USE IN KILL CHAIN FUNCTIONS

Current naval operations require sailors to make time-critical and high-stakes decisions based on uncertain situational knowledge in dynamic operational environments. Recent tragic events have resulted in unnecessary casualties, and they represent the decision complexity involved in naval operations and specifically highlight challenges within the OODA loop (Observe, Orient, Decide, and Assess). Kill chain decisions involving the use of weapon systems are a particularly stressing category within the OODA loop—with unexpected threats that are difficult to identify with certainty, shortened decision reaction times, and lethal consequences. An effective kill chain requires the proper setup and employment of shipboard sensors; the identification and classification of unknown contacts; the analysis of contact intentions based on kinematics and intelligence; an awareness of the environment; and decision analysis and resource selection. This project explored the use of automation and artificial intelligence (AI) to improve naval kill chain decisions. The team studied naval kill chain functions and developed specific evaluation criteria for each function for determining the efficacy of specific AI methods. The team identified and studied AI methods and applied the evaluation criteria to map specific AI methods to specific kill chain functions.Civilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCaptain, United States Marine CorpsCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Experimental and theoretical control of a smart projectile fin using piezoelectric bimorph actuator

The goal of this work is to develop efficient control algorithms for the control of a smart projectile fin. Smart fins are deployed as soon as the projectile reaches the apogee and are used to steer the projectile towards its target by controlling the rotation angle of the fin. The fin is actuated using the piezoelectric macro-fiber composite (MFC) bimorph actuator which is completely enclosed within the aero-shell. The actuator is composed of two Macro Fiber Composites (MFC\u27s), manufactured by Smart Material Co. The presented smart fin design minimizes the volume and weight of the unit; Two different models of the smart fin are developed. One is mathematical model that uses finite element approach to describe dynamics of the smart fin system. This model includes the aerodynamic moment which is a function of the angle of attack of the projectile. Second model is based on system identification approach. A linear model of the actuator and fin is identified experimentally by exciting the system using a chirp signal. Comparison is done between these two models based on open-loop step response of the smart fin system; In this dissertation, five kinds of control systems based on fuzzy logic, inverse dynamics and adaptive structure theory are developed. The aerodynamic disturbances and parameter uncertainties are considered in these controllers. The simulation results illustrate that asymptotic trajectory tracking of the fin angle is achieved, in spite of uncertainties in the system parameters and presence of aerodynamic disturbance. A prototype model of the projectile fin is developed in the laboratory for real-time control. The designed controllers are validated using the subsonic wind tunnel at University of Nevada, Las Vegas (UNLV) for various wind speeds. Experimental results show that the designed controllers accomplish fin angle control

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Planification de trajectoire sous contraintes d'aéronef

The focus of this PhD thesis is on the trajectory planning module as a part of autonomous aircraft system. Feasible trajectories for aircraft flying in environment cluttered by obstacles are studied. Since aircraft dynamics are complex, nonlinear and nonholonomic; trajectory planning for such systems is very difficult and challenging.Rapidly-exploring Random Tree or RRT path planner is used as a basis to find a feasible trajectory. The advantage of this algorithm is that it does not consider only the complete vehicle model but also the environment. Two algorithms are developed to find a feasible and optimal solution. The RRT algorithm, combined with a preprocessing of the exploration space, is used for a complete realistic model of the system. However, this approach does not consider any optimal criteria. In order to consider performance criteria, the RRT* algorithm is used based on a simplified model with the help of the artificial potential field as a heuristic to improve the convergence rate to the solution.The algorithms are simulated in an application of hypersonic aerial vehicles, for example, interceptor missiles flying in high altitude. This makes the aerodynamically controlled aircraft have less maneuverability since the air density decreases exponentially with altitude. 3D shortest paths are developed and used as a metric. Therefore, a feasible and optimal trajectory is obtained efficiently. With these results, real-time constraints will be easier to verify if the algorithm is implemented on board the vehicle. In future work, replanning will be considered to improve the performance of the algorithm in case of dynamic environment or changes in the mission.Le sujet de cette thèse porte sur la planification de trajectoire pour un aéronef autonome. Les trajectoires d'aéronefs se déplaçant dans un environnement encombré par des obstacles sont étudiées. La dynamique des aéronefs étant complexe, non linéaire, et non holonome, la planification de trajectoire de ce type de systèmes est un problème très difficile.L'algorithme Rapidly-exploring Random Tree, ou RRT, est utilisé comme planificateur de base. L'avantage de cet algorithme est qu'il permet de considérer des modèles d'aéronefs complets dans un environnement complexe. Deux algorithmes sont développés pour trouver une solution faisable et optimale. Pour un modèle complet, L'algorithme RRT avec un prétraitement de l'espace d'état est utilisé dans le cas d'une prise en compte du modèle complet du système. Cependant, cette méthode ne considère pas de critères optimaux. Pour y remédier, l'algorithme RRT* est utilisé pour un modèle simplifié du système avec l'aide de champs de potentiels artificiels comme heuristique pour améliorer le taux de convergence vers la solution.Les algorithmes sont simulés pour une application d'aéronefs hypersoniques, comme par exemple des missiles intercepteurs volants à haute altitude. Les aéronefs ont donc moins de manœuvrabilité parce que la densité de l'air diminue exponentiellement avec l'altitude. Les chemins les plus courts en 3D sont développés et utilisés comme une métrique. Des trajectoires réalisables et optimales sont obtenues efficacement. A partir de ces résultats, les contraintes de temps réel à bord du véhicule seront plus faciles à vérifier. Dans les travaux futurs, la replanification sera considérée pour améliorer la performance de l'algorithme en cas d'environnement dynamique ou de changements dans la mission

NASA Automated Rendezvous and Capture Review. A compilation of the abstracts

This document presents a compilation of abstracts of papers solicited for presentation at the NASA Automated Rendezvous and Capture Review held in Williamsburg, VA on November 19-21, 1991. Due to limitations on time and other considerations, not all abstracts could be presented during the review. The organizing committee determined however, that all abstracts merited availability to all participants and represented data and information reflecting state-of-the-art of this technology which should be captured in one document for future use and reference. The organizing committee appreciates the interest shown in the review and the response by the authors in submitting these abstracts

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980