72 research outputs found

    Integrated missile guidance and control using optimization-based predictive control

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    This paper focuses on the design and implementation of optimization-based predictive control for the problem of missile interception. Due to the inherent nonlinearities of the missile–target dynamics or even constraints, it is usually difficult to design a high-accuracy and high-efficiency control algorithm. A nonlinear receding horizon pseudospectral control (RHPC) scheme is constructed and applied to generate the optimal control command. The problem of state estimation, in the presence of measurement noise, is solved by implementing a moving horizon estimation (MHE) algorithm. Since the RHPC and MHE algorithms solve the online open-loop optimal control problem at each sampling instant, the computational cost associated with them can be high. In order to decrease the computational demand due to the optimization process, a recently proposed nonlinear programming sensitivity-based algorithm is used and embedded in the optimization framework. Numerical simulations and analysis are presented to demonstrate the effectiveness of the proposed control scheme

    Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms

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    This book is a reprint of the Special Issue “Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms”,which was published in Applied Sciences

    좁은 화각을 갖는 스트랩다운 탐색기를 위한 유도기법

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    학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 8. 최진영.New guidance laws are proposed to solve the problem of when a missile is equipped with a strapdown seeker instead of a gimbaled seeker. The strapdown seeker has advantages of relatively simple implementation compared to a gimbaled seeker, and it can eliminate frictional cross-coupling significantly save on costs. There have been many studies to enable guided missiles to use strapdown seekers, but they have several weaknesses, such as measurement error caused by scale factor error, radome errors, glint noise, narrow field-of-view (FOV), and so on. Among these weak points, focus is centered on the narrow FOV of the strapdown seeker. A hybrid guidance (HG) law is proposed to maintain the lock-on condition in spite of the narrow FOV of the strapdown seeker. The proposed HG law consists of two guidance phases, which assume operation at a switching boundary. In the first phase, the proportional navigation guidance (PNG) law is applied during the time when the look angle is inside the switching boundary. For the second phase, when the look angle is outside the switching boundary, a new guidance law is derived to keep the look angle within the FOV by employing a Lyapunov-like function based on sliding-mode control methodology. The appropriate determination of the switching boundary is an important issue. The idea behind selecting the switching boundary is to use the PNG law as much as possible, and to make the missile stay in the lock-on condition. A lock-on guidance (LOG) is proposed as another approach to solve the problem of narrow FOV, based on the concept of the pursuit guidance (PG) law. In order to derive the LOG law, we use a Lyapunov-like function based on the sliding-mode control methodology. An advantage of the LOG law is that a missile guided by the LOG law can intercept a target with a very narrow FOV of the strapdown seeker. Because such a seeker often has to be implemented for more accurate measurements, this kind of guidance law is needed to prepare for such a situation. The LOG law is simple and has good performance against a target with high speed.Abstract i Contents iii List of Figures vi List of Tables x Chapter 1. Introduction 1 1.1 Background and Motivations 1 1.2 Contents of the Research 6 Chapter 2. Preliminary Survey 10 2.1 Survey on Guidance Laws 10 2.1.1 Classical Guidance Laws 10 2.1.1.1 Pursuit Guidance Law 12 2.1.1.2 Constant Bearing Course Guidance Law 13 2.1.1.3 Line-of-Sight Guidance Law 13 2.1.1.4 Proportional Navigation Guidance Law 16 2.1.2 Modern Guidance Laws 23 2.1.2.1 Optimal-Control-Based Guidance Law 24 2.1.2.2 Predictive Guidance Law 27 2.1.2.3 Game-Theory-Based Guidance Law 30 2.1.2.4 Sliding-Mode-Control-Based Guidance Law 31 2.1.3 Summary 32 2.2 Survey on Missile Seekers 33 2.2.1 Gimbal Seeker 34 2.2.2 Strapdown Seeker 35 2.2.3 Summary 36 2.3 Remarks and Discussions 37 Chapter 3. The Proposed Guidance Laws 40 3.1 Hybrid Guidance Law 40 3.1.1 Problem Statement 41 3.1.2 The Overall Scheme 46 3.1.3 Guidance Law for the First Phase 48 3.1.4 Guidance Law for the Second Phase 48 3.1.5 Switching Boundary Estimation 50 3.2 Lock-on Guidance Law 56 3.2.1 Problem Statement 57 3.2.2 The Overall Scheme 62 3.2.3 Derivation 64 Chapter 4. Simulation Results 70 4.1 Hybrid Guidance Law 70 4.1.1 Non-maneuvering Target 70 4.1.2 Maneuvering Target 76 4.2 Lock-on Guidance Law 85 4.1.1 Non-maneuvering Target 85 4.1.2 Maneuvering Target 96 4.3 Comparison of Hybrid Guidance Law and Lock-on Guidance Law 105 Chapter 5. Conclusions 109 5.1 Concluding Remarks 109 5.2 Further Study 111 Bibliography 112 국문초록 123Docto

    ESTIMATION-BASED SOLUTIONS TO INCOMPLETE INFORMATION PURSUIT-EVASION GAMES

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    Differential games are a useful tool both for modeling conflict between autonomous systems and for synthesizing robust control solutions. The traditional study of games has assumed decision agents possess complete information about one another’s strategies and numerical weights. This dissertation relaxes this assumption. Instead, uncertainty in the opponent’s strategy is treated as a symptom of the inevitable gap between modeling assumptions and applications. By combining nonlinear estimation approaches with problem domain knowledge, procedures are developed for acting under uncertainty using established methods that are suitable for applications on embedded systems. The dissertation begins by using nonlinear estimation to account for parametric uncertainty in an opponent’s strategy. A solution is proposed for engagements in which both players use this approach simultaneously. This method is demonstrated on a numerical example of an orbital pursuit-evasion game, and the findings motivate additional developments. First, the solutions of the governing Riccati differential equations are approximated, using automatic differentiation to obtain high-degree Taylor series approximations. Second, constrained estimation is introduced to prevent estimator failures in near-singular engagements. Numerical conditions for nonsingularity are approximated using Chebyshev polynomial basis functions, and applied as constraints to a state estimate. Third and finally, multiple model estimation is suggested as a practical solution for time-critical engagements in which the form of the opponent’s strategy is uncertain. Deceptive opponent strategies are identified as a candidate approach to use against an adaptive player, and a procedure for designing such strategies is proposed. The new developments are demonstrated in a missile interception pursuit-evasion game in which the evader selects from a set of candidate strategies with unknown weights

    Underwater Vehicles

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    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

    Fixed-wing UAV tracking of evasive targets in 3-dimensional space

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    In this thesis, we explore the development of autonomous tracking and interception strategies for single and multiple fixed-wing Unmanned Aerial Vehicles (UAVs) pursuing single or multiple evasive targets in 3-dimensional (3D) space. We considered a scenario where we intend to protect high-value facilities from adversarial groups employing ground-based vehicles and quadrotor swarms and focused on solving the target tracking problem. Accordingly, we refined a min-max optimal control algorithm for fixed-wing UAVs tracking ground-based targets, by introducing constraints on bank angles and turn rates to enhance actuator reliability when pursuing agile and evasive targets. An intelligent and persistent evasive control strategy for the target was also devised to ensure robust performance testing and optimisation. These strategies were extended to 3D space, incorporating three altitude control algorithms to facilitate flexible UAV altitude control, leveraging various parameters such as desired UAV altitude and image size on the tracking camera lens. A novel evasive quadrotor algorithm was introduced, systematically testing UAV tracking efficacy against various evasive scenarios while implementing anti-collision measures to ensure UAV safety and adaptive optimisation improve the achieved performance. Using decentralised control strategies, cooperative tracking by multiple UAVs of single evasive quadrotor-type and dynamic target clusters was developed along with a new altitude control strategy and task assignment logic for efficient target interception. Lastly, a countermeasure strategy for tracking and neutralising non-cooperative adversarial targets within restricted airspace was implemented, using both Nonlinear Model Predictive Control (NMPC) and optimal controllers. The major contributions of this thesis include optimal control strategies, evasive target control, 3D target tracking, altitude control, cooperative multi-UAV tracking, adaptive optimisation, high-precision projectile algorithms, and countermeasures. We envision practical applications of the findings from this research in surveillance, security, search and rescue, agriculture, environmental monitoring, drone defence, and autonomous delivery systems. Future efforts to extend this research could explore adaptive evasion, enhanced collaborative UAV swarms, machine learning integration, sensor technologies, and real-world testing

    Parallel evolutionary programming techniques for strategy optimisation in air combat scenarios

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    Air combat between fighter missiles and aircraft can be categorised as a pursuit-evasion problem. One aircraft acts as a pursuer and the other as an evader. Generally, the pursuer will try to capture the evader as quickly as possible and the evader tries to evade capture for as long as possible. For an experienced human pilot, it is trivial to discuss this methodology, but to simulate it, the mathematics involved is very complex and difficult to implement in a computer environment. Classical methods, though very accurate in their analysis, are not suited to solve a complex 6DOF pursuit-evasion problem and they have limitations in representing real-world problems such as discontinuities, discrete, stochastic, chaotic, temporal information or lack of information. In this thesis, evolutionary programming (EP) is applied to determine the optimum maneuvering strategy for an aircraft (evader) to avoid interception by an incoming missile (pursuer). EP is a class of algorithms known as Evolutionary Algorithm (EA). EA has an ability to find an optimal solution in a complex problem which involves discontinuities, discrete, nondifferential parameters and noise. In addition, the methodology was implemented on parallel computer architecture to improve the computing time and expanding the search space. A sensitivity analysis was carried out to determine the best configuration and to understand the effect of parameters, such as number of processors, population size, number of generations, etc., on the results. The effects of sensor and instrument errors were also considered. The method enabled feasible solutions to be found in a relatively short period of time. However, the ability to search for feasible solutions is dependent on various parameters such as initial conditions, aircraft configurations and aerodynamic constraints. It is concluded that, in general, EP is able to determine feasible maneuvering strategies for an evader to avoid interception with and without instrument errors. The methodology has the potential to be used as a training tool for pilots in air combat or as an intelligent engagement strategy for autonomous systems, such as Unmanned Air Combat Vehicles (UCAV)

    Compilation of thesis abstracts, June 2007

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    NPS Class of June 2007This quarter’s Compilation of Abstracts summarizes cutting-edge, security-related research conducted by NPS students and presented as theses, dissertations, and capstone reports. Each expands knowledge in its field.http://archive.org/details/compilationofsis109452750

    Aeronautical engineering: A continuing bibliography with indexes (supplement 247)

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    This bibliography lists 437 reports, articles, and other documents introduced into the NASA scientific and technical information system in December, 1989. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    Multi-attribute tradespace exploration for survivability

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 235-249).Survivability is the ability of a system to minimize the impact of a finite-duration disturbance on value delivery (i.e., stakeholder benefit at cost), achieved through (1) the reduction of the likelihood or magnitude of a disturbance, (2) the satisfaction of a minimally acceptable level of value delivery during and after a disturbance, and/or (3) a timely recovery. Traditionally specified as a requirement in military systems, survivability is an increasingly important consideration for all engineering systems given the proliferation of natural and artificial threats. Although survivability is an emergent system property that arises from interactions between a system and its environment, conventional approaches to survivability engineering are reductionist in nature. Furthermore, current methods neither accommodate dynamic threat environments nor facilitate stakeholder communication for conducting trade-offs among system lifecycle cost, mission utility, and operational survivability. Multi-Attribute Tradespace Exploration (MATE) for Survivability is introduced as a system analysis methodology to improve the generation and evaluation of survivable alternatives during conceptual design. MATE for Survivability applies decision theory to the parametric modeling of thousands of design alternatives across representative distributions of disturbance environments. To improve the generation of survivable alternatives, seventeen empirically-validated survivability design principles are introduced. The general set of design principles allows the consideration of structural and behavioral strategies for mitigating the impact of disturbances over the lifecycle of a given encounter.(cont.) To improve the evaluation of survivability, value-based metrics are introduced for the assessment of survivability as a dynamic, continuous, and path-dependent system property. Two of these metrics, time-weighted average utility loss and threshold availability, are used to evaluate survivability based on the relationship between stochastic utility trajectories of system state and stakeholder expectations across nominal and perturbed environments. Finally, the survivability "tear(drop)" tradespace is introduced to enable the identification of inherently survivable architectures that efficiently balance performance metrics of cost, utility, and survivability. The internal validity and prescriptive value of the design principles, metrics, and tradespaces comprising MATE for Survivability are established through applications to the designs of an orbital transfer vehicle and a satellite radar system.by Matthew G. Richards.Ph.D
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