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Real-Time Attitude-Independent Magnetometer Bias Estimation for Spinning Spacecraft

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2018年第1期41卷 276-279页

作者： Soken, Halil Ersin Sakai, Shin-ichiro Japan Aerosp Explorat Agcy Inst Space & Astronaut Sci Chuo Ku Yoshinodai 3-1-1 Sagamihara Kanagawa 2525210 Japan

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Impact-Angle-Constrained Suboptimal Model Predictive Static Programming Guidance of Air-to-Ground Missiles

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第1期35卷 153-164页

作者： Oza, Harshal B. Padhi, Radhakant Indian Inst Sci Dept Aerosp Engn Bangalore 560012 Karnataka India

A nonlinear suboptimal guidance law is presented in this paper for successful interception of ground targets by air-launched missiles and guided munitions. The main feature of this guidance law is that it accurately satisfies terminal impact angle constraints in both azimuth as well as elevation simultaneously. In addition, it is capable of hitting the target with high accuracy as well as minimizing the lateral acceleration demand. The guidance law is synthesized using recently developed model predictive static programming (MPSP). Performance of the proposed MPSP guidance is demonstrated using three-dimensional (3-D) nonlinear engagement dynamics by considering stationary, moving, and maneuvering targets. Effectiveness of the proposed guidance has also been verified by considering first. order autopilot lag as well as assuming inaccurate information about target maneuvers. Multiple munitions engagement results are presented as well. Moreover, comparison studies with respect to an augmented proportional navigation guidance (which does not impose impact angle constraints) as well as an explicit linear optimal guidance (which imposes the same impact angle constraints in 3-D) lead to the conclusion that the proposed MPSP guidance is superior to both. A large number of randomized simulation studies show that it also has a larger capture region.

关键词： Air to Ground Missile Guidance System Trajectory Optimization Yaw Model Predictive Control Autopilot Aerodynamic Force Proportional Navigation Variable Structure Control algorithms convergence

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Optimal Selection of the Coefficient Matrix in State-Dependent Control Methods

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2015年第5期38卷 861-873页

作者： Topputo, Francesco Miani, Martino Bernelli-Zazzera, Franco Politecn Milan Dept Aerosp Sci & Technol I-20156 Milan Italy

This paper presents a state-dependent method for solving nonlinear, control-affine, finite-time optimal control problems. The problem is set in a state-dependent form and solved as a sequence of time-varying linear-quadratic regulators, for which an approach based on state transition matrices has been developed. The novelty of the method consists of the possibility of managing a number of different state-dependent coefficient factorizations of the uncontrolled dynamics, for use with various state-dependent control methods. At each iteration, a nonlinear programming problem is solved to select the state-dependent combination that maximizes the controllability, so minimizing the control effort and, likely, the objective function. Test problems are presented to show the effectiveness of the method.

关键词： Linear Quadratic Regulator Transversality Condition Nonlinear Programming State Dependent Riccati Equation Lagrange Multipliers algorithms convergence Nonlinear Dynamics Earth Boundary Value Problems Spline Interpolation

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SPACE STRUCTURE CONTROL DESIGN BY VARIANCE ASSIGNMENT

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 1985年第4期8卷 454-462页

作者： SKELTON, RE DELORENZO, M USAF ACAD COLORADO SPRINGSCO 80840

algorithms designed to assign specified root-mean-squared values to multiple inputs or multiple outputs are constructed. The algorithms are used to select sensors and actuators from an admissible set of types and locations, and to determine actuator design requirements for the control of flexible structures to meet specified output variance constraints. Numerical properties of the convergence of the algorithms are demonstrated for NASA's 64-m hoop-column antenna.

关键词： Large Space Structures Actuators Antennas Flexible Structures Closed Loop System Spacecraft Missions Linear Quadratic Gaussian algorithms convergence Cost Analysis Finite Element Modeling

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Tour planning for an unmanned air vehicle under wind conditions

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2007年第5期30卷 1299-1306页

作者： McNeely, Rachelle L. Iyer, Ram V. Chandler, Phillip R. Texas Tech Univ Dept Math & Stat Lubbock TX 79409 USA USAF Res Lab Wright Patterson AFB Wright Patterson AFB OH 45433 USA

A very important subproblem in the task assignment problem for unmanned air vehicles is the evaluation of costs for the state transitions of a directed graph. Usually a Dubins vehicle flying in the absence of wind is considered in the computation of costs. However, when a prevailing wind vector field is considered, the costs taken on very different values and the task assignment problem can have very different solutions. In this paper, we consider the problem of constructing minimum-time trajectories for a Dubins vehicle in the presence of a time-varying wind vector field. We present results on the existence and uniqueness of minimum-time solutions for a Dubins vehicle flying in a general time-varying wind vector field under some technical conditions. These results extend the conclusions of the well-known Dubins theorem. We also propose an algorithm for obtaining the minimum-time solution for an unmanned air vehicle and prove its convergence. We also present the results of numerical experiments that show that the importance of considering wind vector fields while planning the tour for an unmanned air vehicle.

关键词： Air Vehicle Micro Air Vehicle Numerical Stability Coordinate Transformations Pontryagin's Maximum Principle Air Force Research Laboratory algorithms convergence Boundary Value Problems Numerical algorithms Euler Equations

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Derivative-Free Line-Search Algorithm for Multi-Fidelity Optimization

Derivative-Free Line-Search Algorithm for Multi-Fidelity Opt...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Liuzzi, Giampaolo Lucidi, Stefano Rinaldi, Francesco Pellegrini, Riccardo Serani, Andrea Diez, Matteo CNR CNR IASI Inst Syst Anal & Comp Sci Via Taurini 19 I-00185 Rome Italy Sapienza Univ Dept Comp Control & Management Engn Ruberti Via Ariosto 25 I-00185 Rome Italy Univ Padua Dept Math Via Trieste 63 I-35131 Padua Italy CNR CNR INM Inst Marine Engn Via Vallerano 139 I-00128 Rome Italy

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

The paper presents a multi-fidelity coordinate-search derivative-free algorithm for non-smooth constrained optimization (MF-CS-DFN), in the context of simulation-based design optimization (SBDO). The objective of the work is the development of an optimization algorithm able to improve the convergence speed of the SBDO process. The proposed algorithm is of a line-search type and can handle objective function evaluations performed with variable accuracy. The algorithm automatically selects the accuracy of the objective function evaluation based an internal steplength parameter. The MF-CS-DFN algorithm starts the optimization with low accuracy and low-cost evaluations of the objective function, then the accuracy (and evaluation cost) is increased. The method is coupled with a potential flow solver whose accuracy is determined by the computational grid size. No surrogate models are used in the current study. The algorithm is applied to the hull-form optimization of a destroyer-type vessel in calm water using 14 hull-shape parameters as design variables. The optimization aims at the total resistance reduction. Seven refinements of the computational grid are used by the multi-fidelity optimizations. Four setups of the MF-CS-DFN algorithm are tested and compared with an optimization performed only on the finest grid. The results show that three of the tested setups achieve better performance than the high-fidelity optimization, converging to a lower resistance value with a reduced computational cost.

关键词： Surrogate Model Potential Flow Optimization Algorithm Search Algorithm Reynolds Averaged Navier Stokes algorithms convergence SONAR Shape Optimization Gaussian Process Hydrodynamics

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Effectiveness of Surrogate-Based Optimization algorithms for System Architecture Optimization

Effectiveness of Surrogate-Based Optimization Algorithms for...

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AIAA Aviation Forum and Exposition

作者： Bussemaker, Jasper H. Barton, Nathalie Lefebvre, Thierry Ciampa, Pier D. Nagel, Bjoern DLR German Aerosp Ctr Inst Syst Architectures Aeronaut Aircraft Design & Syst Integrat Hamburg Germany Univ Toulouse DTIS ONERA Informat Proc & Syst Dept Toulouse France DLR German Aerosp Ctr Inst Syst Architectures Aeronaut Hamburg Germany

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

The design of complex system architectures brings with it a number of challenging issues, among others large combinatorial design spaces. Optimization can be applied to explore the design space, however gradient-based optimization algorithms cannot be applied due to the mixed-discrete nature of the design variables. It is investigated how effective surrogate-based optimization algorithms are for solving the black-box, hierarchical, mixed-discrete, multiobjective system architecture optimization problems. Performance is compared to the NSGAII multi-objective evolutionary algorithm. An analytical benchmark problem that exhibits most important characteristics of architecture optimization is defined. First, an investigation into algorithm effectiveness is performed by measuring how accurately a known Pareto-front can be approximated for a fixed number of function evaluations. Then, algorithm efficiency is investigated by applying various multi-objective convergence criteria to the algorithms and establishing the possible trade-off between result quality and function evaluations needed. Finally, the impact of hidden constraints on algorithm performance is investigated. The code used for this paper has been published.

关键词： Optimization Algorithm Multi Objective Evolutionary algorithms Black Box algorithms convergence Surrogate Model Gaussian Process Design of Experiments Computational Fluid Dynamics Systems Engineering Genetic Algorithm

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Enhanced 3D Localization on Venus: A Map Matching and Particle Filtering Approach

Enhanced 3D Localization on Venus: A Map Matching and Partic...

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AIAA SciTech Forum

作者： Cottrill, Heath Gu, Yu West Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26506 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper presents a localization solution for an aerial robot operating in the atmosphere of Venus. The system estimates its state using an onboard inertial navigation system (INS), which may drift over time. To compensate for this error, height and pressure measurements are collected, compared to a known dataset using map matching, and integrated using particle filtering. Simulation results show that the algorithm, when compared to the INS, improves the estimation of all states, including attitude, velocity, and position. A sensitivity analysis demonstrates the algorithm's ability to improve localization with inertial measurement unit (IMU) of varying qualities. Furthermore, it is shown to maintain localization with lower quality height and pressure measurements and improve it when better ones are available. Nonetheless, the decrease in sensor quality results in a lower convergence rate, posing limitations.

关键词： Inertial Navigation System Inertial Measurement Unit Inertial Sensor algorithms convergence Aerial Robots Aerobot Accelerometer Altimeter Gyroscopes Planets

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Iteratively feasible optimal spacecraft guidance with non-convex path constraints using convex optimization

Iteratively feasible optimal spacecraft guidance with non-co...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Misra, Gaurav Bai, Xiaoli Rutgers State Univ Dept Mech & Aerosp Engn Piscataway NJ 08854 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

In this paper, a convex optimization based approach is proposed for solving the relative spacecraft guidance problem with non-convex obstacle avoidance constraints akin to sequential convex programming approaches proposed in literature, which require solving a sequence of simpler convex programs. However, contrary to existing approaches, the method proposed in this paper ensures that the iterates remain feasible as long as the first iterate is feasible and achieves monotonic convergence of the objective function. Significantly, the proposed methodology leads to anytime solutions, i.e., the computation can be aborted whenever needed and still return a quality solution, which is highly desirable for real-time operations due to potential unexpected situations and limited computation resources. However, most existing methods only guarantee the correctness of the solution when they converge, whereas preconvergence solution obtained can be useless or even dangerous when applied. The underlying methodology assumes linear dynamics with polynomial path constraints and relies on the convex-concave procedure and sum-of-squares programming to obtain tractable inner convex approximations. To validate the efficacy of the proposed method, a relative spacecraft fuel optimal guidance problem under Clohessy-Hill-Wiltshire (CHW) dynamics is studied under plume impingement, keep-out zones, and obstacle avoidance constraints.

关键词： Nonlinear Programming Spacecraft Trajectory Optimization Model Predictive Control Optimal Control algorithms convergence Sequential Quadratic Programming Pseudo Spectral Method Boundary Value Problems Guidance Laws Rockets

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Planning Trajectories for a Robot Manipulator with Tool Orientation in Semiautomatic Control Systems 2nd

Planning Trajectories for a Robot Manipulator with Tool Orie...

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2nd International Conference on Cyber-Physical Systems and Control, CPS and C 2021

作者： Rostova, Ekaterina N. Rostov, Nikolay V. St. Petersburg199178 Russia Peter the Great St. Petersburg Polytechnic University Polytechnicheskaya St. 29 St. Petersburg195251 Russia

ISBN: (纸本)9783031208744

Today, due to digitalization, it is important to extend the functional capabilities of state-of-the-art robot control systems. In the paper, we consider digital semiautomatic control systems of robot manipulators with tool position and orientation set on a tool’s trajectory by a human operator using multi-degree-of-freedom master handles. The programs for preliminary planning of the robot links’ trajectories in offline mode were developed with the use of iterative numerical methods. Known theoretical methods of tool orientation are discussed. The problems of planning with different ways of tool orientation setting are formulated. We analyzed iterative algorithms with and without calculating the robot’s Jacobi matrix. The algorithms based on solving the nonlinear least squares problems in suggested formulations were recommended. Examples of planning link trajectories for a 6-link robot are presented when a tool moves along a square piecewise 3D trajectory. Different techniques of tool orientation setting on the trajectory pieces were applied. Testing of planned trajectories was carried out using the robot animated model. The results of the work can be implemented in computer simulators for study and design of modern digital semiautomatic control systems of robot manipulators. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： algorithms convergence Human operator Inverse kinematic problem Iterative numerical methods Nonlinear least-squares problem Planning algorithms testing Robot link trajectory planning Robot manipulator Robot tool Semiautomatic control systems Tool orientation setting Tool position

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