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Novel Approach to Improve Stability and convergence of Flowfield Solution Processes: Mode Multigrid

AIAA JOURNAL 2023年第8期61卷 3496-3506页

作者： Wang, XuKun Liu, Yilang Zhang, Weiwei Northwestern Polytech Univ Sch Aeronaut Natl Key Lab Sci & Technol Aerodynam Design & Res Xian 710072 Peoples R China

In the field of computational fluid dynamics, stability and convergence problems are often encountered when solving the governing equation. This paper studies the effect of the mode multigrid on the stability and convergence of iterative algorithms. By further analyzing the mechanism for accelerating the convergence of mode multigrid, a new adaptive mode multigrid (AMMG) is proposed, and an adaptive selection criterion is formulated for the parameters of dynamic modal decomposition, which can accurately identify and filter out the unstable modes in the flowfield, thus efficiently obtaining the accurate steady solution. In the cases of laminar flow past circular cylinder and turbulent flow past airfoil, the AMMG significantly improves the stability of the iterative algorithm;in the case of transonic flow past airfoil, the AMMG solves the problem of shock wave shaking during the iteration, and the convergence is significantly improved. In summary, the AMMG method significantly enhances the stability and convergence of the iterative algorithm, and can be used as an effective convergence-preserving computation strategy.

关键词： Computational Fluid Dynamics Airfoil Finite Volume Formulation Reynolds Averaged Navier Stokes Numerical algorithms algorithms convergence Numerical Stability

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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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Tackling Nonconvex Collision Avoidance Constraints for Optimal Trajectory Planning Using Saturation Functions

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第6期45卷 1002-1016页

作者： Zhao, Zichen Shang, Haibin Wei, Bingwei Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China Beijing Inst Technol Key Lab Dynam & Control Flight Vehicle Beijing 100081 Peoples R China

The problem of optimal trajectory planning with nonconvex collision avoidance constraints is discussed in this paper. The trajectory planning algorithm aims to generate a feasible trajectory with specified performance indexes to reduce collisions of aerospace vehicles in the presence of second-order smooth obstacles. The algorithm design that manages such mission scenarios is challenging because of the stringent avoidance constraints of various nonconvex types, especially considering the requirements of efficient computation. This problem is addressed within the sequential convex programming (SCP) framework by utilizing the characteristics of saturation functions. The introduction of the saturation function is found to significantly improve the convergence of the SCP algorithm by overcoming the drawbacks of potential interruptions from the iteration process and controlling the search directions for successive solutions. Theoretical analyses are performed to guarantee that the original constraints are satisfied and to ensure the iterative solution searches in the directions of the true optimal solution. Under multiple randomly generated test environments, the applications of the proposed approach in highly constrained aircraft path planning problems and spacecraft rendezvous operations are numerically simulated by comparing two representative conventional SCP-based methods to demonstrate the effectiveness, efficiency, and convergence of the proposed methodology.

关键词： Iterative Solution Path Planning Spacecraft Rendezvous algorithms convergence Nonlinear Programming UAV Fuel Consumption Bang Bang Control Obstacle Avoidance Numerical Simulation

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Autonomous Maneuver Targeting Around Small Bodies Using Continuous-Thrust Propulsion

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第3期45卷 499-516页

作者： Kuettel, Donald H. H. McMahon, Jay W. Univ Colorado Orbital Res Cluster Celestial Applicat Smead Dept Aerosp Engn Boulder CO 80303 USA

This paper presents a novel fuel-efficient continuous-thrust maneuver targeting (CTMT) algorithm that is capable of planning finite, continuous maneuvers in a larger autonomous spacecraft guidance architecture. This is accomplished using a constant-thrust bilinear tangent guidance law in conjunction with an optimal Lambert algorithm and a Newton-Raphson predictor-corrector targeting scheme. This simple approach is capable of planning a plethora of different free-time and fixed-time single-burn, burn-coast intercept, or burn-coast-burn bilinear tangent maneuvers from an initial state/orbit to a desired state/orbit. For the study case of asteroid Bennu, when used with thrust levels that are greater than 5% of the surface acceleration of asteroid Bennu, the CTMT algorithm is able to converge on 99% of orbital transfers initiated from a circular, 1.5 km, terminator orbit. Furthermore, many of the continuous-thrust maneuvers calculated by the CTMT algorithm are the optimal constant-thrust trajectories between two states in the small-body dynamical environment, and they are able to be calculated hundreds of times faster with the CTMT algorithm than with state-of-the-art nonlinear optimization algorithms. Ultimately, the CTMT algorithm shows promise as a candidate for future autonomous guidance applications.

关键词： Thrust Propulsion System Optimal Impulsive Maneuvers Broyden Fletcher Goldfarb Shanno Guidance Laws Asteroids Lambert Algorithm Spacecraft Trajectories Sparse Nonlinear Optimizer algorithms convergence

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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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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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Onboard Real-Time Generation of Launch Vehicle Abort Orbits

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2021年第8期44卷 1541-1549页

作者： Hao, Zeming Zhang, Ran Beihang Univ Sch Astronaut Beijing 100191 Peoples R China

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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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Filter Initialization with Three-Dimensional Lidar Images in Proximity to Small Bodies

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第2期43卷 310-318页

作者： Dietrich, Ann B. McMahon, Jay W. Univ Colorado Boulder CO 80309 USA Charles Stark Draper Lab Precis Nav Cambridge MA 02139 USA 431 UCB Ann & HJ Smead Aerosp Engn Sci Boulder CO USA

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