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Adaptive Radau pseudo-spectral optimization for descending trajectory of a hypersonic cruise vehicle

Aerospace Systems 2020年第4期3卷 275-286页

作者： Feng, Xinle Lv, Yali Gao, Yang Li, Yuankai Province Key Laboratory of Aircraft Swarm Intelligent Sensing and Cooperative Control University of Electronic Science and Technology of China Chengdu 611731 China

During descending flight of a hypersonic cruise vehicle (HCV), the flight environment is complicated due to the drastically changed atmosphere. It is necessary for the flight trajectory to perform accurate and fast optimization. To solve the nonlinear optimization problem, in this paper, a global adaptive Radau pseudo-spectral method, which is introduced with an hp adaptive strategy (p method to increase the number of points in time interval and h method to refine the interval) is presented. The maximum range and the shortest engagement time are considered, respectively, as performance index to optimize controlling of the attack angle. Using Lagrange interpolation polynomial approximation, the optimal control problem is transformed into a problem of nonlinear programming and solved by a sequence quadratic programming algorithm. Simulation results have shown that the presented method has high computational efficiency and desirable accuracy, with the flying constraints satisfied. It is an effective trajectory optimization method for HCVs. © 2020, Shanghai Jiao Tong University.

关键词： Adaptive Radau pseudo-spectral method Aerodynamic data fitting nonlinear programming Optimal control Trajectory optimization

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Reduced-rank Least Squares Parameter Estimation in the Presence of Byzantine Sensors 54

Reduced-rank Least Squares Parameter Estimation in the Prese...

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54th Annual Conference on Information Sciences and Systems (CISS)

作者： Nagananda, K. G. Blum, Rick S. Koppel, Alec Lehigh Univ Dept ECE Bethlehem PA 18015 USA US Army Res Lab Informat Sci Div Adelphi MD 20783 USA

ISBN: (纸本)9781728140841

In this paper, we study the impact of the presence of byzantine sensors on the reduced-rank linear least squares (LS) estimator. A sensor network with N sensors makes observations of the physical phenomenon and transmits them to a fusion center which computes the LS estimate of the parameter of interest. It is well-known that rank reduction exploits the bias-variance tradeoff in the full-rank estimator by putting higher priority on highly informative content of the data. The low-rank LS estimator is constructed using this highly informative content, while the remaining data can be discarded without affecting the overall performance of the estimator. We consider the scenario where a fraction 0 <= alpha <= 1 of the N sensors are subject to data falsification attack from byzantine sensors, wherein an intruder injects a higher noise power (compared to the unattacked sensors) to the measurements of the attacked sensors. Our main contribution is an analytical characterization of the impact of data falsification attack of the above type on the performance of reduced-rank LS estimator. In particular, we show how optimally prioritizing the highly informative content of the data gets affected in the presence of attacks. A surprising result is that, under sensor attacks, when the elements of the data matrix are all positive the error performance of the low-rank estimator experiences a phenomenon wherein the estimate of the mean-squared error comprises negative components. A complex nonlinear programming-based recipe is known to exist that resolves this undesirable effect;however, the phenomenon is oftentimes considered very objectionable in the statistical literature. On the other hand, to our advantage this effect can serve to detect cyber attacks on sensor systems. Numerical results are presented to complement the theoretical findings of the paper.

关键词： nonlinear programming

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Linear Regression Models Applied to Spacecraft Imperfect Information Pursuit-Evasion Differential Games

Linear Regression Models Applied to Spacecraft Imperfect Inf...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Linville, Dax A. Hess, Joshuah A. Air Force Inst Technol 2950 Hobson Way Wright Patterson AFB OH 45433 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Space based pursuit-evasion differential games can be formulated as optimal control problems in either a deterministic or stochastic sense. By building a linear regression model from a large data set, produced by an indirect heuristic optimization algorithm, one can quickly map pursuer relative starting positions to terminal capture positions and interpolate for capture time. This can be done for arbitrary performance ratios between the pursuer and evader, as well as for arbitrary pursuer starting positions on an initial relative orbit about the evader. A parameter study is performed to analyze the effect of uncertainty in the pursuer starting position on an otherwise deterministic pursuit-evasion differential game in order to showcase the speed and accuracy of the linear regression model.

关键词： Spacecrafts Pontryagin's Maximum Principle Optimization Algorithm Particle Swarm Optimization Satellites Satellite Rendezvous nonlinear programming Unscented Kalman Filter MATLAB General Mission Analysis Tool

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The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage

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JOURNAL OF MODELLING IN MANAGEMENT 2020年第3期15卷 705-725页

作者： Khalilzadeh, Mohammad Karami, Arya Hajikhani, Alborz Pontificia Univ Catolica Peru CENTRUM Catolica Grad Business Sch Lima Peru Sharif Univ Technol Fac Ind Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran

Purpose This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based partial and general coverage of suppliers makes the number of orders of products more realistic. In this model, the weights of suppliers are determined by fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, as a multi-criteria decision analysis method, in the objective function. Also, the authors consider the parameters related to delays as triangular fuzzy numbers. Findings A small-sized numerical example is provided to clearly show the proposed model. The exact epsilon constraint method is used to solve this given multi-objective combinatorial optimization problem. Subsequently, the sensitivity analysis is conducted to testify the proposed model. The obtained results demonstrate the validity of the proposed multiple objectives mixed integer mathematical programming model and the efficiency of the solution approach. Originality/value In real-life situations, supplier selection parameters are uncertain and incomplete. Hence, the fuzzy set theory is used to tackle uncertainty. In this paper, a multi-objective supplier selection problem is formulated taking into consideration the coverage of suppliers and suppliers' weights. Integrating coverage of suppliers to select and allocate the order to them can be mentioned as the main contribution of this stu

关键词： Decision-making Optimisation nonlinear programming Multi-criteria programming Fuzzy set Epsilon-constraint method

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Human Motion Capture Based on Kinect and IMUs and Its Application to Human-Robot Collaboration 5

Human Motion Capture Based on Kinect and IMUs and Its Applic...

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5th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Zhang, Junhao Li, Peng Zhu, Tenghui Zhang, Wen-An Liu, Steven Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China TU Kaiserslautern Dept Elect & Comp Engn D-67663 Kaiserslautern Germany

ISBN: (纸本)9781728164793

In this paper, a nonlinear optimization solver is proposed to establish the human upper body motion capture system, including the orientation of each bone joint and the global position of the hip bone. 5 IMUs and one Kinect are used, the rotation data and acceleration data of IMUs, Kinect skeleton position data and human pose prior are fused in a non-linear optimization way. The method proposed in this paper combines the characteristics of Kinect data with high accuracy and IMU data with stability, which can make up for the accuracy of human pose capture in dynamic, magnetically disturbed and occlusion conditions. In order to verify the practicability of the human motion capture system proposed in this paper, the system is firstly applied to real-time human motion capture, then a simple human-robot collaboration (HRC) case is implemented, which is very common in modern collaborative medical field. The experimental results show that the proposed human motion capture system can achieve stable human motion measurement, which can meet the needs of HRC scenarios.

关键词： nonlinear programming

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Selective Maintenance Optimization Problem In Systems Under Repairpersons Availability 7

Selective Maintenance Optimization Problem In Systems Under ...

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7th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Chaabane, K. Khatab, A. Diallo, C. Venkatadri, U. Aghezzaf, E-H Univ Lorraine LGIPM F-57000 Metz France Dalhousie Univ Dept Ind Engn Halifax NS Canada Univ Ghent Dept Ind Syst Engn & Prod Design Ghent Belgium Flanders Make Ind Syst Engn ISyE Limburg Belgium

ISBN: (纸本)9781728159539

Industrial systems are sometimes designed to operate their missions with finite breaks scheduled between two consecutive missions. During the break, maintenance actions can be carried out. Given the limited break duration, in addition to other limited maintenance resources, not all components can be maintained. To meet the required performance of the system during the next mission, it is often required to select components to be maintained. This decision making problem is known as the selective maintenance problem (SMP). In the literature, the existing SM models merely rely on the assumption that repair channels are always available to perform their maintenance duties. The present paper introduces a novel and more realistic formulation of the SMP where the unavailability of the repair channels is accounted for. Two integrated non-linear programming models are developed and solved, without loss of generality, in a series-parallel system under multiple repair channels. The results derived allow to show the validity and the accuracy of the proposed approach.

关键词： nonlinear programming

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Geometrically reconstructing laser Coulomb-exploded molecules 31

Geometrically reconstructing laser Coulomb-exploded molecule...

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31st International Conference on Photonic, Electronic and Atomic Collisions (ICPEAC)

作者： Singh, M. D. Ramadhan, A. Tian, K. Sanderson, J. Wales, B. Karimi, R. Beaulieu, S. Liu, W. K. Kieffer, J. C. Legar, F. Univ Waterloo Waterloo ON N2L 3G1 Canada Inst Natl Rech Sci Varennes PQ J3X 1S2 Canada Amirkabir Univ Technol Tehran 158754413 Iran

Geometrical reconstructions are performed for Carbonyl Sulfide (OCS) through Coulomb Explosion Imaging (CEI) employing intense femtosecond laser ionization with pulse durations 7 fs, 30 fs, 60 fs, 100 fs, and 200 fs, using two methods that significantly differ in approach. Firstly, a look up table is employed to reconstruct OCS (2, 2, 2) channel and highlight the presence of degenerate regions. Following this a more sophisticated constrained nonlinear optimization approach improves on precision and gives an indication of uncertainty. Results are compared with equilibrium geometry.

关键词： nonlinear programming

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Longitudinal control of transition to powered flight for a parachute-dropped multirotor

Longitudinal control of transition to powered flight for a p...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Opazo, Tomas, I Langelaan, Jack W. Penn State Univ Dept Aerosp Engn University Pk PA 16802 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

The problem of controlling the safe transition of a multirotor vehicle between its release from a parachute to the moment it reaches steady state flight is analyzed. The problems of optimal trajectory, controller tuning, safety and stability to initial conditions are also studied. The proposed solution involves a two step process to find a safe controller. First, an optimal control problem is defined and then transcribed, using a direct collocation method, into a nonlinear programming problem. Second, the trajectory error for a subset of initial conditions is calculated, and the worst case is defined as the overall cost. This emerging Min-Max problem is then solved using particle swarm optimization to obtain the best set of controller gains. In order to evaluate performance, a cost function based on margins between the vehicle's state and their respective maximum allowable values was defined. Monte Carlo simulations were ran over the space of possible initial conditions. The combination of optimal trajectory and particle swarm derived controller gains results in an average state cost reduction of 23% when compared to a near-hover controller derived using Ziegler-Nichols method.

关键词： Multicopter Longitudinal Control Particle Swarm Optimization Monte Carlo Simulation nonlinear programming Trajectory Optimization Collocation Method Cost Reduction Aerodynamic Torque Electronic Speed Control

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Mesh Refinement Method for Solving Bang-Bang Optimal Control Problems Using Direct Collocation

Mesh Refinement Method for Solving Bang-Bang Optimal Control...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Agamawi, Yunus M. Hager, William W. Rao, Anil, V Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA Univ Florida Dept Math Gainesville FL 32611 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

A mesh refinement method is developed for solving bang-bang optimal control problems using direct collocation. The method starts by finding a solution on a coarse mesh. Using this initial solution, the method then determines automatically if the Hamiltonian is linear with respect to the control, and, if so, estimates the locations of the discontinuities in the control. The switch times are estimated by determining the roots of the switching functions, where the switching functions are determined using estimates of the state and costate obtained from the collocation method. The accuracy of the switch times is then improved on subsequent meshes by dividing the original optimal control problem into multiple domains and including variables that define the locations of the switch times. While in principle any collocation method can be used, in this research the previously developed Legendre-Gauss-Radau collocation method is employed because it provides an accurate approximation of the costate which in turn improves the approximation of the switching functions. The method of this paper is designed to be used with a previously developed mesh refinement method in order to accurately approximate the solution in segments where the solution is smooth. The method is demonstrated on three examples where it is shown to accurately determine the switching structure of a bang-bang optimal control problem. When compared with previously developed mesh refinement methods, the results demonstrate that the method developed in this paper improves computational efficiency when solving bang-bang optimal control problems.

关键词： Bang Bang Control Adaptive Mesh Refinement nonlinear programming Free Flying Robots MATLAB Finite Element Method Robot Arms Boundary Value Problems Runge Kutta Methods Computing

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Multi-objective Optimization for Guaranteed Delivery in Video Service Platform 20

Multi-objective Optimization for Guaranteed Delivery in Vide...

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26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)

作者： Hang Lei Zhao, Yin Cai, Longjun Alibaba Grp Beijing Peoples R China

ISBN: (纸本)9781450379984

Guaranteed-Delivery (GD) is one of the important display strategies for the IP videos in video service platform. Different from the traditional recommendation strategy, GD requires the delivery system to guarantee the exposure amount (also called impressions in some works) for the content, where the amount generally comes from the purchase contract or business consideration of the platform. In this paper, we study the problem of how to maximize certain gains, such as video view (VV) or fairness of different contents (CTR variations between contents) under the GD constraints. We formulate such a problem as a constrained nonlinear programming problem, in which the objectives are to maximize the total VVs of contents and the exposure fairness between contents. In order to capture the trends of VV versus the impression number (page views, PV) for each video content, we propose a parameterized ordinary differential equation (ODE) model, and the parameters of the ODE are fitted by the video historical PV and CLICK datas. To solve the constrained nonlinear programming, we use genetic algorithm (GA) with a specific design of coding scheme considering the ODE constraints. The empirical study based on real-world data and online test on *** verifies the effectiveness and superiority of our approach compared with the state of the art in the industry practice.

关键词： Guaranteed-Delivery strategy video service platform ordinary differential equation nonlinear programming genetic algorithm

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