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Collision Avoidance in Cooperative Missions: Bezier Surfaces for Circumnavigating Uncertain Speed Profiles

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2019年第8期42卷 1779-1796页

作者： Mehdi, Syed Bilal Choe, Ronald Hovakimyan, Naira Univ Illinois Dept Mech Sci & Engn 1206 West Green St Urbana IL 61801 USA Univ Illinois Dept Aerosp Engn 104 South Wright St Urbana IL 61801 USA

This paper presents a collision-prediction and avoidance algorithm for multivehicle cooperative missions. Using Bezier surfaces, the algorithm avoids time discretization of trajectories and is capable of considering uncertainties in speed profiles. The algorithm runs independently onboard each vehicle and, upon detection of a possible collision, replans its trajectory. Under a few assumptions, the modified trajectory is guaranteed to avoid the predicted collision as well as satisfy mission specific constraints. The deviations in position, velocity, and acceleration caused by the avoidance maneuver are small and respect bounds that can be computed offline. These bounds can be used during the mission-planning phase to guarantee satisfaction of vehicle dynamic constraints and intervehicle safety distances even during collision-avoidance maneuvers.

关键词： Vehicle Trajectories Multirotor Automatic Dependent Surveillance Broadcast National Airspace System Mixed Integer Linear programming Optimal Control Ground Station sequential quadratic programming Unmanned Aerial Vehicle Model Predictive Control

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A novel application of integrated grasshopper optimization heuristics for attenuation of noise interferences

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AIN SHAMS ENGINEERING JOURNAL 2022年第2期13卷 101536-101536页

作者： Khan, Wasim Ullah Raja, Muhammad Asif Zahoor He, Yigang Chaudhary, Naveed Ishtiaq Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan COMSATS Univ Islamabad Dept Elect & Comp Engn Attock Campus Attock 43600 Pakistan Int Islamic Univ Dept Elect Engn Islamabad Pakistan

Novel application of integrated swarming intelligence computing paradigm is exploited for reliable treatment of nonlinear active noise control (ANC) systems using global search capacity of grasshopper optimization algorithm (GOA) combined with local search efficacy of sequential quadratic programming (SQP), i.e., GOA-SQP. The designed optimization mechanism GOA-SQP is applied to minimize the cost function of ANC controller incorporating the nonlinear Volterra filtering having linear/nonlinear primary/secondary paths in case of different noise interferences of sinusoidal, random, and complex random type signals. The comparison of the results through statistical observations in terms of accuracy, convergence and complexity indices reveals that the GOA-SQP based ANC controllers are operative, resilient and viable.(c) 2021 The Authors. Production and hosting by Elsevier B.V. on behalf of Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Active noise control Grasshopper optimization algorithm sequential quadratic programming System identification Volterra filtering

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3D structure from a single calibrated view using distance constraints

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2004年第6期E87D卷 1527-1536页

作者： Gong, RB Xu, G Ritsumeikan Univ Kusatsu 5258577 Japan

We propose a new method to recover scene points from a single calibrated view using a subset of distances among the points. This paper first introduces the problem and its relationship with the perspective 17 point problem. Then the number of distances required to uniquely recover scene points are explored. The result is then developed into a practical vision algorithm to calculate the initial points' coordinates using distance constraints. Finally SQP (sequential quadratic programming) is used to optimize the initial estimations. It can minimize a cost function defined as the sum of squared reprojection errors while keeping the specified distance constraints strictly satisfied. Both simulation data and real scene images have been used to test the proposed method, and good results have been obtained.

关键词： perspective n point problem single view reconstruction sensitivity analysis sequential quadratic programming

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Parameter Identification for a 3D Heating Process by the Adjoint Method based on Experimental Data

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IFAC-PapersOnLine 2021年第11期54卷 103-108页

作者： Dirk Wolfram Thomas Meurer Chair of Automatic Control Faculty of Engineering Kiel University 24143 Kiel Germany

Model-based control of systems governed by partial differential equations relies on the knowledge of the model parameters. Their determination is complicated by the spatial-temporal process dynamics. In addition the interaction of the process and the (embedded) actuation devices might be subject to uncertainties. This work applies a late-lumping approach for parameter identification given a 3-dimensional heat conduction and heat transfer problem with actuation dynamics represented by a coupled PDE-ODE model. By defining a suitable minimization problem the necessary optimality conditions in terms of adjoint PDE-ODE couplings are determined using variational calculus. In additional gradient information can be directly extracted that is used in course of the numerical evaluation by making use of sequential quadratic programming. For this the Finite-Element method is applied for the forward solution of the model equations and backward solution of the adjoint equations. Data collected at the experimental realization of 3-dimensional heating process for different actuation scenarios is used for evaluation and comparison.

关键词： Parameter identification Heat equation Adjoint Method Actuator dynamics Optimization Finite Element Method Partial Differential Equations sequential quadratic programming

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Planning and Management of a Water Reservoir System Due to Expected Climate Changes

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IFAC Proceedings Volumes 1998年第20期31卷 775-780页

作者： P. Fritsch S. Hopfgarten H. Puta Dept. of Automation and Systems Engineering Technical University of Ilmenau P.O. Box 10 05 65 D-98684 Ilmenau Germany

The paper is dedicated to the problem of planning and management of water resources systems. The tasks are formulated as time-discrete dynamic optimal control problem and transformed to a large-scale structured nonlinear optimisation problem with sparse data structures. The solving procedure is an SQP-type algorithm. Two different hydrological scenarios were investigated applying the proposed approach and compared with an existing reservoir management plan. The simulative management in an extraordinary situation was also performed.

关键词： Model-based control sequential quadratic programming Management Planning Water resources system Hydrological changes

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The

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SIAM Journal on Scientific Computing 2009年第3期31卷 2386-2417页

作者： Nigam Chandra Parida Soumyendu Raha

Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to useful control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerate perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the original problem. The regularization is quantifiable in terms of time step size in the mesh and the regularization parameter. For fully regularized systems the scheme converges linearly in time step size. The method is illustrated with examples.

关键词： 65L80 49J15 65K99 65F99 dynamic optimization high index differential-algebraic equations path constraints sequential quadratic programming

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An automated approach to magnetic divertor configuration design

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NUCLEAR FUSION 2015年第1期55卷 013001-013001页

作者： Blommaert, M. Dekeyser, W. Baelmans, M. Gauger, N. R. Reiter, D. Forschungszentrum Julich Inst Energy & Climate Res Plasma Phys IEK 4 D-52425 Julich Germany Katholieke Univ Leuven Dept Mech Engn B-3001 Louvain Belgium Rhein Westfal TH Aachen Dept Math D-52062 Aachen Germany Rhein Westfal TH Aachen Ctr Computat Engn Sci D-52062 Aachen Germany

Automated methods based on optimization can greatly assist computational engineering design in many areas. In this paper an optimization approach to the magnetic design of a nuclear fusion reactor divertor is proposed and applied to a tokamak edge magnetic configuration in a first feasibility study. The approach is based on reduced models for magnetic field and plasma edge, which are integrated with a grid generator into one sensitivity code. The design objective chosen here for demonstrative purposes is to spread the divertor target heat load as much as possible over the entire target area. Constraints on the separatrix position are introduced to eliminate physically irrelevant magnetic field configurations during the optimization cycle. A gradient projection method is used to ensure stable cost function evaluations during optimization. The concept is applied to a configuration with typical Joint European Torus (JET) parameters and it automatically provides plausible configurations with reduced heat load.

关键词： divertor design edge plasma modelling magnetic topology power deposition sequential quadratic programming parameter optimization

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Structural design optimization of shallow frame structures undergoing large deflections

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AIAA JOURNAL 2004年第12期42卷 2592-2599页

作者： Sedaghati, R Suleman, A Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada Univ Victoria Dept Mech Engn Victoria BC V8W 3P6 Canada

An optimization algorithm for structural design against instability is developed for shallow beam structures undergoing large deflections. The algorithm is based on the maximization of the limit load under specified volume constraint. The analysis for obtaining the limit load involves coupling of axial and bending deformations and is based on the nonlinear finite element analysis using the displacement control technique. The optimization is carried out using both the sequential-quadratic-programming (SQP) and optimality-criterion (OC) techniques, and the results are compared. For the SQP technique, the sensitivity derivatives of the critical load factor are calculated using the adjoint method based on the information obtained from the nonlinear buckling analysis. A shallow plane arch illustrates the structural design optimization methodology, and the results are compared with those in the literature. It is shown that a design based on the generalized eigenvalue problem (linear buckling) gives an optimum limit load less than the initial limit load, whereas the optimization using the nonlinear buckling analysis obtains a larger value for the optimum limit load compared to the initial limit load. It has also been demonstrated that the optimum results obtained using OC technique are in good agreement with those obtained through SQP technique. However, the computational time for the OC is significantly lower than that of SQP, which requires search techniques and sensitivity of the limit load for its successful completion and termination.

关键词： Structural Optimization Finite Element Analysis sequential quadratic programming Buckling Analysis Critical Loading Beam (Structures) Lagrange Multipliers Energy Density Young's Modulus Composite Structures

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Optimal Power Flow Solution for Bipolar DC Networks Using a Recursive quadratic Approximation

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ENERGIES 2023年第2期16卷 589页

作者： Montoya, Oscar Danilo Gil-Gonzalez, Walter Hernandez, Jesus C. Univ Distrital Francisco Jose de Caldas Fac Ingn Grp Compatibil & Interferencia Electromagnet GCEM Bogota 110231 Colombia Univ Tecnol Bolivar Fac Ingn Lab Inteligente Energia Cartagena 131001 Colombia Univ Tecnol Pereira Dept Elect Engn Pereira 660003 Colombia Univ Jaen Dept Elect Engn Campus Lagunillas S-NEdificio A3 Jaen 23071 Spain

The problem regarding of optimal power flow in bipolar DC networks is addressed in this paper from the recursive programming stand of view. A hyperbolic relationship between constant power terminals and voltage profiles is used to resolve the optimal power flow in bipolar DC networks. The proposed approximation is based on the Taylors' Taylor series expansion. In addition, nonlinear relationships between dispersed generators and voltage profiles are relaxed based on the small voltage voltage-magnitude variations in contrast with power output. The resulting optimization model transforms the exact nonlinear non-convex formulation into a quadratic convex approximation. The main advantage of the quadratic convex reformulation lies in finding the optimum global via recursive programming, which adjusts the point until the desired convergence is reached. Two test feeders composed of 21 and 33 buses are employed for all the numerical validations. The effectiveness of the proposed recursive convex model is verified through the implementation of different metaheuristic algorithms. All the simulations are carried out in the MATLAB programming environment using the convex disciplined tool known as CVX with the SEDUMI and SDPT3 solvers.

关键词： recursive optimal power flow solution sequential quadratic programming bipolar DC networks unbalanced loads power loss minimization

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Power iteration and inverse power iteration for eigenvalue complementarity problem

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NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 2019年第4期26卷 e2244-e2244页

作者： Abdi, Fatemeh Shakeri, Fatemeh Amirkabir Univ Technol Fac Math & Comp Sci Dept Appl Math Tehran 441315875 Iran Inst Res Fundamental Sci IPM Sch Math Tehran 193955746 Iran

In this paper, an inverse complementarity power iteration method (ICPIM) for solving eigenvalue complementarity problems (EiCPs) is proposed. Previously, the complementarity power iteration method (CPIM) for solving EiCPs was designed based on the projection onto the convex cone K. In the new algorithm, a strongly monotone linear complementarity problem over the convex cone K is needed to be solved at each iteration. It is shown that, for the symmetric EiCPs, the CPIM can be interpreted as the well-known conditional gradient method, which requires only linear optimization steps over a well-suited domain. Moreover, the ICPIM is closely related to the successive quadratic programming (SQP) via renormalization of iterates. The global convergence of these two algorithms is established by defining two nonnegative merit functions with zero global minimum on the solution set of the symmetric EiCP. Finally, some numerical simulations are included to evaluate the efficiency of the proposed algorithms.

关键词： conditional gradient method eigenvalue complementarity problem inverse power iteration method power iteration method sequential quadratic programming

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