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21st International-Federation-of-Automatic-Control (IFAC) Symposium on Automatic Control in Aerospace (ACA)

作者： Mukundan, Vijith Maity, Arnab Kumar, Shashi Ranjan Rajeev, U. P. Indian Space Res Org Vikram Sarabhai Space Ct Trivandrum 695022 Kerala India Indian Inst Technol Dept Aerosp Engn Mumbai 400076 Maharashtra India

This paper aims to investigate optimization of a highly constrained three-dimensional trajectory of a launch vehicle stage powered by air-breathing engine, with oblate gravitational field. The trajectories of such vehicles are difficult to optimize, owing to strong nonlinear coupling between the thrust, aerodynamics and the vehicle's states, and stringent constraints on structural load and aerodynamic heating. The objective of trajectory optimization is to impart maximum velocity at a desired altitude and direction, with minimum fuel consumption, using angle of attack and engine throttle as control inputs. Path constraints on dynamic pressure, bending moment, and heat flux as well as control constraints need to be satisfied. Trajectory is optimized using the approach of discretization of control variables, which converts this optimal control problem to a nonlinear programming (NLP) problem. This NLP problem is solved using a metaheuristic method (harmony search optimization), and the sensitivity of the solution with respect to discretization is also analyzed. The versatility of trajectory planning method is demonstrated by solving the problem with different initial conditions, objectives and constraints. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： Trajectory launch vehicle optimization constraints harmony search nonlinear programming problem

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Optimal Allocation of Testing Resource for Modular Software based on Testing-Effort Dependent Software Reliability Growth

Optimal Allocation of Testing Resource for Modular Software ...

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3rd International Conference on Computing Communication and Networking Technologies (ICCCNT)

作者： Ahmad, N. Khan, M. G. M. Islam, Syed Faizul TM Bhagalpur Univ Univ Dept Stat & Comp Appl Bhagalpur 812007 India Univ South Pacif Sch Comp Informat & Math Sci Suva Fiji

Software reliability is a key factor in software development process. Testing phase of software begins with module testing whereby, modules are tested independently to remove substantial amount of faults within a specified testing resource. Therefore, the available resource must be allocated among the modules in such a way that number of faults is removed as much as possible from each of the module to achieve higher software reliability. In this paper two optimization problem are discussed for optimal allocation of testing resources for the modular software system. These optimization problems are formulated as nonlinear programming problems (NLPP), which are modeled by a software reliability growth model based on a non-homogeneous Poisson process which incorporated Log-logistic testing-effort function. LINGO program is used to solve the optimization problems. Finally, numerical examples are given to illustrate the procedure developed in this paper. It is shown that the optimal allocation of testing-resources among software modules can improve software reliability.

关键词： Software reliability growth model resource allocation problem nonlinear programming problem inflection S-shaped models

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Robust control design method for uncertain system using a set of measurements

Robust control design method for uncertain system using a se...

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American Control Conference (ACC)

作者： Khadraoui, S. Nounou, H. Nounou, M. Datta, A. Bhattacharyya, S. P. Texas A&M Univ Qatar Dept Elect & Comp Engn Doha Qatar

ISBN: (纸本)9781479901784

This work deals with the design of robust fixed-structure controllers for uncertain systems based on a finite set of measured data. This set of measurements is given in the frequency domain. In the current control design approaches, controllers are usually designed based on plant models obtained on the basis of measured data. However, due to various forms of uncertainties such as: plant parameter variations, external disturbances, measurement noise, etc, such models are unable to perfectly describe the behavior of the physical system. Hence, degradation in the controller performance is expected due to such uncertainties and errors associated with the identification process. For that, we propose a new control technique that uses the uncertain measurements to directly design robust controllers, for a class of uncertainties, without going through the use of identification process. In such a proposed design method, interval techniques are introduced to bound plant uncertainties. Its main principle is to find the set of admissible values of the controller parameters so that the family of all possible frequency responses of the closed-loop system lies between an upper and lower bounds of a desired frequency response. This problem is formulated as a nonlinear programming problem which can easily be solved to characterize the solution set of the controller parameters. The main feature of our proposed approach is that it enables to design robust fixed-structure controllers by taking into account the plant uncertainties. Moreover, since no mathematical model is needed in the controller synthesis, the design process does not depend on the increasing order and complexity of the system. A simulation example is presented to illustrate and validate the efficacy of the proposed method.

关键词： Data-based control Robust controller Plant uncertainty Interval analysis Frequency response template nonlinear programming problem

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Calibration Estimator of Population Mean in Stratified Random Sampling

Calibration Estimator of Population Mean in Stratified Rando...

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Asia Pacific World Congress Computer Science Engineering

作者： Singh, G. K. Rao, D. K. Khan, M. G. M. Univ South Pacific Sch Comp Informat & Math Sci Suva Fiji

ISBN: (纸本)9781479919550

Stratified Sampling is one of the most widely used sampling techniques as it increases the precision of the estimate of the survey variable. On the other hand, calibration estimation is a method of adjusting the original design weights to improve survey estimates by using auxiliary information such as the known population total ( or mean) of the auxiliary variables. A calibration estimator uses calibrated weights that are determined to minimize a given distance measure to the original design weights while satisfying a set of constraints related to the auxiliary information. In this paper, a new calibration estimator of population mean in stratified sampling design is proposed, which incorporates not only the population mean but also the variance stratified mean available for the auxiliary variable. The problem of determining the optimum calibrated weights is formulated as a nonlinear programming problem (NLPP) that is solved using Lagrange multiplier technique. The computational details of the procedure are illustrated in the presence of one auxiliary variable. A numerical example is presented and a simulation study is carried out to illustrate the computational details and the performance of the proposed calibration estimator. The results reveal that the proposed calibration estimator is more efficient than the other calibration estimators of the population mean.

关键词： Calibration estimation stratified sampling auxiliary information nonlinear programming problem Lagrange multiplier technique

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Optimal Performance of Modular and Synchronized Mechatronic Systems 19

Optimal Performance of Modular and Synchronized Mechatronic ...

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19th IEEE International Conference on Emerging Technology and Factory Automation (ETFA)

作者： Kanthabhabhajeya, Sathyamyla Lennartson, Bengt Chalmers SE-41296 Gothenburg Sweden

ISBN: (纸本)9781479948451

Optimizing the configuration and overall performance of synchronized modular systems is considered in this paper. The synchronized modules can be considered as a hybrid system, including continuous-time dynamics of local moving devices, combined with high-level discrete event sequences. The continuous-time trajectories are approximated by the Gauss pseudospectral method, resulting in a nonlinear programming (NLP) problem. The optimal configuration generates the maximal production rate subject to dynamic constraints. A complete design procedure is presented and applied to a case study of a packaging machine, where an alternative optimal configuration is achieved compared to current industrial practices.

关键词： Gaussian processes continuous time systems discrete event systems mechatronics nonlinear programming Gauss pseudospectral method NLP problem continuous-time dynamics continuous-time trajectories high-level discrete event sequences hybrid system industrial practices local moving devices modular mechatronic systems nonlinear programming problem optimal performance packaging machine synchronized mechatronic systems synchronized modular systems synchronized modules Acceleration Approximation methods Indexes Optimal control Optimization Pumps Synchronization

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A Time-optimal Trajectory Generation Algorithm for Quadrotors with Various States Constraints 3

A Time-optimal Trajectory Generation Algorithm for Quadrotor...

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3rd IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： He, Zhen Fang, Yongchun Liang, Xiao Lin, He Xiao, Yuting Zhang, Xuebo Nankai Univ Tianjin Key Lab Intelligent Robot Inst Robot & Automat Informat Syst Tianjin 300350 Peoples R China

ISBN: (纸本)9781538670668

Time optimal trajectory generation, where a quadrotor is brought from an initial state to a terminal one in minimal time while satisfying various dynamic and kinematic constraints, is enjoying more and more popularity. In this paper, we propose a time optimal trajectory generation algorithm by exploiting the differential flatness properly of the quadrotor dynamics to formulate the optimal control problem, which is further transformed into a nonlinear programming problem. Then we find coefficients that satisfy preset constraints to obtain dynamically feasible and smooth trajectories represented via time parameterized polynomials. Simulation and experimental results show the effectiveness of the proposed algorithm.

关键词： Trajectory generation differential flatness time optimal nonlinear programming problem

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Exploration of near rectilinear halo orbits and their transfer trajectories in the Jupiter-Europa system 74

Exploration of near rectilinear halo orbits and their transf...

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74th International Astronautical Congress, IAC 2023

作者： Lu, Pengfei Wang, Yue Cui, Shuhao School of Astronautics Beihang University No.9 South Third Street Shahe Higher Education Park Changping District Beijing102206 China

The icy moons of Jupiter have garnered widespread attention due to their potential to be habitats for extraterrestrial life and hence attracted substantial research interest. Previous studies have proven that the traditional perturbed two-body, low-altitude, and high-inclination orbits around the Jovian icy moons are usually unstable and ΔV cost-intensive for capture. Near rectilinear halo orbits (NRHOs) in the circular restricted three-body problem (CRTBP) possess several advantageous properties, such as favorable stability, small closest distances to the secondary, high inclinations, and higher energy compared to the perturbed two-body orbits, therefore they have enormous potential to be further utilized in the icy moons' exploration. This paper investigates the NRHOs in the Jupiter-Europa system. The L1 and L2 NRHO families are determined and their properties, including the stability, geometry, as well as orbital resonance, are thoroughly examined and discussed. Furthermore, transfers between the symmetric southern and northern NRHOs are designed through a systematic methodology, which includes an initial search process and the establishment and solution of a nonlinear programming (NLP) problem. Numerical results indicate that the solutions can be categorized as the interior and exterior types, and the lowest ΔV required for the transfer between the typical resonant NRHOs is approximately several tens of m/s. The works could provide a foundation for the further exploitation of the NRHOs in the Jovian icy moons' explorations. Copyright © 2023 by Prof. Yue Wang. Published by the IAF, with permission and released to the IAF to publish in all forms.

关键词： Icy moons Jupiter-Europa system Near rectilinear halo orbits nonlinear programming problem Transfer design

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An Enumeration-Based Deterministic Algorithm for Solving optimization problem 6

An Enumeration-Based Deterministic Algorithm for Solving opt...

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6th IEEE International Conference on Automation, Electronics and Electrical Engineering, AUTEEE 2023

作者： Yang, Changlin Aeronautics Computing Technology Research Institute Process Management Office Xi'an China

ISBN: (纸本)9798350305623

An enumeration-based deterministic algorithm is proposed for solving optimization problem. Discretization of the feasible region for each decision variable is applied to establish search tree so that all the solutions could be enumerated. A new search region is established from the optimization of previous literation. Meanwhile, adjustment of search step with exponential decay function is conducive to reducing the search scope until the convergence of result is realized. The proposed algorithm is applied for three kinds of typical optimization problem, including Non-linear Programing problem, Job-Shop Scheduling problem and Traveling Salesman problem. The results obtained by the new algorithm are compared with results of swarm intelligent optimization algorithm. Results indicate that for the combinational optimization, high convergence rate could be realized by adjusting the feasible region for each decision variable. For non-linear programming problem, the accuracy of results obtained from deterministic algorithm is better than that from self-organizing migrating algorithm, which infers that enumeration-based deterministic algorithm could be used to solve NP hard problem. © 2023 IEEE.

关键词： deterministic algorithm enumeration job-shop scheduling problem nonlinear programming problem optimization traveling salesman problem

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Optimal control problems involving constrained, switched, and delay systems

Optimal control problems involving constrained, switched, an...

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作者： Loxton, Ryan Christopher Curtin University of Technology

学位级别：master

In this thesis, we develop numerical methods for solving five nonstandard optimal control problems. The main idea of each method is to reformulate the optimal control problem as, or approximate it by, a nonlinear programming problem. The decision variables in this nonlinear programming problem influence its cost function (and constraints, if it has any) implicitly through the dynamic system. Hence, deriving the gradient of the cost and the constraint functions is a difficult task. A major focus of this thesis is on developing methods for computing these gradients. These methods can then be used in conjunction with a gradient-based optimization technique to solve the optimal control problem efficiently.%%%%The first optimal control problem that we consider has nonlinear inequality constraints that depend on the state at two or more discrete time points. These time points are decision variables that, together with a control function, should be chosen in an optimal manner. To tackle this problem, we first approximate the control by a piecewise constant function whose values and switching times (the times at which it changes value) are decision variables. We then apply a novel time-scaling transformation that maps the switching times to fixed points in a new time horizon. This yields an approximate dynamic optimization problem with a finite number of decision variables. We develop a new algorithm, which involves integrating an auxiliary dynamic system forward in time, for computing the gradient of the cost and constraints in this approximate problem.%%%%The second optimal control problem that we consider has nonlinear continuous inequality constraints. These constraints restrict both the state and the control at every point in the time horizon. As with the first problem, we approximate the control by a piecewise constant function and then transform the time variable. This yields an approximate semi-infinite programming problem, which can be solved using a penalty functi

关键词： optimal control problems numerical methods nonlinear programming problem decision variables cost functions dynamic system constraint functions gradient-based optimization technique

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A Shape Optimisation with the Isogeometric Boundary Element Method and Adjoint Variable Method for the Three-Dimensional Helmholtz Equation

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COMPUTER-AIDED DESIGN 2022年 142卷 103126-103126页

作者： Takahashi, Toru Sato, Daisuke Isakari, Hiroshi Matsumoto, Toshiro Nagoya Univ Grad Sch Engn Dept Mech Syst Engn Furo Cho Nagoya Aichi 4648603 Japan

This paper presents a shape optimisation system to design the shape of an acoustically-hard object in the three-dimensional open space. The boundary element method (BEM) is suitable to analyse such an exterior field. However, the conventional BEM, which is based on piecewise polynomial shape and approximate (interpolation) functions, can require many design variables because they are usually chosen as a part of the nodes of the underlying boundary element mesh. In addition, it is not easy for the conventional method to compute the gradient of the sound pressure on the surface, which is necessary to compute the shape derivative of our interest, of a given object. To overcome these issues, we employ the isogeometric boundary element method (IGBEM), which was developed in our previous work. With using the IGBEM, we can design the shape of surfaces through control points of the NURBS surfaces of the target object. We integrate the IGBEM with the nonlinear programming software through the adjoint variable method (AVM), where the resulting adjoint boundary value problem can be also solved by the IGBEM with a slight modification. The numerical verification and demonstration validate our shape optimisation framework. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Boundary element method Isogeometric analysis Shape optimisation Adjoint variable method nonlinear programming problem

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