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Nonlinear System Identification Tools Applied to the Modelling of Submarine Dynamics

IFAC Proceedings Volumes 2003年第4期36卷 49-54页

作者： M.E. Furlong G.E. Hearn S.M. Veres E. Rogers School of Engineering Sciences University of Southampton UK Ocean Engineering Division Southampton Oceanography Centre UK Department of Electronics and Computer Science University of Southampton UK

This paper presents initial results on the use of nonlinear systems identification algorithms to estimate the hydrodynamic coefficients in fully coupled, nonlinear submarine motion equations. Parameter identification algorithms rely on the sequential quadratic programming technique. The paper briefly describes the form of the non-linear equations used in the submarine simulation, describes the system identification algorithms developed and then illustrates their application to three test cases of interest. These are based on horizontal motion only and aim to identify the model coefficients in the cases when these are completely unknown, partially known, and partially known but with an error on the known values respectively.

关键词： system identification sequential quadratic programming submarine/AUV hydrodynamic coefficients motion simulation

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Ariane V Ascent Trajectory Optimization with a First-Stage Splash-Down Constraint

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IFAC Proceedings Volumes 1989年第2期22卷 27-32页

作者： K.H. Well DLR German Aerospace Research Establishment Institute for Flight Systems Dynamics Oberpfaffenhofen FRG

The paper describes a numerical approach for determining the optimal ascent trajectory into a geostationary transfer orbit of an ARIANE V type vehicle subject to a first stage splash-down constraint. The control function is angle of attack and for simplicity a planar ascent is considered. By parameterizing the control function and by introducing suitable time transformations the multi-stage system is formulated as a single stage system and solved numerically using sequential quadratic programming. It is concluded that this approach is efficient in terms of computer time and insensitive with respect to modelling weaknesses such as linear interpolation of aero- and thrust data.

关键词： Optimal control parameter optimization sequential quadratic programming aerospace trajectories rocket ascent

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Optimization of Stiffness Characteristics for the Design of Bistable Composite Laminates

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AIAA JOURNAL 2012年第10期50卷 2211-2218页

作者： Betts, David N. Kim, H. Alicia Bowen, Christopher R. Univ Bath Dept Mech Engn Bath BA2 7AY Avon England

Asymmetric composite laminates can have a bistable response to mechanical loading. The large deflections that can be achieved by snap-through from one stable state to another, along with a need for small and removable energy input, make them of interest for a wide range of engineering applications. After 30 years of research efforts the shapes and response to applied strains of laminates of general layup have been well characterized. More recently, with the development of smart actuators, the design and application of bistable laminates has been considered. This paper presents an optimization technique for the design of bistable laminates enabled by an analytical solution for an asymmetric laminate design. The optimization formulation maximizes the bending stiffness in the direction of known loading condition while the bending stiffness in the direction of snap-through is minimized. A minimum deflection requirement is applied as a constraint. The design problem has multiple local optima, with the global optimum not intuitively obvious from the problem definition, differing from the typical high-deflection cross-ply solution.

关键词： Bending Stiffness Composite Laminates Finite Element Modeling Thermal Expansion Material Properties Poisson's Ratio Energy Density sequential quadratic programming Rayleigh Ritz Approach Smart Actuator

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Dynamic production optimization for offshore Electric Submersible Pump oilfields based on oil-water two phase virtual flow metering

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PETROLEUM SCIENCE AND TECHNOLOGY 2024年

作者： Bai, Zonghan Kang, Qi Wu, Haihao Gong, Jing China Univ Petr Beijing Peoples R China Tsinghua Univ Tsinghua Univ Shenzhen Dept Automat Res Inst Shenzhen Peoples R China

Enhancing offshore oilfield production is critical, but optimizing production equipment parameters presents significant challenges due to the difficulty in obtaining accurate fluid properties and the necessity for precise equipment models. Multiphase flow calculations depend on preset fluid parameters, which are particularly challenging to determine in offshore environments. This paper proposes a virtual measurement method tailored for reservoir, well, and pipeline network models in offshore oilfields. The approach involves calibrating the Electric Submersible Pump (ESP) model and calculating the viscosity of oil-water emulsions to assess phase separation and fluid water content within the well. By utilizing revised data and production efficiency indicators, the optimal ESP operating frequency is determined to enhance offshore oilfield production. Adjusting the operating parameters based on these calculations enables continuous production optimization until the discrepancy between real-time data and computed results falls within the acceptable accuracy range. This method conserves substantial capital investment, enhances operational efficiency, and significantly boosts enterprise profitability.

关键词： Dynamic production optimization ESP performance analysis offshore oilfield production oil-water phases sequential quadratic programming virtual flow measurement

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Solution of Economic Dispatch Problem Using Hybrid Multi-Verse Optimizer

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ELECTRIC POWER SYSTEMS RESEARCH 2022年第0期208卷 1页

作者： Iqbal, M. Naveed Bhatti, Abdul Rauf Butt, Arslan Dawood Sheikh, Yawar Ali Paracha, Kashif Nisar Ashique, Ratil H. Univ Faisalabad Dept Elect Engn & Technol Govt Coll Faisalabad 38000 Pakistan Green Univ Bangladesh Dept EEE Kanchon Bangladesh

Economic Dispatch (ED) is one of the important problems among numerous vital operational problems of power economics. ED is a non-convex, non-drivable, and non-linear optimization issue along with diverse constraints. In this research work, a neoteric natural influential optimization tool Multi-verse Optimizer (MVO) hybridized with sequential quadratic programming (SQP) termed as Hybrid MVO (MVO-SQP) is proposed for the solution of multi-constrained ED problem. This contemporary effort contemplates on ED problem in the milieu of convergence features, numerical proficiency, and *** non-convex ED problem is encrypted at Hybrid Multi-verse Optimizer (HMVO) framework and employed in MATLAB for 30 trials, 300 iterations, and 30 exploration universes. The presented mechanism is verified on typical standard test systems comprising of 6, 13, 15, and 40 unit test systems, and experimental outcomes are juxtaposed with the reported approaches in the literature. The statistical analysis shows that the proposed approach saves 2.927 $/h for 6 units test system, 9.0618 $/h for 13 units test system, 1.831 $/h for 15 units test system, and 113.515 $/hr for 40 units test system with losses. It is envisioned that this work will equip the researchers with an improved tool to solve ED problem.

关键词： Economic Dispatch Multi-Verse Optimizer sequential quadratic programming Differential Evolution Valve Point Loading Effect Transmission Line Loss Prohibited Operated Zones

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An Optimistic Solver for the Mathematical Model of the Flow of Johnson Segalman Fluid on the Surface of an Infinitely Long Vertical Cylinder

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MATERIALS 2021年第24期14卷 7798-7798页

作者： Khan, Naveed Ahmad Alshammari, Fahad Sameer Romero, Carlos Andres Tavera Sulaiman, Muhammad Mirjalili, Seyedali Abdul Wali Khan Univ Dept Math Mardan 23200 Pakistan Prince Sattam bin Abdulaziz Univ Dept Math Coll Sci & Humanities Al Kharj Al Kharj 11942 Saudi Arabia Univ Santiago Cali Fac Engn COMBA R&D Lab Cali 76001 Colombia Torrens Univ Australia Ctr Artificial Intelligence Res & Optimisat Brisbane Qld 4006 Australia Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea

In this paper, a novel soft computing technique is designed to analyze the mathematical model of the steady thin film flow of Johnson-Segalman fluid on the surface of an infinitely long vertical cylinder used in the drainage system by using artificial neural networks (ANNs). The approximate series solutions are constructed by Legendre polynomials and a Legendre polynomial-based artificial neural networks architecture (LNN) to approximate solutions for drainage problems. The training of designed neurons in an LNN structure is carried out by a hybridizing generalized normal distribution optimization (GNDO) algorithm and sequential quadratic programming (SQP). To investigate the capabilities of the proposed LNN-GNDO-SQP algorithm, the effect of variations in various non-Newtonian parameters like Stokes number (S-t), Weissenberg number (W-e), slip parameters (a), and the ratio of viscosities ( f ) on velocity profiles of the of steady thin film flow of non-Newtonian Johnson-Segalman fluid are investigated. The results establish that the velocity profile is directly affected by increasing Stokes and Weissenberg numbers while the ratio of viscosities and slip parameter inversely affects the fluid's velocity profile. To validate the proposed technique's efficiency, solutions and absolute errors are compared with reference solutions calculated by RK-4 (ode45) and the Genetic algorithm-Active set algorithm (GA-ASA). To study the stability, efficiency and accuracy of the LNN-GNDO-SQP algorithm, extensive graphical and statistical analyses are conducted based on absolute errors, mean, median, standard deviation, mean absolute deviation, Theil's inequality coefficient (TIC), and error in Nash Sutcliffe efficiency (ENSE). Statistics of the performance indicators are approaching zero, which dictates the proposed algorithm's worth and reliability.

关键词： drainage problems Johnson Segalman model computational fluid dynamics weighted legendre neural networks hybrid soft computing generalized normal distribution optimization sequential quadratic programming

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Rapid Generation of Accurate Entry Landing Footprints

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2010年第3期33卷 756-767页

作者： Lu, Ping Xue, Songbai Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

Rapid and reliable generation of the landing footprint of an entry vehicle is the key capability required for onboard determination of landing options. Under the conventional formulation of the maximum-crossrange problem at specified downranges, the footprint problem is difficult to numerically solve. When inequality trajectory constraints are imposed, accurate determination of footprints becomes even more challenging. Using the quasi-equilibrium glide condition in entry flight, a near-optimal closed-form bank angle control law is first developed for the class of problems, including the maximum-crossrange problem. Then, it is shown that the footprint problem is equivalent to seeking the solutions of a series of much simpler problems of the closest approach to a moving virtual target. The closest-approach problem is a univariate root-finding problem using the near-optimal control law. Common inequality entry trajectory constraints are enforced, without any additional difficulty, with appropriate velocity-dependent bounds of the bank angle by using the quasi-equilibrium glide condition. As a result, an accurate and fully constrained landing footprint from any feasible initial condition can be obtained rapidly and very reliably. The validity of the method is verified with independent trajectory optimization software. Footprints for an entry vehicle in several different mission scenarios and constraint settings are generated to demonstrate the method.

关键词： Aerodynamic Coefficients Transversality Condition Earth Flight Path Angle Angle of Attack Flight Control System Newton Raphson Method Dynamic Pressure sequential quadratic programming International Space Station

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Nontangent, developed contour bulkheads for a single-stage launch vehicle

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JOURNAL OF SPACECRAFT AND ROCKETS 2000年第1期37卷 114-121页

作者： Wu, KC Lepsch, RA NASA Langley Res Ctr Met & Thermal Struct Branch Hampton VA 23681 USA NASA Langley Res Ctr Vehicle Anal Branch Hampton VA 23681 USA

Dry weights for single-stage launch vehicles that incorporate nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1,414 aspect ratio ellipsoidal bulkheads. Weights, volumes, and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weights of vehicles that Incorporate the optimized bulkheads are predicted using a vehicle weights and sizing Code. Two optimization approaches are employed. A structural-level method, where the vehicle's three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of 4365 lb (2.2%) from the 200,679-lb baseline vehicle dry weight, in the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. For the vehicle-level analysis, modified bulkhead designs are analyzed and incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle-level analysis predicts a dry weight reduction of 5129 lb, a 2.6% reduction from the baseline weight. Based on these results, nontangent, developed contour bulkheads may provide substantial weight savings for single stage vehicles.

关键词： Expendable Launch Vehicle Aspect Ratio Structural Analysis Propellant Circumferential Stress sequential quadratic programming International Space Station Lockheed Martin Corporation Material Properties Internal Pressure

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Uncertainty-Based Structural Optimization Using Universal Grey Number Theory

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AIAA JOURNAL 2019年第11期57卷 5002-5013页

作者： Rao, S. S. Wang, Shuo Univ Miami Dept Mech & Aerosp Engn Coral Gables FL 33146 USA Univ Miami Coral Gables FL 33146 USA Harbin Engn Univ Coll Automat Harbin 150001 Heilongjiang Peoples R China

Several types of uncertainties are encountered in the design of machines and structures. The geometric parameters or dimensions are specified in terms of nominal values and tolerances, the experimentally determined material properties exhibit scatter over a range, and many types of loads are inherently variable (loads due to wind, floods, and earthquakes). It is difficult to develop probability distributions to all such uncertain parameters. Even if probability distributions are developed, their confidence levels need to be established using a t- or chi-squared distribution. However, it is easier and more accurate to model the uncertain quantities/parameters as intervals. Thus, for example, in the interval parameter-based optimization, only the known or expected ranges of the design parameters are used with no need to establish the confidence levels of their intervals. This work presents an interval parameter-based optimum design of structural components. Although the field of interval analysis deals with computation of interval numbers, it suffers from the so-called dependency problem, whereby the computations get more and more inaccurate, resulting in wider intervals of the computed response quantities as compared to the true intervals if multiple arithmetic operations are performed using the same interval number or if complicated expressions are evaluated using interval numbers. Hence, a more accurate method, known as the universal grey number theory, is used in this work for the analysis and computations involved in the optimization procedure. Two numerical optimization problems, which are the design of a stepped bar subjected to an axial load and the design of a welded beam subjected to a transverse load, are presented to illustrate the procedure.

关键词： Structural Optimization Probability Distribution Material Properties Numerical Optimization MATLAB Young's Modulus sequential quadratic programming Genetic Algorithm Compressive Stress Structural System

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A Filter-Based Sample Average SQP for Optimization Problems With Highly Nonlinear Probabilistic Constraints

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JOURNAL OF MECHANICAL DESIGN 2010年第11期132卷 111002-111002页

作者： Hsu, Kai-Shian Chan, Kuei-Yuan Natl Cheng Kung Univ Tainan 70101 Taiwan

In this work, we develop a filter-based sequential quadratic programming (SQP) algorithm for solving reliability-based design optimization (RBDO) problems with highly nonlinear constraints. The proposed filter-based SQP uses the approach of average importance sampling (AAIS) in calculating the values and gradients of probabilistic constraints. AAIS allocates samples at the limit state boundaries such that relatively few samples are required in calculating constraint probability values to achieve high accuracy and low variance. The accuracy of probabilistic constraint gradients using AAIS is improved by a sample filter that eliminates sample outliers that have low probability of occurrence and high gradient values. To ensure convergence, the algorithm uses an iteration filter in place of the penalty function to avoid the ill-conditioning problems of the penalty parameters in the acceptance of a design update. A sample reuse mechanism that improves the efficiency of the algorithm by avoiding redundant samples is introduced. The "unsampled" region, the region not covered by previous samples, is identified using iteration step lengths, the trust region, and constraint reliability levels. As a result, the filter-based sampling SQP efficiently handles highly nonlinear probabilistic constraints with multiple most probable points or functions without analytical forms. Several examples are demonstrated, and the results are compared with those from first order reliability method/second order reliability method and Monte Carlo simulations. Results show that by integrating the modified AAIS with the filter-based SQP, the overall computation cost of solving RBDO problems can be significantly reduced. [DOI: 10.1115/1.4002560]

关键词： sequential quadratic programming approach of average importance sampling reliability-based design optimization gradient of probability function

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