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Control of the Static Voltage Stability Margin Using Optimal Power Flow

IFAC Proceedings Volumes 1995年第26期28卷 329-334页

作者： P. Mangang S.S. Ahmed A. Petroianu Dept. of Electr. Engineering University of Karlsruhe Germany Rust Kennedy & Donkin Power Godalming Surrey GU7 2AZ England Dept. of Electr. Engineering University of Cape Town South Africa

This paper presents an optimal strategy for the control of the static voltage stability margin (SVSM) in stressed power systems. The optimal control strategy is determined by an Optimal Power Flow (OPF) using existing reactive power control devices. The objective of the OPF is the maximisation of a static voltage stability index (MVSI). A conceptual real-time implementation of the proposed optimal control strategy is outlined and the optimal control strategy is applied to a 16-bus network. It is demonstrated that the SVSM can be significantly enhanced by using a static voltage stability index instead of the reactive power losses as objective function of the OPF.

关键词： Static voltage stability static voltage stability margin Optimal Power Flow singular value decomposition sequential quadratic programming

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On Gradient Computation in Single-shooting Nonlinear Model Predictive Control

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IFAC Proceedings Volumes 2010年第5期43卷 613-618页

作者： Ruben Ringset Lars Imsland Bjarne Foss Cybernetica AS Leirfossveien 27 N-7038 Trondheim Norway Department of Engineering Cybernetics NTNU N-7038 Trondheim Norway

This paper gives an overview of methods for computing derivative information in dynamic optimization with path constraints. Efficiency of forward and adjoint techniques are discussed in a discrete-time setting and some algorithms are derived. Next, the discussion is extended to also include continuous-discrete systems. Dimensions in the model, signal parameterization, horizon length and sampling interval affect each of the methods differently. The key contributions of this paper is to give an overview of these methods, how they can be combined, and how different parameters affect efficiency.

关键词： dynamic optimization nonlinear model predictive control adjoint method sensitivity analysis sequential quadratic programming

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A novel design of Gaussian WaveNets for rotational hybrid nanofluidic flow over a stretching sheet involving thermal radiation

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2021年 123卷 105196-105196页

作者： Ilyas, Hira Ahmad, Iftikhar Raja, Muhammad Asif Zahoor Shoaib, Muhammad Univ Gujrat Dept Math Gujrat 50700 Pakistan Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan COMSATS Univ Islamabad Dept Math Attock Campus Attock 43600 Pakistan

The aim of this study is to analysis the mass and heat transfer in radiative three dimensional flow of hybrid nanofluid over the stretchable sheet by exploiting the strength of integrated computational intelligent algorithm by utilization of Gaussian wavelet neural networks (GWNNs) trained with the genetic algorithms (GAs) based global search supported with sequential quadratic programming (SQP) based local refinements i.e., GWNN-GA-SQP. The mean squared error based cost function is developed for the fluidic problem by applying Gaussian WaveNet GWNNs optimize with GAs and SQP. The numerical outcomes of the fluidic model are obtained by the proposed GWNN-GA-SQP solver to examine the thermal and velocities profile effect for three physical quantities based on magnetic parameter, nanomaterial concentration and transformated angular velocity. Moreover, a exhaustive analysis of the numerical solutions of GWNN-GA-SQP solver with reference Adams method endorse the stability, accuracy and consistency on multiple autonomous runs through different statistical performance operators and complexity analysis.

关键词： Stochastic numerical computing Neural networks Gaussian wavelets Genetic algorithms sequential quadratic programming Hybrid nanofluid Stretching sheet

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Comparison of Surrogate Models in a Multidisciplinary Optimization Framework for Wing Design

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AIAA JOURNAL 2010年第5期48卷 995-1006页

作者： Paiva, Ricardo M. Carvalho, Andre R. D. Crawford, Curran Suleman, Afzal Univ Victoria Dept Mech Engn Victoria BC V8W 2Y2 Canada

The replacement of the analysis portion of an optimization problem by its equivalent metamodel usually results in a lower computational cost. In this paper, a conventional nonapproximative approach is compared against three different metamodels: quadratic-interpolation-based response surfaces, Kriging, and artificial neural networks. The results obtained from the solution of four different case studies based on aircraft design problems reinforces the idea that quadratic interpolation is only well-suited to very simple problems. At higher dimensionality, the usage of the more complex Kriging and artificial neural networks models may result in considerable performance benefits.

关键词： Surrogate Model Multilayer Perceptron Aircraft Design Aerodynamic Shape Optimization Cumulative Distribution Function MDO Lift to Drag Ratio sequential quadratic programming Reynolds Averaged Navier Stokes Thickness Ratio

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Parametric Control Allocation for Vessels Equipped with Two Non-Fully Rotable Thrusters

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IFAC Proceedings Volumes 2012年第27期45卷 368-373页

作者： Vincenzo Calabrò Andrea Caiti ISME - Inter-University Centre on Integrated Systems for Marine Environment - Centro E. Piaggio University of Pisa Via Diotisalvi 2 56126 Pisa Italy

The paper presents two parametric control allocation systems for vessels equipped with two independent non-fully orientable thrusters. The proposed control-allocation methods are presented under the form of parametric sequential quadratic programming, in case of presence of unbounded references or in a direct parametric mapping, in case of norm-∞ bounded references (i.e. through human interface devices). Simulation results and comparison with previously presented algorithm prove the effectiveness of the proposed methods.

关键词： Parametric Control Allocation sequential quadratic programming Robust Control Allocation

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Contingency-constrained optimisation method for operating urban power grids with flexible switching stations

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JOURNAL OF ENGINEERING-JOE 2019年第16期2019卷 1619-1624页

作者： Liu, Jia Cheng, Haozhong Xu, Qian Lan, Zhou Zeng, Pingliang Yao, Liangzhong Shanghai Jiao Tong Univ Key Lab Control Power Transmiss & Convers Minist Educ Shanghai Peoples R China State Grid Zhejiang Elect Power Corp Econ Res Ins Hangzhou Zhejiang Peoples R China China Elect Power Res Inst Beijing Peoples R China

This study presents a multi-objective operation optimisation model for urban power grids with flexible switching (FS) stations to comprehensively improve system security and reliability. In the proposed model, uncertainties associated with load variation and component failures are considered. Moreover, constraints after a feeder or transformer N-1 contingency are preliminarily formulated. The operation problem optimises the apparent power of feeder section loading. The combination of normal boundary intersection and sequential quadratic programming is employed to solve the non-linear optimisation model. A case study carried out on a test 75-feeder distribution grid with FS stations demonstrates the effectiveness of the proposed model and solving method. Compared with conventional distribution loadability, the optimal load distribution solution obtained in this study provides a trade-off between system security and reliability. The coordinated operation optimisation method is suitable for urban smart distribution grids featured by distribution automation and large-scale interconnections.

关键词： optimal load distribution solution operation problem FS stations coordinated operation optimisation method flexible switching stations apparent power urban power grids nonlinear optimisation model feeder section loading component failures system security test 75-feeder distribution grid urban smart distribution grids optimisation sequential quadratic programming load distribution load variation normal boundary intersection smart power grids contingency-constrained optimisation method power system security nonlinear programming power grids multiobjective operation optimisation model quadratic programming power distribution reliability

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Efficient Implementation and Sampling Period Analysis of MPC for Water Distribution Networks*

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IFAC-PapersOnLine 2022年第33期55卷 42-47页

作者： P.C.N. Verheijen M. Lazar D. Goswami Dep. of Electrical Engineering Eindhoven University of Technology The Netherlands

In this paper we consider the design and implementation of Model Predictive Control (MPC) for water distribution networks (WDNs). First, we define the nonlinear differential algebraic equations that model a WDN, using both classical methods and simplified pump implementations. Then the cost function used in the MPC algorithm is formulated, where extra steps are taken to build a quadratic and convex cost function. The entire control problem is solved using a tailored sequential quadratic programming (SQP) method. The resulting control algorithm for WDNs is tested on a small distribution network to both illustrate the effectiveness and to perform additional tests on the effects of reducing the sampling period. The simulation results of this experiment indicate that the presented SQP–MPC can be implemented at faster rates than 1 hour and that this results in improved economic benefits.

关键词： Model Predictive Control Water Distribution Networks Non–Linear Control sequential quadratic programming

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Two-dimensional Trajectory Optimization of a Soft Lunar Landing from a Parking Orbit Considering a Landing Site

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IFAC Proceedings Volumes 2010年第15期43卷 178-183页

作者： Jong-Sun Ahn Bong-Gyun Park Min-Jea Tahk Space Exploration Engineering Department Korea Advanced Institute of Science and Technology Daejeon Korea Aerospace Engineering Department Korea Advanced Institute of Science and Technology Daejeon Korea (Tel:82-42-350-5758) Aerospace Engineering Department Korea Advanced Institute of Science and Technology Daejeon Korea

Abstract In this paper, minimum-fuel, two-dimensional trajectory optimization from a parking orbit to the desired landing site is presented. The landing site is usually not considered when performing the trajectory optimization. However, to design the precise trajectories to land at the desired site, the landing site has to be considered as the terminal constraint. To convert the trajectory optimization problem into a parameter optimization problem, a pseudospcetral (PS) method is used, and CFSQP is used as a numerical solver. To check that the results obtained are good solutions, the feasibility check is performed.

关键词： Soft landing trajectory optimization legendre pseudospectral method pseudospectral knotting method sequential quadratic programming

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A Comparative Study of Improved Dynamics of Single Link Flexible Revolute-Jointed Robotic Manipulator

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Procedia Engineering 2016年 144卷 425-434页

作者： S. Mahto A.K. Gogoi U.S. Dixit Research Scholar ME Deptt. IIT Guwahati 781039 India Professor EEE Deptt. IIT Guwahati 781039 India Professor Mech. Deptt. IIT Guwahati 781039 India

In this work, shape optimization is carried out of a single link flexible revolute flexible manipulator to extremize two objective functions (static tip deflection and fundamental frequency) using sequential quadratic programming (SQP) method. Robotic link is considered as an Euler-Bernoulli beam and finite element formulation is done. Newmark's scheme is used for its dynamic analysis. A comparative study of vibration suppression is carried out of uniform and shape optimized revolute robotic link under the excitation of sinusoidal/controlled torque.

关键词： Euler-Bernoulli beam shape optimization finite element method sequential quadratic programming energy-based robust control

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A design of predictive computational network for transmission model of Lassa fever in Nigeria

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RESULTS IN PHYSICS 2022年第0期39卷

作者： Shoaib, Muhammad Tabassum, Rafia Raja, Muhammad Asif Zahoor Nisar, Kottakkaran Sooppy Alqahtani, Mohammed S. Abbas, Mohamed COMSATS Univ Islamabad Dept Math Attock Campus Islamabad Pakistan Natl Yunlin Univ Sci & Technol 123 Univ Rd Yunlin 64002 Taiwan Prince Sattam bin Abdulaziz Univ Coll Arts & Sci Dept Math Wadi Aldawaser 11991 Saudi Arabia King Khalid Univ Coll Appl Med Sci Radiol Sci Dept Abha 61421 Saudi Arabia Univ Leicester Space Res Ctr BioImaging Unit Michael Atiyah Bldg Leicester LE1 7RH England King Khalid Univ Coll Engn Elect Engn Dept Abha 61421 Saudi Arabia Delta Univ Sci & Technol Coll Engn Comp & Commun Dept Gamasa 35712 Egypt

This paper presents an innovative artificial neural networks (ANNs) based hybrid algorithm of genetics optimization and sequential quadratic programming (AGOSQP) to construct the mathematical model for the dynamics of Lassa fever (DLF) in Nigeria. The model designated by the transmission of disease between two populations: human population i.e. susceptible (Sh), exposed (Eh), infectious (Ih) and recovered (Rh) humans and rodent population i.e. susceptible (Sr) and infectious (Ir) rodents. The log sigmoid function as an objective function based on mean squared error is constructed to optimize AGOSQP where genetic algorithm work as global searching optimization and SQP serve as the local searching optimization. To assess the correctness, robustness and convergence stability, the comparison between state of art Adam method and proposed AGOSQP is established. The Theil's inequality coefficient (TIC), root mean square error (RMSE) and mean absolute deviation (MAD) are also computed to authenticate the efficiency of proposed AGOSQP to solve the model for the dynamics of Lassa fever.

关键词： Lassa fever Genetic algorithm Adam method Neural Networks sequential quadratic programming

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