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Real-time P-H curve CNC interpolators for high speed cornering

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2008年第3-4期39卷 302-316页

作者： Jahanpour, Javad Imani, Behnam Moetakef Ferdowsi Univ Mashad Dept Mech Engn Fac Engn Mashhad Iran

In this paper, real-time Pythagorean hodograph (P-H) curve CNC interpolators are used for high speed corner machining. There are large contouring errors around sharp corners when low-bandwidth servo controllers (such as P-PI control) are used. In order to decrease the amount of the cornering errors, an improved interpolation method is proposed. The first deceleration phase of motion and the over-corner P-H curve constructed for regions with sharp corners are devised by quadratic and constant velocity interpolation algorithms, respectively. The geometric parameters of the over-corner P-H curve and the feed rate along the modified tool path are computed by pattern search algorithm in order to reduce the maximum cornering error. The proposed interpolation algorithm is implemented for symmetrical and unsymmetrical corners. The results of simulation, such as the cornering error and the total cornering time, are compared with previously published methods. It has been observed that the developed over-corner P-H approach can substantially reduce the amount of cornering error.

关键词： numerical control P-H curves real-time CNC interpolators physical constraints cornering error pattern search algorithm

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A supply chain disruption risk mitigation model to manage COVID-19 pandemic risk

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ENVIRONMENTAL SCIENCE AND POLLUTION REsearch 2021年 1-16页

作者： Shahed, Kazi Safowan Azeem, Abdullahil Ali, Syed Mithun Moktadir, Md Abdul Bangladesh Univ Engn & Technol Dept Ind & Prod Engn Dhaka 1000 Bangladesh Univ Dhaka Inst Leather Engn & Technol Dhaka 1209 Bangladesh

This study develops a mathematical model to mitigate disruptions in a three-stage (i.e., supplier, manufacturer, retailer) supply chain network subject to a natural disaster like COVID-19 pandemic. This optimization model aims to manage supply chain disruptions for a pandemic situation where disruptions can occur to both the supplier and the retailer. This study proposes an inventory policy using the renewal reward theory for maximizing profit for the manufacturer under study. Tested using two heuristics algorithms, namely the genetic algorithm (GA) and pattern search (PS), the proposed inventory-based disruption risk mitigation model provides the manufacturer with an optimum decision to maximize profits in a production cycle. A sensitivity analysis was offered to ensure the applicability of the model in practical settings. Results reveal that the PS algorithm performed better for such model than a heuristic method like GA. The ordering quantity and reordering point were also lower in PS than GA. Overall, it was evident that PS is more suited for this problem. Supply chain managers need to employ appropriate inventory policies to deal with several uncertain conditions, for example, uncertainties arising due to the COVID-19 pandemic. This model can help managers establish and redesign an inventory policy to maximize the profit by considering probable disruptions in the supply chain network.

关键词： Supply chain disruption Supply chain resiliency COVID-19 Genetic algorithm pattern search algorithm Inventory policy Supply chain mitigation

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Novel load frequency control scheme for hybrid power systems employing interline power flow controller and redox flow battery

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2021年第1期47卷 11787-11805页

作者： Mishra, Sonalika Prusty, Umesh Chandra Prusty, Ramesh Chandra Panda, Sidhartha VSSUT Dept Elect Engn Burla 768018 India

This article proposes a novel load frequency control (LFC) scheme for hybrid power systems (HPS) in the presence of Interline Power Flow Controller (IPFC) and redox flow battery (RFB). Due to the vagueness nature of solar energy and wind energy sources present in the HPS, the LFC problem is a critical task in HPS. For this study, a fuzzy proportional integral derivative (FPID) controller with hybrid salp swarm algorithm and pattern search algorithm (hSSA-PS) is used to optimize the controller parameter of the HPS system under random and stochastic environments. The usefulness of the proposed hSSA-PS algorithm is established over salp swarm algorithm (SSA), genetic algorithm (GA) and Particle swarm optimization (PSO) algorithms. The performance of the system under study is evaluated with/without the presence of IPFC and RFB. It is observed that system performance is improved with the presence of an IPFC controller and RFB. The robustness of the proposed controller is justified by conducting sensitivity analysis. It is noticed that in presence of the proposed FPID controller the reduction in ITAE/IAE/ISE values is 92.18%, 90.84 and 98.52% as compared to PID controller and 31.42%, 86.90% and 90% as compared to PID controller in the occurrence of IPFC and RFB under stochastic environment. The robustness of the proposed controller is justified by conducting a sensitivity analysis. Also, the outperformance of the suggested controller is contrasted with some advanced controllers reported in some recent papers.

关键词： Frequency regulation Fuzzy logic controller Hybrid power system Interline power flow controller pattern search algorithm Redox flow battery Salp swarm algorithm

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Optimal setting of directional over-current relays in distribution networks considering transient stability

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2016年第1期26卷 122-133页

作者： Mosavi, S. Mohammad Ali Kejani, Tohid Akbari Javadi, Hamid Shahid Beheshti Univ AC Fac Elect Engn Tehran Iran PSEEZ Asaluyeh Iran Islamic Azad Univ Islamshahr Branch Dept Elect Engn Islamshahr Iran Shahid Beheshti Univ AC Islamshahr Branch Fac Elect Engn Tehran Iran

Because of the nonlinear characteristic of directional over-current relays (DOCR), optimal setting and coordination of DOCRs are a complicated task in an interconnected distributed network. These relays are usually coordinated without considering constraints of power system transient stability. In this paper, we present a novel methodology for relay coordination considering transient stability as a constraint in optimization problem of over-current relays setting. The relays are set and coordinated based on the obtained results. For this purpose, an appropriate objective function is proposed, and then a two-phase procedure is used in order to consider relays constraints. pattern search (PS) algorithm is employed to solve the problem under MATLAB software. Results of the proposed approach on a typical distributed network are shown and discussed. These results signify the effectiveness of the presented method. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： directional over-current relay optimal relay setting pattern search algorithm relay coordination transient stability

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Developing a flow control strategy to reduce nutrient load in a reclaimed multi-reservoir system using a 2D hydrodynamic and water quality model

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SCIENCE OF THE TOTAL ENVIRONMENT 2014年 466卷 871-880页

作者： Park, Yongeun Cho, Kyung Hwa Kang, Joo-Hyon Lee, Seung Won Kim, Joon Ha Gwangu Inst Sci & Technol Sch Environm Sci & Engn Gwangu 500712 South Korea Ulsan Natl Inst Sci & Technol Sch Urban & Environm Engn Ulsan 698805 South Korea Dongguk Univ Seoul Dept Civil & Environm Engn Seoul 100715 South Korea

Blocking the natural bi-directional flow in an estuarine system using an artificial dyke has commonly caused serious water quality problems. In the southwestern part of South Korea, a parallel triple-reservoir system was constructed by blocking the mouth of three different rivers (Yeongsan, Okcheon, and Kumja), which were then interconnected using two open channels. This system has experienced a deterioration in water quality due to pollutants accumulated from the upper watershed, and has continually discharged pollutant loads to the outer ocean. Therefore, the objective of this study is to establish an effective dam operation plan for reducing nutrient loads released from the integrated reservoir. In this study, the CE-QUAL-W2 model, which is a 2-dimentional hydrodynamic and water quality model, was applied to predict the pollutant load released from each reservoir in response to different flow scenarios for the interconnecting channel. The model was calibrated using two novel methods: a sensitivity analysis to determine meaningful model parameters, and a pattern search to optimize the parameters. From the scenario analysis using flow control, it was determined that the total nitrogen (TN) and total phosphorus (TP) loadings could be reduced by 27.2% and 6.6%, respectively, under the optimal channel flow scenario by regulating the chlorophyll-a concentration in the reservoir. The results confirm that effective dam operation could contribute to a decrease in pollutant loads in the receiving seawater body. As such, this study suggests operational strategies for a multi-reservoir system that can be used to reduce the nutrient load being discharged from reservoirs. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Integrated reservoirs Water quality modeling (CE-QUAL-W2) pattern search algorithm Sensitivity analysis Flow control

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Novel computing paradigms for parameter estimation in power signal models

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NEURAL COMPUTING & APPLICATIONS 2020年第10期32卷 6253-6282页

作者： Mehmood, Ammara Chaudhary, Naveed Ishtiaq Zameer, Aneela Raja, Muhammad Asif Zahoor Pakistan Inst Engn & Appl Sci Dept Elect Engn Islamabad Pakistan Int Islamic Univ Dept Elect Engn Islamabad Pakistan Pakistan Inst Engn & Appl Sci Dept Comp & Informat Sci Islamabad Pakistan COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan

The strength of evolutionary computational heuristic paradigms is exploited for parameter estimation of power signal modeling problems by incorporating differential evolution (DE), genetic algorithms (GAs) and pattern search (PS) methodologies. The objective function of power signal harmonics is constructed by utilizing the power of approximation theory in mean squared error sense. The stiff optimization task of signal harmonics is performed with heuristic solvers DE, GAs and PS that provide efficacy, fast convergence rate and avoid getting trapped in local minima. Statistics reveal that DE outperforms its counterparts in terms of accuracy, robustness and complexity measures.

关键词： Power signals Parameter estimation Differential evolution Genetic algorithm pattern search algorithm Evolutionary computing

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Dynamic pressure based mid-course guidance scheme for hypersonic boost-glide vehicle

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2019年第9期233卷 3211-3222页

作者： Kumar, G. Naresh Sarkar, A. K. Talole, S. E. Def Res & Dev Lab Hyderabad India Def Inst Adv Technol Dept Aerosp Engn Pune 411025 Maharashtra India

In this study, a guidance scheme for an aerodynamically controlled hypersonic boost-glide class of flight vehicle is proposed. In this work, optimum glide dynamic pressure corresponding to maximum L/D throughout the flight is calculated and a mid-course guidance law formulation to track the dynamic pressure while suppressing phugoid oscillations is proposed for real-time flight trajectory shaping. Efficacy of the proposed guidance scheme has been demonstrated through simulation studies. Robustness analysis on the proposed guidance algorithm is carried out using Monte Carlo technique. Lastly, a pattern search algorithm-based offline generated maximum L/D optimal trajectory existing in literature, which meets minimum dynamic pressure, maximum airframe skin temperature, as well as other in-flight and terminal constraints is used as reference trajectory to evaluate the performance of the proposed guidance scheme.

关键词： Dynamic pressure hypersonic boost-glide vehicle mid-course guidance Monte Carlo pattern search algorithm skin temperature stability

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Controller design via nonsmooth multidirectional search

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 2006年第6期44卷 1923-1949页

作者： Apkarian, P Noll, D CERT ONERA Control Syst Dept F-31055 Toulouse France Univ Toulouse 3 CNRS UMR 5640 Toulouse France

We propose an algorithm which combines multidirectional search (MDS) with nonsmooth optimization techniques to solve difficult problems in automatic control. Applications include static and fixed-order output feedback controller design, simultaneous stabilization, H-2/H-infinity-synthesis, and much else. We show how to combine direct search techniques with nonsmooth descent steps in order to obtain convergence certificates in the presence of nonsmoothness. Our technique is efficient when small and medium size controllers for plants with large state dimension are sought. Our numerical testing includes several benchmark examples. For instance, our algorithm needs 0.41 s to compute a static output feedback stabilizing controller for the Boeing 767. utter benchmark problem [ E. E. J. Davison, IFAC Technical Committee Reports, Pergamon Press, Oxford, 1990], a system with 55 states. The first static controller without performance specifications for this system was obtained in [ J. Burke, A. Lewis, and M. Overton, SIAM J. Optim., 15 ( 2003), pp. 751 - 779].

关键词： NP-hard design problems static output feedback fixed-order synthesis simultaneous stabilization mixed H2/ H-infinity-synthesis pattern search algorithm moving polytope nonsmooth analysis spectral bundle method epsilon-subgradients bilinear matrix inequality (BMI)

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Dynamic Sensor Scheduling for Data Size Reduction in a Sensor Cloud System Based on Minimum Reconstruction Error

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WIRELESS PERSONAL COMMUNICATIONS 2024年第3期135卷 1423-1447页

作者： Shylashree, N. Kumar, Sachin VTU RV Coll Engn Dept Elect & Commun Bengaluru 560059 India South Ural State Univ Big Data & Machine Learning Lab Chelyabinsk Russia

Sensing and subsequent analysis of the environmental data of a given geographical area is an essential requisite for the planned development of that region. Nowadays, IoT Sensor-Cloud ecosystem has been adopted to collect data from IoT sensors and transmit it to the chosen Cloud Server for further processing and dissemination. In a large Wireless Sensor Network formed by the IoT sensors, there will be a significant amount of redundancy in the dataset when the nodes are placed closely, and the sensed data varies slowly and gradually with regard to time and space. Then, avoiding redundant data transmission can lead to lower energy consumption and communication overhead. Adaptive subset selection of sensor nodes for data size reduction in a Wireless Sensor Network is an approach to efficiently managing the amount of data transmitted within the network. Then, in the current time schedule, it is possible to optimally select a subset of the sensor nodes for data collection without very much affecting the overall data fidelity. An optimal sensor node subset selection scheme that reduces the communication load with minimum information loss is proposed to achieve this task. The unselected nodes are put in sleep mode, which consequently results in lower sensor energy expenditure. The subset selection algorithm is implemented based on the derivative-free pattern search optimizer that minimizes the reconstruction error during the associated extrapolation. This approach differs entirely from the Compressive Data Gathering approach. The simulation results reveal that the performance of the proposed scheme is superior to other similar competitive methods in terms of the mean square error, which is found to be 1.95, with the percentage participation nodes equal to 50% and when the sensor data is uniformly distributed over 20 and 30 units.

关键词： pattern search algorithm Grid data extrapolation Minimum reconstruction error Keyframes Intermediate frames Wakeup duty cycle

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Control of Supply Risk Based on Ranking Foreign Suppliers Using pattern search Weighted Fuzzy Comprehensive Evaluation

Control of Supply Risk Based on Ranking Foreign Suppliers Us...

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The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

作者： Lei Yang Cheng Liu Zhiyong Zhang Yongqiang Shi Department of Logistics Engineering and Management School of Economics and Commerce South China University of Technology Guangzhou 510006 P.R.China

Essential characteristics of foreign suppliers are identified that should be considered in the supplier selection process to control supply chain disruption risk in the manufacturer's assembly operation. Since that the tangible and intangible characteristics are integrated in the supplier-ranking procedure and the multi-criteria evaluation system is introduced while the weight of each criteria may not be known in advance, in this paper, the fuzzy comprehensive evaluation(FCE) is employed to settle the prompt break skip illogicality of the membership degree of supplier' performance to a reliability level, and the pattern search algorithm (PSA) is imposed to figure out the significant weights to make full use of existing well-known benchmark supplier selected by consultants and manufacturer's executives in group-decision rather than completely subjective preferring determination by persons.A case study is presented in which a manufacturer ranks its current foreign supplier against two other potentials based on criterions of supply reliability. The outcome illustrates the practicality of the pattern search weighted FCE method's application in the selection strategy of foreign business partners.

关键词： supplier selection supply chain risk control pattern search algorithm group decision-making fuzzy comprehensive evaluation

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