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2DOF multi-objective optimal tuning of disturbance reject fractional order PIDA controllers according to improved consensus oriented random search method

2DOF multi-objective optimal tuning of disturbance reject fr...

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作者： Özbey, Necati Brno University of Technology

This study presents a Fractional Order Proportional Integral Derivative Acceleration (FOPIDA) controller design methodology to improve set point and disturbance reject control performance. The proposed controller tuning method performs a multi-objective optimal fine-tuning strategy that implements a Consensus Oriented random search (CORS) algorithm to evaluate transient simulation results of a set point filter type Two Degree of Freedom (2DOF) FOPIDA control system. Contributions of this study have three folds: Firstly, it addresses tuning problem of FOPIDA controllers for first order time delay systems. Secondly, the study aims fine-tuning of 2DOF FOPIDA control structure for improved set point and disturbance rejection control according to transient simulations of implementation models. This enhances practical performance of theoretical tuning method according to implementation requirements. Thirdly, the paper presents a hybrid controller tuning methodology that increases effectiveness of the CORS algorithm by using stabilizing controller coefficients as an initial configuration. Accordingly, the CORS algorithm performs the fine-tuning of 2DOF FOPIDA controllers to achieve an improved set point and disturbance rejection control performances. This fine-tuning is carried out by considering transient simulation results of 2DOF FOPIDA controller implementation model. Moreover, Reference to Disturbance Ratio (RDR) formulation of the FOPIDA controller is derived and used for measurement of disturbance rejection control performance. Illustrative design examples are presented to demonstrate effectiveness of the proposed method.

关键词： Fractional order control 2DOF controller design Disturbance rejection Reference to disturbance ratio random search algorithm

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Radioactive source search problem and optimisation model based on meta-heuristic algorithm

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APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2022年第1期7卷 927-956页

作者： Zhang, Min Lu, Xuewen Hoffman, Ettiene Kharabsheh, Radwan Xiao, Qianghua Univ South China Sch Math & Phys Hengyang Hunan Peoples R China Sch Math Phys & Energy Engn Hengyang Hunan Peoples R China Univ Calgary Dept Math & Stat Calgary AB T2N 1N4 Canada Canadian Univ Dubai Dubai U Arab Emirates Appl Sci Univ Bahrain Business Adm Econ & Adm Sci Al Hidd Bahrain

In the process of rational development and utilisation of nuclear energy, people often face nuclear accidents such as lost and stolen radioactive sources;so, the means of searching for these sources quickly in highly radioactive environments is an important security challenge. In the past, these jobs were limited to workers specialising in nuclear technology. They used gamma-ray detection equipment to search for radioactive sources, but the search efficiency was low. The main purpose of this article is to design a meta-heuristic algorithm based on imitating professional technicians to locate radioactive sources in a computer-aided manner. At the same time, due to the complexity that may characterise the actual search, the search strategy must be optimised. The article established an intelligent random search model with human thinking Finally, it was proved based on the mathematical theory that the complexity of the model search algorithm is linear, and the simulation experiment results show that the optimisation algorithm has good efficiency and fault tolerance.

关键词： nuclear radioactive source random search algorithm complexity

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Incorporating Filters in random search algorithms for the Hourly Operation of a Multireservoir System

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2018年第2期144卷 04017088-04017088页

作者： Chen, Duan Leon, Arturo S. Fuentes, Claudio Gibson, Nathan L. Qin, Hui Sci Res Inst Changjiang River Dept Project Planning 23 Huangpu Rd Wuhan 430010 Hubei Peoples R China Univ Houston Dept Civil & Environm Engn Houston TX 77204 USA Oregon State Univ Dept Stat Corvallis OR 97331 USA Oregon State Univ Dept Math Corvallis OR 97331 USA Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Hubei Peoples R China

Optimization of short-term reservoir operation normally involves ramping constraints of outflows and water elevations at short time steps (e.g.,hourly). random search algorithms, such as genetic algorithms, have been widely used in optimization of reservoir operation. When applying random search algorithms to hourly reservoir operation, two important issues arise. The first one is the frequent violation of ramping constraints on the hourly reservoir outflows because of the random nature of the optimization algorithm. In other words, the optimization struggles to meet the ramping constraints when finding feasible solutions. The second issue is the zigzag fluctuation of the hourly decision variables as a result of the random search, which is unrealistic to implement in practice. In this study, the Savitzky-Golay smoothing filter (also known as least-squares filter) is incorporated periodically within the routine of the Nondominated Sorting Genetic algorithm (NSGA-II). The goal of this study is to smooth out the decision variable functions without deteriorating the performance of the optimization algorithm. The performance of the proposed approach is quantified through three indexes using a multireservoir system with 3,360 decision variables as the test case. The results show that use of the Savitzky-Golay filter not only provides a solution to the two aforementioned issues, but also significantly improves the performance of the NSGA-II for hourly reservoir operation. The optimal decisions obtained using the proposed approach display similar hourly variability to decisions of actual reservoir operation. (c) 2017 American Society of Civil Engineers.

关键词： random search algorithm Zigzag operational scheme Reservoir operation Savitzky-Golay filter Smoothing

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Multi-join Query in Database Based on Genetic and Ant Colony algorithm Optimization 19

Multi-join Query in Database Based on Genetic and Ant Colony...

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4th International Conference on Big Data and Computing (ICBDC)

作者： Shi, Lingling He, Dongzhi Beijing Univ Technol Fac Informat Technol Beijing Peoples R China

ISBN: (纸本)9781450362788

Faced with massive data and the complexity of query requirements, how to improve the query speed of database has become a research hotspot. This paper analyses the artificial intelligence algorithms, genetic ant colony algorithm (GA-ACA), which is used for database query optimization. The GA-ACA is prone to decrease the diversity in multi-connection search of database, which results in inefficiency and local extremum. To solve this problem, our paper proposes an improvement algorithm on multi-connection query. Based on the premise of population diversity, the algorithm analyses the population entropy and variance. And it chooses the equal probability crossover or the unequal probability crossover according to the evolutionary state, which effectively avoids the phenomenon of local optimum due to the iteration of similar individuals. This paper improves the crossover operation and redefines the generation mode of new population. Experiments show that the improved algorithm avoids the local optimal solution to some extent, meanwhile shortens the searching time.

关键词： Genetic ant colony algorithm database query optimization random search algorithm crossover operation Population diversity

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Design optimization of offshore wind farms with multiple types of wind turbines

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APPLIED ENERGY 2017年 205卷 1283-1297页

作者： Feng, Ju Shen, Wen Zhong Tech Univ Denmark Dept Wind Energy DK-2800 Lyngby Denmark

Most studies on offshore wind farm design assume a uniform wind farm, which consists of an identical type of wind turbines. In order to further reduce the cost of energy, we investigate the design of non-uniform offshore wind farms, i.e., wind farms with multiple types of wind turbines and hub-heights. Given a set of different types of wind turbines with a different default hub height for each type, we can specify the design of a wind farm by the types of turbines, number of turbines for each type, and turbine locations. We consider the optimization of such design to minimize the levelized cost of energy, which is calculated using a capital cost model that covers the turbine cost and the balance of plant cost. An empirical wind turbine design cost and scaling model is utilized to model the cost of turbines with different sizes. Constraints on wind farm boundary, wind turbine proximity and total capacity are also included. We solve the problem with a newly developed extended random search algorithm and tested it in a realistic design optimization problem based on the Horns Rev 1 offshore wind farm in Denmark. The optimized non-uniform designs are compared with their uniform counterparts. We find that a non-uniform design can achieve a lower levelized cost of energy than its uniform counterparts, when the capital cost per MW is slightly lower for the smaller size turbine. Comparison with the mixed-discrete particle swarm optimization algorithm is also carried out for a non-uniform wind farm design problem with a fixed number of turbines, which shows the effectiveness and superiority of the proposed algorithm. Finally, the advantages and possible disadvantages of non-uniform design are also identified and discussed.

关键词： Offshore wind farm Non-uniform wind farm Layout optimization Design optimization random search algorithm Levelized cost of energy

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New method for indoor positioning by using wireless communication base stations

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ELECTRONICS LETTERS 2017年第20期53卷 1385-1386页

作者： Zheng, Xiaoyang Su, Hong Wei, Zhengyuan Hu, Shunren Chongqing Univ Technol Coll Sci Chongqing 400054 Peoples R China Chongqing Univ Technol Coll Elect Informat & Automat Chongqing 400054 Peoples R China

A novel approach for indoor localisation is presented and it is composed of two mathematical models. One is a stochastic differential equation proposed to modify time of arrival of a mobile terminal (MT) to a base station (BS). Another is a multivariate optimisation model implemented to estimate the location of the MT by a random search algorithm. Through simulations using only the time of arrivals and measured coordinates of the BSs, the performance of the proposed scheme is evaluated by the measured coordinates of the 25 MTs. Simulation results demonstrate that the mean localisation error is only 0.5138 m and this method is very effective and applicable.

关键词： indoor radio mobile radio evolutionary computation stochastic processes optimisation search problems time-of-arrival estimation indoor positioning wireless communication base stations indoor localisation mathematical models stochastic differential equation time-of-arrival modification mobile terminal multivariate optimisation model location estimation random search algorithm mean localisation error

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Multi-loop PI/PID controllers design for disturbance rejection based on non-parametric effective model and non-convex optimisation

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IET CONTROL THEORY AND APPLICATIONS 2014年第15期8卷 1499-1512页

作者： Jin, Qibing Liu, Qie Beijing Univ Chem Technol Coll Informat Sci & Technol Inst Automat Beijing 100029 Peoples R China

In this study, the authors address the design of the multi-loop controllers for multi-input and multi-output (MIMO) processes for disturbance rejection. Three types of disturbance rejection are analysed, and they demonstrate that those disturbance responses are directly related to the integral terms of the controllers. A concept of non-parametric effective model is introduced here to decompose a MIMO control system into several equivalent single-input and single-output control systems. Based on the effective model in each loop, a non-convex optimisation problem is established to obtain the optimal controller parameters with certain robustness indices. Considering the drawbacks of using random search algorithm, they develop a numerical algorithm to solve this non-convex optimisation problem. Simulation studies demonstrate that the proposed method improves the disturbance rejection compared with other decentralised controllers.

关键词： MIMO systems three-term control PI control control system synthesis concave programming optimal control search problems numerical analysis multiloop PI-PID controllers design disturbance rejection nonparametric effective model multi-input and multi-output processes disturbance responses MIMO control system nonconvex optimisation problem equivalent single-input and single-output control systems optimal controller parameters certain robustness indices random search algorithm numerical algorithm decentralised controllers

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Optimized Scheduling Strategies for Hybrid Density Functional Theory Electronic Structure Calculations 14

Optimized Scheduling Strategies for Hybrid Density Functiona...

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International Conference on High Performance Computing, Networking, Storage and Analysis

作者： Dawson, William Gygi, Francois Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

ISBN: (纸本)9781479955008

Hybrid Density Functional Theory (DFT) has recently gained popularity as an accurate model of electronic interactions in chemistry and materials science applications. The most computationally expensive part of hybrid DFT simulations is the calculation of exchange integrals between pairs of electrons. We present strategies to achieve improved load balancing and scalability for the parallel computation of these integrals. First, we develop a cost model for the calculation, and utilize random search algorithms to optimize the data distribution and calculation schedule. Second, we further improve performance using partial data-replication to increase data availability across cores. We demonstrate these improvements using an implementation in the Qbox Density Functional Theory code on the Mira BlueGene/Q computer at Argonne National Laboratory. We perform calculations in the range of 8k to 128k cores on two representative simulation samples from materials science and chemistry applications: liquid water and a metal-water interface.

关键词： chemistry computing density functional theory molecular electronic states parallel machines resource allocation scheduling search problems Argonne National Laboratory Mira Blue Gene/Q computer Qbox density functional theory code calculation schedule chemistry data availability data distribution electronic interaction exchange integral hybrid DFT simulation hybrid density functional theory electronic structure calculation liquid water load balancing load scalability materials science application metal-water interface optimized scheduling strategy parallel computation partial data-replication random search algorithm representative simulation Computational modeling Discrete Fourier transforms Load management Optimal scheduling Processor scheduling Schedules ARGONNE NATIONAL LABORATORY data distribution molecular electronic states discrete Fourier transform PARALLEL PROCESSING (COMPUTERS) data availability scheduling of multiprocessor Load balancing load management density functional theory tabu search Optimal scheduling parallel machines Chemistry Computational modeling

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Design of computer network topologies: A Vroom Inspired Psychoclonal algorithm

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APPLIED MATHEMATICAL MODELLING 2013年第3期37卷 888-902页

作者： Shukla, Nagesh Dashora, Yogesh Tiwari, M. K. Shankar, Ravi Univ Warwick WMG Digital Lab Coventry CV4 7AL W Midlands England SMART Infrastruct Facil Wollongong NSW 2522 Australia Sabre Travel Technol Private Ltd Bangalore 560066 Karnataka India Indian Inst Technol Dept Ind Engn & Management Kharagpur 721302 W Bengal India Indian Inst Technol Dept Management Studies New Delhi India

In the prevailing era of network and communication technology, the problem pertaining to the determination of the most economic way to interconnect nodes while satisfying some reliability and quality of service constraints has been agnized as one of the most intricate and challenging problem for the modern day researchers and practitioners belonging to Communication and Networking community. Motivated by the improved performance of the concepts like proliferation, affinity maturation, receptor editing, etc., over the more prevalent generalized crossover and mutation;and by the application and effectiveness of Maslow's need hierarchy in combinatorial optimization as well the more logical motivational concepts provided by Vroom's valence expectancy theory, authors have proposed and investigated their applications to the topological design of distributed packet switched networks. The extensive computations over the problems of varying complexities and dimensions prove the superiority of the proposed methodology. It has been observed that the proposed Vroom Inspired Psychoclonal algorithm (VIPA) outperforms the traditional well established random search algorithms (i.e. Genetic algorithm, Simulated Annealing and Artificial Immune Systems) in the context of underlying problem;the performance being significantly improved as the problem complexity increases. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Communication and Networking random search algorithm Combinatorial optimization

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Antenna Optimization in Long-Term Evolution Networks

Antenna Optimization in Long-Term Evolution Networks

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作者： Deng, Qichen KTH Royal Institute of Technology

学位级别：master

The aim of this master thesis is to study algorithms for automatically tuning antenna parameters to improve the performance of the radio access part of a telecommunication network and user experience. There are four dierent optimization algorithms, Stepwise Minimization algorithm, random search algorithm, Modied Steepest Descent algorithm and Multi-Objective Genetic algorithm to be applied to a model of a radio access network. The performances of all algorithms will be evaluated in this thesis. Moreover, a graphical user interface which is developed to facilitate the antenna tuning simulations will also be presented in the appendix of the report

关键词： Multi-Objective Optimization Non Dominated (Pareto Optimal) Solutions Pareto Front Cost Function Stepwise Minimization algorithm random search algorithm Modied Steepest Descent algorithm Multi-Objective Genetic algorithm Graphical User Interface (GUI). Natural Sciences Mathematics Naturvetenskap Matematik Physics Chemistry Mathematics fysik/kemi/matematik Master of Science - Mathematics Teknologie masterexamen - Matematik Mathematics Matematik

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