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Statistical analysis of control parameters in evolutionary map L-systems-based topology optimization

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2018年第3期58卷 997-1013页

作者： Ikonen, Teemu J. Sobester, Andras Univ Southampton Computat Engn & Design Southampton SO16 7QF Hants England

Map L-systems-based parametrization, also referred to as the cellular division method, is a generative encoding, suitable for topology optimization. The parametrization is compact due to its ability to reuse its elements, and therefore capable of covering a large design space with relatively few design variables. Map L-systems are often evolved using genetic algorithms (GAs). A key implementation detail of such procedures, as with most GA-based geometry searches, is the choice of parameters controlling the operation of the evolutionary process. The optimal choice of these in conventional optimization formulations is highly problem-specific-far less so, however, when the GA evolves an L-systems encoding and does not act directly on the geometry. This is because the L-system encoding is, itself, independent of the geometry. We study the effects of different control parameters by conducting a statistical test of over 400 parameter combinations on five test cases, for which the global optima are known. The best-performing parameter combinations are reported as a Pareto front of the average number of objective function evaluations and ranking based on the average of optimized fitnesses. Finally, three Pareto-optimal parameter combinations are selected and applied to an optimization problem of maximizing the fundamental natural frequency of an integrally stiffened aluminum panel. The best of the resulting designs has a higher fundamental natural frequency than the baseline design by a margin of 11.2%.

关键词： Topology optimization Generative encoding L-systems Genetic algorithm control parameters

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Optimal tuning of the control parameters of an inverter-based microgrid using the methodology of design of experiments

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IET POWER ELECTRONICS 2020年第16期13卷 3651-3660页

作者： Miret, Jaume Balestrassi, Pedro Paulo Camacho, Antonio Guzman, Ramon Castilla, Miguel Tech Univ Catalonia Dept Elect Engn Vilanova I La Geltru Spain Univ Fed Itajuba Inst Ind Engn Itajuba Brazil Tech Univ Catalonia Dept Automat Control Vilanova I La Geltru Spain

The design of the control system in an inverter-based microgrid (mu Gs) is a challenging problem due to the large number of parameters involved. Different optimisation methods based on obtaining an approximated mathematical model of the mu G can be found in the literature. In these approaches, the non-linearities and uncertainties of the real system are typically not considered, which may result in a non-optimal tuning of the control parameters. In addition, in most applications, the problem has been simplified, assuming that all controllers have the same value for their control parameters. However, in this case, the behaviour of the system is sub-optimal since the particularities of each node of the mu G are not taken into account. In this study, an experimental approach for tuning the control parameters of an inverter-based mu G is introduced. The approach is based on the methodology of design of experiments and it considers different values for the control parameters of all controllers. In this study, this methodology is applied to the design of a droop-free control scheme;however, it can be easily extended to other control schemes. The validity of the proposal is verified through selected experimental results.

关键词： optimisation distributed power generation power distribution control invertors design of experiments optimal tuning control parameters inverter-based microgrid control system nonoptimal tuning inverter-based mu G droop-free control scheme control schemes design of experiments

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Cooperative effects of control parameters on the dynamic responses of vehicle powertrain during start-up process

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2022年第13期236卷 2932-2948页

作者： Wang, Dongyang Hu, Minghui Qin, Datong Chongqing Univ Sch Automot Engn Chongqing Peoples R China State Key Lab Mech Transmiss Chongqing Peoples R China

The degradation of the frictional characteristics of a wet clutch, with repeated engagements throughout its full life, alters the dynamic responses of the powertrain, which weakens the effect of the control system with a fixed control law. To solve this problem, cooperative effects of control parameters on the dynamic responses of the vehicle start-up process throughout the full life cycle of the wet clutch were studied. First, the degradation law of the wet clutch frictional characteristics was obtained with a test rig, and the life cycle of wet clutch was divided into three stages, based on statistical data from the automobile factory. Then, the powertrain model of start-up process was developed and verified with a test. Finally, the cooperative effects of the hydraulic-pressure rising rate and the initial relative speed on the dynamic responses of the vehicle powertrain at the three stages of the clutch life were studied. The results revealed that the control parameters have different influences on the dynamic responses of the vehicle start-up at the different stages of wet clutch service life. To obtain good start-up performance, different optimal combinations of controllable parameters should be adopted at different stages of the wet-clutch service life.

关键词： Friction characteristics powertrain dynamic responses control parameters cooperative effect

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Insights into the effects of control parameters and mutation strategy on self-adaptive ensemble-based differential evolution

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INFORMATION SCIENCES 2020年 514卷 203-233页

作者： Wang, Shir Li Morsidi, Farid Ng, Theam Foo Budiman, Haldi Neoh, Siew Chin Univ Pendidikan Sultan Idris Fac Art Comp & Creat Ind Tanjong Malim 35900 Perak Malaysia Univ Sains Malaysia Ctr Global Sustainabil Studies George Town 11800 Malaysia Univ Notthingham Malaysia Fac Sci Sch Comp Sci Jln Broga Semenyih 43500 Selangor Malaysia Univ Islam Kalimantan Fak Teknol Informasi Jl Adhiyaksa 2 Kalimantan Selatan 70123 Indonesia

This work explores the challenges in identifying appropriate and significant parameter configurations in differential evolution (DE) under the influence of population diversity and dimension size. For most DE algorithms, the configuration of control parameters is a vital prerequisite for balancing exploration and exploitation within the confinement of a search space. This study investigates the implementation of various adaptive parameter setting configurations on benchmark functions via the proposal of an algorithmic scheme called self-adaptive ensemble-based DE (SAEDE). This algorithm uses self-adaptive and ensemble mechanisms to set the relevant parameters for each generation. SAEDE is compared with two other ensemble-based DEs, and their performance is evaluated using 34 benchmark functions consisting of 20 low dimensions and 14 high dimensions. Furthermore, the convergence of these DEs is tested by using Q-measure. Experimental results indicate that SAEDE achieves the highest frequency of maximum success rate in 28 out of the 34 benchmark functions. SAEDE also achieves the lowest Q-measure of 4237318. These findings show the competitiveness and efficiency of SAEDE in locating optimal solutions while avoiding exhaustive searches of suitable parameters by users in terms of achieving optimization while minimizing the dependency on user setting. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Differential evolution Self-adaptive Evolutionary algorithm Ensemble control parameters Mutation strategies

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A study of the Classical Differential Evolution control parameters

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SWARM AND EVOLUTIONARY COMPUTATION 2016年 26卷 86-96页

作者： Penunuri, F. Cab, C. Carvente, O. Zambrano-Arjona, M. A. Tapia, J. A. Univ Autonoma Yucatan Fac Ingn AP 150 Merida Yucatan Mexico

An extensive numerical study has been conducted to shed some light on the selection of parameters for the Classical Differential Evolution (DE/rand/1/bin) optimization method with the dither variant It is well known that the crossover probability (C-r) has an active role in the convergence of the method. Our experiments show that even when the number of generations needed to achieve convergence as a function of the C-r parameter is of a stochastic nature, in some regions a reasonably well defined dependence of this number as a function of C-r can be observed. Motivated by this result, a self-adaptive DE methodology has been proposed. This new methodology applies the DE/rand/1/bin strategy itself to find a good value for the C-r parameter. Regarding the population size parameter, a phenomenological study involving the search space, the tolerance error, and the complexity of the function has been made. The proposed methodology has been applied to 10 of the most common test functions, giving the best success rate (100% in all the studied examples) and in general a faster convergence than the classical DE/rand/1/bin strategy. (C) 2015 Published by Elsevier B.V.

关键词： Differential evolution control parameters Self-adaptive Strategy Complexity

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Fitting the control parameters of a genetic algorithm:: An application to technical trading systems design

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第3期179卷 847-868页

作者： Nunez-Letamendia, Laura Inst Empresa Dept Finance Madrid 28006 Spain

This paper studies the problem of how changes in the design of the genetic algorithm (GA) have an effect on the results obtained in real-life applications. In this study, focused on the application of a GA to the tuning of technical trading rules in the context of financial markets, our tentative thesis is that the GA is robust with respect to design changes. The optimization of technical trading systems is a suitable area for the application of the GA metaheuristic, as the complexity of the problem grows exponentially as new technical rules are added to the system and as the answer time is crucial when applying the system to real-time data. Up to now, most of GAs applications to this subject obviated the question of possible "design dependence" in their results. The data we report, based on our experiments, do not allow us to refute the hypothesis of robustness of the GA to design implementation, when applying to technical trading systems tuning. (c) 2005 Elsevier B.V. All rights reserved.

关键词： genetic algorithm control parameters financial markets trading system technical rule

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Estimation of optimum genetic control parameters for job shop scheduling

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2002年第3期19卷 224-234页

作者： Ponnambalam, SG Jawahar, N Kumar, BS Reg Engn Coll Dept Prod Engn Tiruchirappalli 620015 India Thiagarajar Coll Engn Dept Mech Engn Madurai Tamil Nadu India Bluemt Ceram Ltd Coimbatore Tamil Nadu India

Genetic algorithms (GA) have demonstrated considerable success in providing good solutions to many non-polynomial hard optimisation problems. GAs are applied for identifying efficient solutions for a set of numerical optimisation problems. Job shop scheduling (JSS) has earned a reputation for being difficult to solve. Many workers have used various values of genetic parameters. This paper attempts to tune the control parameters for efficiency, that are used to accelerate the genetic algorithm (applied to JSS) to converge on an optimal solution. The genetic parameters, namely, number of generations, probability of crossover, probability of mutation, are optimised relating to the size of problems. The results are validated in job shop scheduling problems. The results indicate that by using an appropriate range of parameters, the genetic algorithm is able to find an optimal solution faster.

关键词： control parameters genetic algorithm job shop scheduling

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An AI system for the decision to control parameters of TP film printing

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EXPERT SYSTEMS WITH APPLICATIONS 2009年第5期36卷 9580-9583页

作者： Huang, Chih-Chien Huang, Huang-Chu Chen, Yu-Ju Hwang, Rey-Chue I Shou Univ Dept Elect Engn Kaohsiung Taiwan Kaohsiung Marine Univ Dept Elect Commun Kaohsiung Taiwan Cheng Shiu Univ Informat Management Dept Kaohsiung Taiwan

In this paper, an artificial intelligent mechanism for the decision of control parameters of touch panel film printing was developed. This mechanism is capable of providing the accurate information for the control parameters of the film printing, so that the technician Could make a good setting work for the real-line manufacturing operation of touch panel film. Thus, this system not only can help the technician to improve the efficiency on the work of film printing, but also can reduce the cost caused by the defective products for the company. In our study, this intelligent system was constructed by using quantum neural network. It can automatically display the proper value of each control parameter needed for the film printing when the thickness of film is determined. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Artificial intelligent control parameters Touch panel Film printing

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Influence of Active Power Output and control parameters of Full-Converter Wind Farms on Sub-Synchronous Oscillation Characteristics in Weak Grids

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ENERGIES 2020年第19期13卷 5225页

作者： Hao, Yafeng Liang, Jun Wang, Kewen Wu, Guanglu Joseph, Tibin Sun, Ruijuan Zhengzhou Univ Sch Elect Engn Zhengzhou 450001 Peoples R China Cardiff Univ Sch Engn Cardiff CF24 3AA S Glam Wales China Elect Power Res Inst State Key Lab Power Grid Safety & Energy Conserva Beijing 100192 Peoples R China

Active power outputs of a wind farm connected to a weak power grid greatly affect the stability of grid-connected voltage source converter (VSC) systems. This paper studies the impact of active power outputs and control parameters on the subsynchronous oscillation characteristics of full-converter wind farms connected weak power grids. Eigenvalue and participation factor analysis was performed to identify the dominant oscillation modes of the system under consideration. The impact of active power output and control parameters on the damping characteristics of subsynchronous oscillation is analysed with the eigenvalue method. The analysis shows that when the phase-locked loop (PLL) proportional gain is high, the subsynchronous oscillation damping characteristics are worsened as the active power output increases. On the contrary, when the PLL proportional gain is small, the subsynchronous oscillation damping characteristics are improved as the active power output increases. By adjusting the control parameters in the PLL and DC link voltage controllers, system stability can be improved. Time-domain results verify the analysis and the findings.

关键词： weak grids full-converter wind active power output control parameters subsynchronous oscillation eigenvalue analysis

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Sensitivity analysis on Gaussian quantum-behaved particle swarm optimization control parameters

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SOFT COMPUTING 2023年第13期27卷 8759-8774页

作者： Rugveth, Vankayala Sai Khatter, Kiran BML Munjal Univ Dept Comp Sci Gurgaon India

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that falls under the category of nature-inspired algorithms and is similar to evolutionary computing in various ways. Rather than the survival of the fittest, the PSO is driven by a representation of a social psychological model inspired by the group behaviors of birds and other social species. The particle's position is modified in PSO based on its position as well as velocity, while in quantum mechanics, the trajectory idea is absurd;however, the uncertainty principle suggests that a particle's position, as well as velocity, cannot be determined simultaneously. As a result, an advanced version of the quantum mechanics-based PSO method is proposed. The study in this paper is focused on an investigation of a new quantum-behaved PSO (QPSO) method called Gaussian quantum-behaved particle swarm optimization (GQPSO), which uses a mutation operator with a Gaussian distribution and is inspired by classical PSO methods and quantum mechanics concepts. In GQPSO, inadequate control parameter tuning results in poor solutions. To better understand the effect of different control parameters and their implications on GQPSO results, this paper used a full parametric sensitivity analysis on five different problems (the Design of a pressure vessel, Tension/Spring Compression, Rastrigin function, Ackley function, and Constrained Box Volume Problem). By adjusting each parameter one at a time, different optimization problems were used to investigate GQPSO. As a result, to allow particles to change their earliest best solution based on viability, a constraint-handling mechanism was developed. The optimal parameter set for GQPSO is provided based on the analysis of the results. With the help of the proposed optimal parameter set (contraction-expansion coefficient values as (1 = 1.6,2 = 1.3), swarm size as '350', and number of Iterations as '500'), GQPSO returned an optimized solution for Rastrigin and Ac

关键词： Particle swarm optimization (PSO) Constrained optimization Sensitive analysis Quantum-behaved particle swarm optimization (QPSO) control parameters Optimal parameter set Gaussian quantum-behaved particle swarm optimization-optimal parameter set (GQPSO-OPS)

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