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optimization control of spacecraft proximation based on r-domination adaptive bare-bones particle swarm optimization algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 278卷

作者： Zhu, Zhihao Guo, Yu Gao, Zhi Yancheng Inst Technol Sch Elect Engn Yancheng Peoples R China Nanjing Univ Sci & Technol Sch Automat Nanjing Peoples R China Yancheng Inst Technol Sch Informat Engn Yancheng Peoples R China

This paper proposes a novel finite-time (FT) optimization control approach of spacecraft proximation based on a new r-domination adaptive bare-bones multi-objective particle swarm optimization scheme (r-ABBMOPSO). Specifically, a new adaptive particle update strategy is developed for bare-bones multi-objective particle swarm optimization algorithm (BBMOPSO) to enhance the robustness of the search. To make the search toward the desired point, r-ABBMOPSO applies r-domination to replace Pareto-domination. In addition, a new adaptive mutation algorithm is designed to strong the population search diversity. By virtue of r-ABBMOPSO to obtain the optimal control parameters, a FT six degrees of freedom (6-DOF) proximation controller with the adaptive update laws of the unknown parameters is proposed to regulate chaser spacecraft approach to target spacecraft. Finally, numerical comparison examples illustrate the performance of the proposed optimization controller.

关键词： Finite-time optimization control Adaptive particle update Adaptive mutation Six degrees of freedom

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Speed optimization control of a Permanent Magnet Synchronous Motor Based on TD3

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ENERGIES 2025年第4期18卷 901-901页

作者： Hu, Zuolei Zhang, Yingjie Li, Ming Liao, Yuhua Hunan Univ Coll Informat Sci & Elect Engn Changsha 410000 Peoples R China Hunan Univ Sci & Technol Sch Informat & Elect Engn Xiangtan 411201 Peoples R China Univ Manchester Dept Mech Aerosp & Civil Engn Manchester M13 9PL England

Permanent magnet synchronous motors (PMSMs) are widely used in industrial automation and electric vehicles due to their high efficiency and excellent dynamic performance. However, controlling PMSMs presents challenges such as parameter variations and system nonlinearities. This paper proposes a twin delayed deep deterministic policy gradient (TD3)-based energy-saving optimization control method for PMSM drive systems. The TD3 algorithm uses double networks, target policy smoothing regularization, and delayed actor network updates to improve training stability and accuracy. Simulation experiments under two operating conditions show that the TD3 algorithm outperforms traditional proportional-integral (PI) controllers and linear active disturbance rejection control (LADRC) controllers in terms of reference trajectory tracking, q-axis current regulation, and speed tracking error minimization. The results demonstrate the TD3 algorithm's effectiveness in enhancing motor efficiency and system robustness, offering a novel approach to PMSM drive system control through deep reinforcement learning.

关键词： PMSM TD3 optimization control energy-saving

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Sensitivity analysis of aero-engine performance optimization control system and its hardware test verification

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2025年第2期42卷 433-446页

作者： Fang, Juan Zhang, Nan Liu, Weimin Wuxi Inst Technol Wuxi 214121 Peoples R China AECC Aeroengine Control Syst Inst Wuxi 214063 Peoples R China

The performance seeking control (PSC) method is aimed at improving the performance of aircraft engine without changing hardware devices. However, the complexity of the system makes it difficult to achieve its application in engineering. Thus, the key issues in PSC of turbofan engine are studied based on global sensitivity analysis, and the improvements are made to the optimization system according to the analysis. Firstly, the principle of PSC is analyzed based on traditional frameworks. And an improved linear programming method based on task scheduling is proposed to reduce the time consumption within a single closed-loop simulation. The impact of the estimation model accuracy on optimization results is studied adopting a sensitivity analysis method based on Monte Carlo sampling to address the optimization lose efficacy. Finally, the hardware-in-the-loop simulation is carried out utilizing model-based design method in a certain type of turbofan engine electronic controller.

关键词： optimization control areo-engine control real-time performance onboard algorithm

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Dynamic of the air pollution pathogenic model and optimization control

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INTERNATIONAL JOURNAL OF BIOMATHEMATICS 2025年第0期

作者： Hippolyte, Bessane Son-Ongaya Merveil Qi, Longxing Anhui Univ Sch Math Sci Jiulong Rd Hefei 230601 Peoples R China

Air pollution is contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics of the atmosphere. In this paper, the ability of air pollutants to affect the occurrence of infectious respiratory diseases in a population is studied by establishing an SISP respiratory disease model. It is found that the inhalation rate of pollutants, based on the daily emission level of pollutants, has a huge impact on the development of respiratory diseases. It is also found that the existence of multiple endemic equilibria, local stability and global stability of the equilibria, all depend on a certain quantity of pollutant produced in the environment. Moreover, the sensitivity analysis shows that the daily emission of pollutants and the inhalation rate of pollutants have significant positive correlation on the model while the clearance rate of pollutants have strong negative correlations with the model. Based on these results, an control strategy is produced in order to reduce the impact of air pollution on the occurrence of respiratory diseases in our environment and it goes as follows: the first step is to reduce the conversion rate of susceptible people to infective by reducing the inhalation rate of pollutant through raising public awareness on how to protect oneself from air pollutants in order to prevent respiratory infections;the second step is to reduce the daily emission of pollutants from all sources of emissions and try to keep it as low as possible;and the last step is to improve the clearance rate of pollutants in the environment.

关键词： Respiratory disease air pollution daily emission level inhalation rate optimization control

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optimization control of modulation-instability gain in photonic crystal fibres with two zero-dispersion wavelengths

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Chinese Physics B 2009年第12期18卷 5375-5384页

作者：王河林冷雨欣徐至展 State Key Laboratory of High Field Laser Physics Shanghai Institute of Optics and Fine MechanicsChinese Academy of Sciences

We design three kinds of photonic crystal fibres （PCF） with two zero-dispersion wavelengths （ZDWs） using the improved full vector index method （FVIM） and finite-difference frequency domain （FDFD} techniques. Based on these designed fibres, the effect of fibre structure, pump power and wavelength on the modulation instability （MI） gain in the anomalous dispersion region close to the second ZDW of the PCFs is comprehensively analysed in this paper. The analytical results show that an optimal MI gain can be obtained when the optimal pump wavelength （1530 nm） is slightly shorter than the second ZDW （1538 nm） and the optimal pump power is 250 W. Importantly, the total MI gain bandwidth has been increased to 260 nm for the first time, so far as we know, for an optimally-designed fibre with ∧ = 1.4 nm and d/∧ = 0.676, and the gain profile became much smoother. The optimal pump wavelength relies on the second ZDW of the PCF whereas the optimal pump power depends on the corporate operation of the optimal fibre structure and optimal pump wavelength, which is important in designing the most appropriate PCF to attain higher broadband and gain amplification.

关键词： modulation instability gain broadband amplification optimization control

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optimization control for the far-distance rapid cooperative rendezvous of spacecraft with different masses

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AEROSPACE SCIENCE AND TECHNOLOGY 2015年第Sep.期45卷 449-461页

作者： Feng, Weiming Zhao, Di Shi, Lei Yang, Kun Zhao, Junfeng Shandong Univ Dept Engn Mech Jinan 260062 Peoples R China Washington Univ Dept Mech Engn & Mat Sci St Louis MO 63130 USA

In this study, the dynamics equation of orbital elements without singularities is used to describe the far-distance cooperative rendezvous of two spacecraft with different masses. The convergent costate vector is obtained using the particle swarm optimization with differential evolution (PSODE) hybrid algorithm to optimize the far-distance cooperative rendezvous process of the spacecraft. This vector is then used as the initial value for a sequential quadratic programming (SQP) algorithm to again optimize within a small range to obtain a convergent, stable solution. This study focuses on optimizing the control of the far-distance rapid cooperative rendezvous of spacecraft with different masses and explores the interactions between the magnitude of the thrust, the duration of the rendezvous, and the fuel consumption. optimization simulation results indicate that when the rendezvous duration is limited to within a certain interval, the optimal process for the rendezvous of spacecraft with different masses is a cooperative manoeuvring type, and an increase in thrust will significantly save fuel. In the case of unrestricted rendezvous duration, as the thrust increases, the rendezvous time decreases, but there is little change in the total fuel consumption. (C) 2015 Elsevier Masson SAS. All rights reserved.

关键词： Cooperative rendezvous Active-passive rendezvous optimization control Particle swarm and differential evolution hybrid algorithm Sequential quadratic programming method

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optimization control of hydrogen engine ignition system based on ACO-BP

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2021年第78期46卷 38903-38912页

作者： Dang, Jinjin Wang, Lijun Luoyang Polytech Sch Automobile & Rail Transit Luoyang 471400 Peoples R China North China Univ Water Resources & Elect Power Sch Mech Engn Zhengzhou 450045 Peoples R China

With the development of new energy, hydrogen fuel engines have become a research boom in the automotive field. But there are abnormal problems such as backfire and pre-ignition during the combustion of hydrogen engines. This paper is based on the Ant Colony optimization-Back Propagation (ACO-BP) algorithm to study the influence of different speed and load conditions on the ignition advance angle, so as to optimize the control of the hydrogen engine. The experimental system is established on a hydrogen engine converted from a 492Q gasoline engine. The prediction of the optimal ignition advance angle was obtained through experiments, and the optimal ignition MAP diagram of the hydrogen engine is constructed. The optimal ignition advance angle under different working conditions can effectively avoid the occurrence of hydrogen engine pre-ignition. The accuracy reaches 0.0018209 when the training reaches 14 times, the fitness between the actual value and the predicted value of ACO-BP training is 0.99921, the verification accuracy reaches 0.99913, and the test accuracy reaches 0.99932. Compared with the three optimization methods, the convergence speed and error accuracy of ACO-BP are significantly better than the BP neural networks and Genetic Algorithm-Back Propagation (GA-BP). This method realized the model of the nonlinear mapping model from hydrogen engine speed and load to optimal ignition advance angle, which is of great significance for solving the problem of abnormal combustion in hydrogen engine. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： optimization control Hydrogen engine ACO-BP Abnormal combustion

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optimization control of bionics shell roofs subjected to snow skidding

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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2007年第7期69卷 1446-1459页

作者： Tesar, Alexander Melcer, Jozef Slovak Acad Sci Inst Construct & Architecture Bratislava 84503 45 Slovakia Univ Zilina Dept Struct Mech Zilina 01026 Slovakia

Dynamic identification and optimization of bionics shell roofs subjected to the snow skidding is dealt with in present paper. The optimization control of structural geometry in order to induce the aimed snow skidding with reduction of dead weight snow loads is aimed. Theoretical, numerical and experimental in situ assessments based on wave approaches of the problem are presented. Structural application in situ on attractive shell roof made of laminated wood with optimization control suggested is presented. Copyright (c) 2006 John Wiley & Sons, Ltd.

关键词： bionics shell dynamic identification optimization control snow skidding structural response ultimate behaviour wave approach wood roof

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optimization control of Front-End Speed Regulation (FESR) Wind Turbine Based on Improved NSGA-II

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IEEE ACCESS 2019年 7卷 45583-45593页

作者： Li Xiaoqing Dong Haiying Li Hongwei Li Mingxue Sun Zhiqiang Lanzhou Jiaotong Univ Sch Automat & Elect Engn Lanzhou 730070 Gansu Peoples R China Lanzhou Jiaotong Univ Sch New Energy & Power Engn Lanzhou 730070 Gansu Peoples R China Lanzhou Univ Technol Sch Energy & Power Engn Lanzhou 730050 Gansu Peoples R China Lanzhou Jiaotong Univ Inst Railway Technol Lanzhou 730000 Gansu Peoples R China

Aiming at the power optimization control problem of front-end speed regulation (FESR) wind turbine, when the wind speed above rated wind speed, an optimal control strategy of variable pitch and variable torque based on improved NSGA-II algorithm is proposed. For this strategy, the reverse learning mechanism was used to initialize and evolve, and the crossover probability and mutation probability were adjusted dynamically based on the exponential distribution. A fuzzy comprehensive evaluation was used to get the best solution from the non-inferior solutions. The objective function was established upon the goals of the constant output speed for hydraulic speed converter and the smoothness of FESR's output power. And pitch angle and vane opening angle were optimized by the improved NSGA-II algorithm. Afterward, the optimization control algorithm has been validated through simulation experiment to a 2MWFESR. The simulation results show that the output power of FESR was smoothed, and the speed fluctuation and power fluctuation of FESR were also reduced, better control performance is thus achieved. Therefore, it is feasible and effective to optimize the control of FESR by the improved NSGA-II algorithm proposed in this paper.

关键词： Front-end speed regulation (FESR) wind turbine hybrid automata power control optimization control improved NSGA-II algorithm

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optimization control method for carbon footprint of machining process

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2017年第5-8期92卷 1601-1607页

作者： Zhang Cuixia Liu Conghu Zhao Xi Suzhou Univ Sch Mech & Elect Engn Suzhou 234000 Peoples R China Shanghai Jiao Tong Univ Antai Coll Econ & Management Shanghai 200030 Peoples R China TRW Automot Technol Shanghai Co Ltd Shanghai 201814 Peoples R China

Energy conservation has become one of the key elements of core competitiveness for manufacturing enterprise. On the basis of studying the characteristics of carbon emissions in machining process, the state space model of carbon footprint for machining process is constructed, and carbon footprint transfer matrix is derived. It reveals the mechanism of generation, transmission, and coupling for carbon footprint in machining process. Considering the machining precision constraints and time constraints, the paper researched on optimization control method for carbon footprint of machining process based on dynamic programming to minimize the carbon emissions. Finally, this method is applied in a fracture splitting workshop, and the result shows this method can reduce 10.28% of carbon emissions in machining process. This paper provides theoretical and technical support for energy saving in machining process.

关键词： Machining Carbon footprint State space optimization control

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