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Performance analysis of hybrid geometric-probabilistic shaped 8/12 quadrature amplitude modulation for coherent optical communication system

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OPTICAL ENGINEERING 2023年第6期62卷 068104-068104页

作者： Xu, Junping Ma, Jie Liu, Jianfei Lu, Jia Zeng, Xiangye Luo, Mingming Hebei Univ Technol Sch Elect & Informat Engn Tianjin Peoples R China Tianjin Key Lab Elect Mat & Devices Tianjin Peoples R China Hebei Key Lab Adv Laser Technol & Equipment Tianjin Peoples R China

. A hybrid shaping (HS) scheme based on geometric shaping (GS) and probabilistic shaping (PS) in a coherent optical communication system is proposed. A particle swarm optimization algorithm and Maxwell-Boltzmann distribution are employed to sequentially implement GS and PS. The results demonstrate that hybrid shaped 8/12-ary quadrature amplitude modulation (HS-8/12QAM) is superior to regular-8/12QAM (R-8/12QAM) in terms of reducing the bit error rate (BER) and increasing the generalized mutual information (GMI). HS-8QAM achieves a 2 dB optical signal-to-noise ratio (OSNR) gain and 0.45bits/symbol GMI gain compared with R-8QAM. Meanwhile, HS-12QAM achieves 1.9 dB OSNR gain and 0.68 bits/symbol GMI gain compared with R-12QAM. In addition, HS-8/12QAM is better than R-8/12QAM in terms of transmission distance and data rate.

关键词： coherent optical communication particle swarm optimization algorithm hybrid shaping generalized mutual information

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Research on fault location algorithm of TPSS based on PSOA

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PEERJ COMPUTER SCIENCE 2023年 9卷 e1213页

作者： Jia, Yunqian Shanghai Inst Technol Sch Railway Transport Shanghai Peoples R China

It is extremely important to research traction power supply system (TPSS) protection technology in order to ensure the safe operation of urban rail transit. A TPSS includes rails, return cables, rail potential limiting devices, one-way conducting devices, drainage cabinets, ballast beds, and tunnel structural reinforcements. In urban rail transit, on the basis of the dynamic characteristics of the TPSS, a fault location algorithm based on particle swarm optimization algorithm (PSOA) is developed. An evaluation of multi-point monitoring data is proposed based on fuzzy processing of the average value of polarization potential forward deviation and multi-attribute decision-making. Monitoring points and standard comparison threshold values are determined by the distribution law of stray currents. In conjunction with the actual project, the model is trained using field measured data. Based on the results, TPSSOA is able to achieve optimal discharge current control, reduce network losses and improve power quality. Moreover, the reconstruction results demonstrate the high usability of the proposed method, which will provide guidance to design the TPSS in the future.

关键词： Traction power supply Machine learning particle swarm optimization algorithm Fault location

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Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

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PHYSICAL COMMUNICATION 2023年第1期57卷

作者： Tan, Fangqing Xu, Xu Chen, Hongbin Li, Shichao Guilin Univ Elect Technol Guangxi Key Lab Wireless Wideband Commun & Signal Guilin 541004 Peoples R China Guilin Univ Elect Technol Sch Informat & Telecommun Guilin 541004 Peoples R China

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input-single-output system. In particular, considering the system circuits' energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user' rate requirement, the BS's maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element's working state is controlled by a circuit switch, each reflection element's switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Reconfigurable intelligent surface Energy efficiency Beamforming Sine cosine algorithm particle swarm optimization algorithm

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Optimal design and dynamic performance analysis of a fractional-order electrical network-based vehicle mechatronic ISD suspension

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2023年 184卷

作者： Shen, Yujie Hua, Jie Fan, Wei Liu, Yanling Yang, Xiaofeng Chen, Long Jiangsu Univ Res Inst Automot Engn Zhenjiang 212013 Peoples R China Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China

To further explore the beneficial effects of the vibration isolation performance of a new vehicle ISD (inerter-spring-damper) suspension using a mechatronic inerter, this paper proposes a novel optimal design methodology for a vehicle mechatronic ISD suspension system based on a fractional-order electrical network is proposed. In view of difficulties in the engineering imple-mentation of fractional-order mechanical network elements, this paper first studies the corre-sponding relationship and analytical expression of fractional-order mechanical and electrical network elements respectively. Under the instruction of fractional calculus, the fractional-order electrical network elements are used to realize equivalent fractional-order mechanical network elements by adopting a ball-screw mechatronic inerter. Then, a quarter car dynamic model of vehicle mechatronic ISD suspension is constructed, and the parameters of the fractional-order electrical network and the integer-order electrical network are obtained by means of particle swarm optimization algorithm. The performance advantages of vehicle mechatronic ISD sus-pension using a fractional-order electrical network are verified by numerical simulations and experiments. The results show that, compared with the application of an integer-order electrical network, the vibration suppression performance of a vehicle mechatronic ISD suspension can be further enhanced by using a fractional-order electrical network.

关键词： Vehicle suspension Mechatronic inerter Fractional-order electrical network particle swarm optimization algorithm Optimal design

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A simulation-based optimization for deploying multiple kinds road rescue vehicles in urban road networks

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年第1期181卷

作者： Tan, Zheyi Zhang, Qian Deng, Weiliang Zhen, Lu Shao, Wei Shanghai Univ Sch Management Shang Da Rd 99 Shanghai 200444 Peoples R China Shanghai Univ Sci Res Management Dept Shang Da Rd 99 Shanghai 200444 Peoples R China

In the rescue process of urban road traffic accidents, the decision-making support system is of great importance since it will affect the rescue response time, and the response time is used as an evaluation index of the system performance. A shorter response time can ensure that casualties are rescued timely and can help restore the road as soon as possible. This paper provides a decision tool for traffic accident rescue vehicles' integrated deployment problem in urban areas. In order to better simulate the stochastic rescue requests, the time and space distribution of traffic, and the dynamic rescue process, a simulation optimization model is established. This model determines the optimal deployment plan for three kinds of road rescue vehicles, i.e., ambulances, wreckers, and sweepers, in several time intervals in one day. To find a better solution, we incorporate a particle swarm optimization (PSO) method into the simulation and optimization procedures. The proposed method is validated by a case study in Shanghai. Additionally, sensitivity analysis is included to study the effects of various parameters and to confirm effectiveness and efficiency of the proposed method. The numerical experiments indicate that simply increasing the number of road rescue resources does not always improve the efficiency of road rescue.

关键词： Traffic accident rescue Vehicle deployment Simulation optimization particle swarm optimization algorithm

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Optimizing the Operation Sequence of Chip Shooter Machine Based on the particle swarm optimization algorithm

Optimizing the Operation Sequence of Chip Shooter Machine Ba...

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2nd International Conference on Advanced Design and Manufacturing Engineering (ADME 2012)

作者： Liang, Wanlei Guan, Xiaodan North China Inst Aerosp Engn Dept Elect Engn Langfang 065000 Peoples R China

ISBN: (纸本)9783037855034

The mounting process is the key factor of the placement efficiency, it is also important for the improvement of the efficiency of whole production line and decrease of the cost. This paper analyzed the mounting process of the Chip Shooter machine, applied the PSO algorithm, constructed the corresponding coding system, proposed the corresponding particle update mechanism, introduced the partially matched crossover idea of the genetic algorithm into the PSO algorithm, and designed the new re-scheduling method of feeder position assignment to optimize the position assignment of feeders and the pickup and placement sequence of components, thus improved the placement efficiency. After comparing the results before and after the simulation test for selected 8 pieces of PCB, the average efficiency of this algorithm is 7.09% higher than genetic algorithm method that is based on sort encoding. The experimental result shows that, this algorithm is more efficiency on the improvement placement efficiency and decrease of the placement time for the chip shooter machine.

关键词： Chip shooter machine Operation sequence optimization particle swarm optimization algorithm

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Constrained Multi-objective particle swarm optimization algorithm

Constrained Multi-objective Particle Swarm Optimization Algo...

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8th International Conference on Intelligent Computing (ICIC)

作者： Gao, Yue-lin Qu, Min N Ethn Univ Inst Informat & Syst Sci Yinchuan Ningxia Peoples R China

ISBN: (纸本)9783642318368

A particle swarm optimization for solving constrained multi-objective optimization problem was proposed (CMPSO). In this paper, the main idea is the use of penalty function to handle the constraints. CMPSO employs particle swarm optimization algorithm and Pareto neighborhood crossover operation to generate new population. Numerical experiments are compared with NSGA-II and MOPSO on three benchmark problems. The numerical results show the effectiveness of the proposed CMPSO algorithm.

关键词： particle swarm optimization algorithm constrained multi-objective optimization Pareto neighborhood crossover operation penalty function method

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Mutual inductance identification of non-contact excitation system

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ADVANCES IN MECHANICAL ENGINEERING 2024年第8期16卷

作者： Li, Ke Ding, Jie Sun, Xiaodong Meng, Xuan Jiangsu Univ Sch Elect & Informat Engn Zhenjiang Peoples R China Jiangsu Univ Automot Engn Res Inst Xuefu Rd 31 Zhenjiang 212013 Peoples R China

Due to the presence of brush and slip ring in the excitation method of electrically excited synchronous motors, this article proposes a new excitation method - non-contact excitation system. This method transfers electrical energy from the stator to the rotor through magnetic coupling, replacing slip ring and brush. However, the magnetic coupling coils at the primary and secondary ends of the system will deviate, which will affect motor operation quality. In order to effectively reduce the changes caused by mutual inductance, this article proposes an improved particle swarm optimization algorithm for mutual inductance identification. This improved algorithm can effectively reduce the shortcomings of low accuracy and easy to fall into local optima in particle swarm optimization. Simulation and experimental results show that the improved particle swarm optimization algorithm can improve search accuracy.

关键词： Non-contact excitation wireless power transfer mutual inductance identification particle swarm optimization algorithm

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PSO-NMPC control strategy based path tracking control of mining LHD (scraper)

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SCIENTIFIC REPORTS 2024年第1期14卷 1-28页

作者： Liu, Ya Peng, Ping-an Wang, Li-guan Wu, Jia-xi Lei, Ming-yu Zhang, Chao-wei Lei, Ru Cent South Univ Sch Resources & Safety Engn Changsha 410083 Peoples R China Minist Educ Xinjiang Inst Engn Key Lab Xinjiang Coal Resources Green Min Urumqi 830023 Peoples R China

The automation of underground articulated vehicles is a critical step in advancing digital and smart mining. Current nonlinear model predictive control (NMPC) controllers face challenges such as delays in turning on large curvature paths and correction lags during the control of underground the Load-Haul-Dump (LHD). To address these issues, this paper proposes a PSO-NMPC control strategy that integrates a particle swarm optimization algorithm (PSO) into the NMPC controller to enhance path tracking for LHDs. To verify the effectiveness of the proposed PSO-NMPC control strategy, the local path of the tunnels is selected as the simulation path, comparing it with the pure NMPC controller based on the path characteristics of the actual tunnel. The results demonstrate that the improved NMPC controller significantly enhances the trajectory tracking performance of the LHD, with maximum absolute lateral deviations for experimental paths 2, 3, and 5 improved by 89.7%, 72.2%, and 68.9%, respectively. Additionally, the improved NMPC controller exhibits superior performance in paths with large curvature compared to those with very small curvature and straight-line paths, effectively addressing the challenges of turn delay and backward lag in LHD operation, thus providing practical significance.

关键词： Mining LHD Nonlinear model predictive control particle swarm optimization algorithm PSO-NMPC control strategy Path tracking control

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Vehicle path planning method based on particle swarm optimization algorithm

Vehicle path planning method based on particle swarm optimiz...

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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Yu, Sheng-long Bo, Yu-ming Chen, Zhi-min Zhu, Kai Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9783037853696

A particle swarm optimization algorithm (PSO) is presented for vehicle path planning in the paper. particle swarm optimization proposed by Kennedy and Eberhart is derived from the social behavior of the birds foraging. particle swarm optimization algorithm a kind of swarm-based optimization *** simulation experiments performed in this study show the better vehicle path planning ability of PSO than that of adaptive genetic algorithm and genetic algorithm. The experimental results show that the vehicle path planning by using PSO algorithm has the least cost and it is indicated that PSO algorithm has more excellent vehicle path planning ability than adaptive genetic algorithm,genetic algorithm.

关键词： particle swarm optimization algorithm genetic algorithm vehicle path planning

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