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6th Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Wang, Yongxian Wang, Tinghui Li, Tian Li, Huaze Jing, Tianjun Shi, Shengduo Pan, Pengkai China Agr Univ Coll Informat Elect Engn Beijing Peoples R China Dingxi Potato Res Inst Gansu Peoples R China

ISBN: (纸本)9798350373486;9798350373479

With the concept of carbon neutrality and carbon peaking, low-carbon economic operation has become a hot research topic. As an important link, agricultural park can play a huge role in energy saving and emission reduction. This paper takes an agricultural park in Beijing as an example, establishes the energy flow model of the agricultural park and conducts the related modeling, solves the model with the carbon emission and operation cost of online shopping and foreign electricity as the objective function, and gives the optimal scheduling and execution plan of low-carbon operation of the agricultural park. Among them, partial least square method is used to predict the photovoltaic power, and the improved pso algorithm is used to solve the low-carbon and economic operation side. The simulation results show that the model can effectively reduce the carbon emission level of power purchase and promote the economic operation of agricultural parks.

关键词： agricultural park partial least squares method improved pso algorithm scheduling optimization

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Optimization of Cooperative Deployment of Multiple Terminal Defense System

Optimization of Cooperative Deployment of Multiple Terminal ...

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IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)

作者： Li, Jian Wang, Shunhong Dai, Chenchao Tang, Qinhong Tian, Xiaoqiang Xian High Tech Res Inst Xian 710025 Peoples R China 96752 Force Beijing 100000 Peoples R China

ISBN: (纸本)9781538611715

In actual combat needs, it is usually necessary to intercept multiple hatches of high-density incoming targets in one direction. In this paper, the cooperative rules of multi-defense system on target interception are formulated. The objective function of optimization is to increase the uniformity of firepower coverage and the priority index of key direction. Combining with the defense cost, the variable control constraint is introduced. The simulation results show that the deployment scheme under the constraint of variable control can achieve the expected interception effect and save the defense cost, and can effectively solve the deployment optimization problem of the end defense system. The deployment plan is in line with actual combat.

关键词： Cooperative deployment optimization Terminal defense system Interception rule improved pso algorithm

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Tunnel ventilation control system based on Levy Flight Dynamics improved Particle Swarm Optimization algorithm 3

Tunnel ventilation control system based on Levy Flight Dynam...

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3rd International Conference on Energy and Power Engineering, Control Engineering (EPECE)

作者： Huang, Dahao Mu, Li Xian Polytech Univ Sch Comp Sci Xian Peoples R China

ISBN: (纸本)9798350366105;9798350366099

Due to the swift progress of China's transportation sector, the quantity of constructed tunnels in the country is on the rise. The majority of current road tunnels have imprecise or fragmented controls to regulate the activation of the tunnel's ventilation system. However, employing these strategies is likely to lead to unnecessary electricity use and higher operational expenses. This paper introduces an enhanced particle group optimisation algorithm (LD-Ipso) for optimising the ventilator control model in tunnels. The algorithm aims to achieve more precise control of the ventilation group during tunnel operation, enhance fan utilisation, decrease power consumption in road tunnel ventilation, and enhance tunnel operation safety. The utilisation of the Levy Flight Avoidance algorithm in this paper is *** enhance the precision and effectiveness of particle search, the utilisation of adaptive inertia weights and adaptive learning factors ensures a harmonious equilibrium between the particles' global and local search capabilities. Four test functions were chosen for evaluation, and the LD-Ipso algorithms demonstrated superior result quality compared to the pso method, the genetic algorithm, the artificial fish stocks algorithm, and the simulated bees stocks algorithm. Ultimately, the system's effectiveness is evaluated by comparing it to the scenario of a tunnel fan opening. The simulation findings demonstrate that the LD-Ipso algorithm can achieve more precise optimisation of the number of fan openings in real-world situations, resulting in reduced energy consumption during fan operation.

关键词： improved pso algorithm Levy flight Ventilator start optimization Adaptive inertia weights Adaptative learning factor

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The Study of Modified ADRC algorithm for Six Degrees of Freedom Shipboard Stabilized Platform 31

The Study of Modified ADRC Algorithm for Six Degrees of Free...

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31st Chinese Control And Decision Conference (CCDC)

作者： Guo, Lei Wang, Xufeng Liu, Lu Shan, Liang Lin, Rong Li, Jun Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Shanghai Electromech Engn Inst Shanghai 201109 Peoples R China

ISBN: (纸本)9781728101057

The shipboard stabilized system is subject to the large angular disturbance due to the disturbance of the wave. Therefore, it is necessary to study its compensation control method. In this article, the control strategy based on fuzzy active disturbance rejection controller (fuzzy ADRC) is proposed to optimize the control effect of this platform. The rules of fuzzy control are used to automatically adjust some parameters of ADRC. Besides, in order to adjust the parameters within a reasonable range, an improved particle swarm optimization (pso) algorithm is designed, which introduces the probability of mutation to jump out of local optimum. Finally, the results of simulation show that the control strategy for the platform has good performance and strong anti-interference ability.

关键词： Active disturbance rejection controller 6-DOF stabilized platform Fuzzy control improved pso algorithm

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Particle Swarm Optimization algorithm Based on Greedy Strategy for Solving MOP Crowd Pricing Problem 17

Particle Swarm Optimization Algorithm Based on Greedy Strate...

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17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

作者： Yue Zehua Wuhan Univ Technol Wuhan 430063 Hubei Peoples R China

ISBN: (纸本)9781538674451

Aiming at the problem of the task location and the crowdsourcing pricing of the task package under the bilateral mechanism, a multi-objective optimization (MOP) model was established, and the particle swarm optimization algorithm based on the task point perspective and the user perspective based greedy strategy was adopted as the fitness function (pso) to solve. The analysis of the pricing law of the task and the judgment of the reasons for the unfinished task are considered. Firstly, we visualize the task and member's feature information, conduct preliminary analysis, and then further analyze the pricing law through K-means clustering. Secondly, we construct the Logit two-dimensional selection model, and through the function form and regression effect of the model, the impact task is not obtained. The reason for the completion is mainly caused by factors such as insufficient credit and time at the time of pricing

关键词： Greedy strategy improved pso algorithm Crowdsourcing pricing

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Optimization of Static and Dynamic Anti-Windup Compensator using New improved Particle Swarm Optimization algorithm 15

Optimization of Static and Dynamic Anti-Windup Compensator u...

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15th IEEE International Symposium on Computational Intelligence and Informatics

作者： Shareef, Zeeshan Usman, Zubair Rana, Muhammad Asif Univ Paderborn Heinz Nixdorf Inst Paderborn Germany Univ Paderborn Dept Elect Engn Paderborn Germany Georgia Inst Technol Dept Elect Engn Atlanta GA 30332 USA

ISBN: (纸本)9781479953370

In this paper, the optimal static and the dynamic anti-windup compensators (AWC) are designed using a new improved particle swarm optimization (pso) algorithm. The existing optimization techniques for AWC make use of LMI (Linear Matrix Inequality) and various concepts of nonlinear control concepts that require complex mathematics. For this optimization, we have developed and utilized an improved version of pso. In this new improved pso algorithm, first the problem space is explored with constant non-zero inertia factor until the fitness function saturates to a local or global minima. The solution obtained thus far is then further refined by rerunning the algorithm but with inertia factor set to zero. This slight improvement enables a better search for a solution within the already explored problem-space. The optimized static and dynamic AWC is compared with the existing LMI-based AWC for the performance index, and it is observed that the improved pso-based AWC gave better results and optimized value of the performance index.

关键词： compensation control nonlinearities control system synthesis optimal control particle swarm optimisation pso-based AWC fitness function global minima improved pso algorithm improved particle swarm optimization local minima nonzero inertia factor optimal dynamic antiwindup compensators optimal static antiwindup compensators optimization techniques optimized dynamic AWC optimized static AWC performance index problem-space Actuators algorithm design and analysis Heuristic algorithms Optimization Particle swarm optimization Transfer functions

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pso algorithm Based Task Allocation in Dynamic Virtual Enterprise

PSO Algorithm Based Task Allocation in Dynamic Virtual Enter...

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2nd International Conference on Manufacturing Science and Engineering

作者： Jiang, Jianhua Sheng, Buyun Gong, Lixiong Yang, Mingzhong Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China Chongqing Univ Technol Chong Qing Automobile Coll Chongqing 400054 Peoples R China

ISBN: (纸本)9783037850312

To solve the order task allocation in Dynamic Virtual Enterprise (DVE), a multi-goal decision-making model was constructed. As to the model, an improved Particle Swarm Optimization (pso) algorithm based order task allocation method was presented on the basis of analyzing the traditional pso algorithm. The method overcome the deficiencies of prematurely and trapped into local optimal solution easily in traditional pso by adjusting the parameters in algorithm automatically and introducing mutation operation from genetic algorithm. And the TOPSIS based computing method of particle fitness value was researched. Finally, the feasibility of the method was verified by an application example.

关键词： Dynamic Virtual Enterprise improved pso algorithm Order Task Allocation

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Cascaded Learning Generation Framework for Quadrotor UAV Maneuvering Simulation Models

Cascaded Learning Generation Framework for Quadrotor UAV Man...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Zeng, Shaoxiong Yang, Weilong Zhou, Dongao Xu, Xinhai Academy of Military Sciences Beijing100091 China

ISBN: (纸本)9798350337020

The quadrotor unmanned aerial vehicle (UAV) is widely used due to its low maintenance cost, high maneuverability and strong hovering capability. Modeling the quadrotor UAV maneuver and simulating its performance can effectively support airborne intelligent algorithms training such as mission planning and scheduling. Traditional quadrotor UAV maneuver modeling method construct high-order mathematical model based on physics analysis, which require significant expertise and difficult to generalize. In this paper, we analyze the quadrotor UAV maneuvering process and propose a cascaded quadrotor UAV maneuvering model generating framework based on deep neural network. Using long short-term memory (LSTM) network to model each part of the quadrotor UAV maneuvering process individually, and flexibly combine network of each part to obtain varying granularity models. A variable-dimensional particle swarm optimization (pso) algorithm based on detour foraging strategy is proposed to simultaneously determine the LSTM network's hidden layers and neurons of each hidden layer. We validate the effectiveness of the maneuvering model generation framework and the improved pso algorithm through comparative experiments. © 2023 IEEE.

关键词： improved pso algorithm LSTM maneuvering model generation framework quadrotor UAV

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Research on Particle Swarm Optimization-Based UAV Path Planning Technology in Urban Airspace

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DRONES 2024年第12期8卷

作者： Cheng, Qing Zhang, Zhengyuan Du, Yunfei Li, Yandong Civil Aviat Flight Univ China Coll Air Traff Management Guanghan 618300 Peoples R China Beihang Univ Sch Elect Informat Engn Beijing 100191 Peoples R China

Urban airspace, characterized by densely packed high-rise buildings, presents complex and dynamically changing environmental conditions. It brings potential risks to UAV flights, such as the risk of collision and accidental entry into no-fly zones. Currently, mainstream path planning algorithms, including the pso algorithm, have issues such as a tendency to converge to local optimal solutions and poor stability. In this study, an improved particle swarm optimization algorithm (LGpso) is proposed to address these problems. This algorithm redefines path planning as an optimization problem, constructing a cost function that incorporates safety requirements and operational constraints for UAVs. Stochastic inertia weights are added to balance the global and local search capabilities. In addition, asymmetric learning factors are introduced to direct the particles more precisely towards the optimal position. An enhanced L & eacute;vy flight strategy is used to improve the exploration ability, and a greedy algorithm evaluation strategy is designed to evaluate the path more quickly. The configuration space is efficiently searched using the corresponding particle positions and UAV parameters. The experiments, which involved mapping complex urban environments with 3D modeling tools, were carried out by simulations in MATLAB R2023b to assess their algorithmic performance. The results show that the LGpso algorithm improves by 23% over the classical pso algorithm and 18% over the GApso algorithm in the optimal path distance under guaranteed security. The LGpso algorithm shows significant improvements in stability and route planning, providing an effective solution for UAV path planning in complex environments.

关键词： urban environment drones obstacle avoidance improved pso algorithm path planning

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An Emergency Coordinated Control Strategy to Improve the Transient Stability of a Single-Ended Distribution Network with Flexible Interconnection Channel Blocking

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SENSORS 2023年第20期23卷 8467页

作者： Ma, Rui Sun, Haichang Qin, Liang State Grid Jibei Elect Power Co Beijing 100052 Peoples R China Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China

Based on the scenario of high-penetration distributed photovoltaic connected to an AC/DC distribution network, this paper analyzes the dynamic characteristics of frequency and voltage in a distribution network after the blocking failure of the flexible interconnection channel. In order to enhance the transient stability of the system after the fault, this paper comprehensively considers the active regulation ability of photovoltaic units, and puts forward an emergency coordinated control strategy for a single-ended distribution network with flexible interconnection channel blocking. Firstly, the non-fault channel is overloaded for a short time, then the comprehensive influence of factors such as electrical distance, response time and adjustment cost on the frequency modulation effect of the system is quantitatively evaluated;according to the evaluation results, the photovoltaic and synchronous units are controlled by "control instead of tripping", and finally, the high-frequency tripping is carried out, based on the principle of "photovoltaics first". After the frequency control is completed, the reactive power optimization model of the system is established, and the improved tabu-particle swarm optimization algorithm is used to solve it, so as to optimize the voltage of the distribution network nodes. Finally, an equivalent simulation model is established to verify the coordinated control strategy.

关键词： AC/DC distribution network blocking coordinated control improved pso algorithm

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