A simplified equivalent model of microgrid, based on the RBF Artificial Neural Network, is present in this paper. The proposed model is suitable for the dynamic studies of microgrids. Nonlinear mapping of RBF neural n...
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ISBN:
(纸本)9781479950324
A simplified equivalent model of microgrid, based on the RBF Artificial Neural Network, is present in this paper. The proposed model is suitable for the dynamic studies of microgrids. Nonlinear mapping of RBF neural network describes the dynamic characteristics of the Point of Common Couple(PCC) of micro-grid under the connected mode. The development model is evaluated using the voltage, current and power of the PCC as the input and output of the RBF neural network in the train process. The PSO algorithm is used for the parameter optimization of RBF and improved the generalization of the dynamic model. The simulation results show the proposed modeling method in this paper is suitable and effective, and the RBF neural network based dynamic model can describe the dynamic characteristics of micro-grid accurately.
The optimal technological parameters of a waster paper's enzymatic deinking process with strong coupling, nonlinear and large time delay are difficult to achieve. BP neural network and improved particleswarm opti...
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ISBN:
(纸本)9781479925650
The optimal technological parameters of a waster paper's enzymatic deinking process with strong coupling, nonlinear and large time delay are difficult to achieve. BP neural network and improved particleswarmoptimization (PSO) were applied to optimize enzymatic deinking process of waste paper. The theory and process were described. Enzymes dosage, temperature and pH were used as inputs of the network, a BP neural network model of the effective residual ink concentration (ERIC) and brightness of the pulp was established. The model had higher prediction precision compared with traditional regression model. The PSO was used to obtain the optimal conditions of deinking process with the lowest ERIC and highest brightness of the pulp. Experiments' results proved the method was an excellent tool for optimization of enzymatic deinking process.
Ionic polymer metal composites (IPMCs) are a type of electroactive polymer (EAP) that can be used as both sensors and actuators. An IPMC has enormous potential application in the field of biomimetic robotics, medical ...
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Ionic polymer metal composites (IPMCs) are a type of electroactive polymer (EAP) that can be used as both sensors and actuators. An IPMC has enormous potential application in the field of biomimetic robotics, medical devices, and so on. However, an IPMC actuator has a great number of disadvantages, such as creep and time-variation, making it vulnerable to external disturbances. In addition, the complex actuation mechanism makes it difficult to model and the demand of the control algorithm is laborious to implement. In this paper, we obtain a creep model of the IPMC by means of model identification based on the method of creep operator linear superposition. Although the mathematical model is not approximate to the IPMC accurate model, it is accurate enough to be used in MATLAB to prove the control algorithm. A controller based on the active disturbance rejection control (ADRC) method is designed to solve the drawbacks previously given. Because the ADRC controller is separate from the mathematical model of the controlled plant, the control algorithm has the ability to complete disturbance estimation and compensation. Some factors, such as all external disturbances, uncertainty factors, the inaccuracy of the identification model and different kinds of IPMCs, have little effect on controlling the output block force of the IPMC. Furthermore, we use the particle swarm optimization algorithm to adjust ADRC parameters so that the IPMC actuator can approach the desired block force with unknown external disturbances. Simulations and experimental examples validate the effectiveness of the ADRC controller.
At present, the particle swarm optimization algorithm is not effective in dealing with discrete variables, avoiding local optimization, and satisfying all inequality constraints of voltage and power factor. Therefore,...
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ISBN:
(纸本)9787564112493
At present, the particle swarm optimization algorithm is not effective in dealing with discrete variables, avoiding local optimization, and satisfying all inequality constraints of voltage and power factor. Therefore, this paper employs variable reflection and integralization to find the discrete correspondent of continuous variable in the particle;and introduces chaos strategy to the searching process to strengthen the capability of finding global optimization solution. Then this paper improves the optimization solution by adjusting the voltage and power factor that exceed limits with "nine palaces" strategy, to ensure the particles in feasible solution space. At last, this paper tests the proposed algorithm with the standard IEEE sample system and some actual network planning. The comparison of calculation results with those in other literatures proves that the new algorithm has more advantages at searching speed and quality.
The proportion of different AGC unit under the shortfall of power in the grid is investigated. The paper adopt PSO algorithm to optimize units of AGC (automatic generation control) which regulate the distribution of p...
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ISBN:
(纸本)9781424428946
The proportion of different AGC unit under the shortfall of power in the grid is investigated. The paper adopt PSO algorithm to optimize units of AGC (automatic generation control) which regulate the distribution of power and be in CPS controlling strategy. The optimal solution is hard to obtain by using average distribution but can be worked by using standard PSO algorithm, and then the CPS level can achieve the optimal under economic conditions. The paper proved the effectiveness of the algorithm by computing example simulation.
作者：
Liu, YiHangzhou Dianzi Univ
Inst Management Sci & Informat Engn Hangzhou 310018 Zhejiang Peoples R China
Logistics distribution locating problem is an important area in Logistics, which select the most reasonable location of distribution centers from many places. This paper establish the Cellular PSO algorithm, which com...
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ISBN:
(纸本)9780769535616
Logistics distribution locating problem is an important area in Logistics, which select the most reasonable location of distribution centers from many places. This paper establish the Cellular PSO algorithm, which combine the particle swarm optimization algorithm and cellular automata. This algorithm was tested in the simulation experiment, and the result indicate that the Cellular PSO algorithm is a effective method of solving the problem of choosing the distribution centers location which can overcome the low precision of the basic particle swarm optimization algorithm. In additional, the Cellular PSO algorithm has high quality and efficiency of searching.
In order to remedy the defect that the determination of weight in fuzzy comprehensive evaluation is impacted by subjectivity, the combination weight is introduced. In this paper, the optimization Model combines the su...
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In order to remedy the defect that the determination of weight in fuzzy comprehensive evaluation is impacted by subjectivity, the combination weight is introduced. In this paper, the optimization Model combines the subjective weight and objective weight, which is solved by PSO, is built. At the same time, In order to give full consideration to the uncertain and fuzzy factors which involved in the grid planning, this paper combines the combination weight and fuzzy comprehensive evaluation to assess the grid-planning scheme. The calculation results of IEEE Garver-6 show that the proposed fuzzy comprehensive evaluation system is clear in theory and convenient to calculate, the combination weight is objective and reasonable as well as its results are scientific and intuitive.
In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with c...
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ISBN:
(纸本)9781479935130
In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In our framework, we propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as an amplify-and-forward two-way relays, they are used to support PUs to achieve their target data rates over the remaining bandwidth. More specifically, CUs acts as relays for the PUs and gain some spectrum as long as they respect a specific power budget and primary quality-of-service constraints. In this context, we first derive closed-form expressions for optimal transmit power allocated to PUs and CUs in order to maximize the cognitive objective. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the optimal relay amplification gains and optimal cognitive released bandwidths as well. Our numerical results illustrate the performance of our proposed algorithm for different utility metrics and analyze the impact of some system parameters on the achieved performance.
Smart railway trajectory planning is one of the most interesting and important topics in the fields of intelligent railway transportation, computer science and evolutionary computation, etc. Several objectives and con...
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ISBN:
(纸本)9781479960798
Smart railway trajectory planning is one of the most interesting and important topics in the fields of intelligent railway transportation, computer science and evolutionary computation, etc. Several objectives and constraints of railway trajectory planning problem are closely related to the distance factor, the construction cost, the altitude factor and the comfortability, etc. More importantly, the new particleswarmoptimization (PSO) algorithm, including two optimization sub-stages, firstly optimize the coordinate in y-axis and secondly optimize the latitude in z-axis to design the optimal 3-D railway trajectory. Numerical results highlight that the new two-stages PSO algorithm can provide one realistic optimal trajectory from any two cities in the complicated three-dimensional GIS scenario, such as Chang Sha city and Nan Chang city.
The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this *** path planning problem is decomposed into the sensor deployment problem and the travelling...
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ISBN:
(纸本)9781479946983
The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this *** path planning problem is decomposed into the sensor deployment problem and the travelling salesman problem based on the fundamental finding that the vehicle could search the region that covered by the sensor if the vehicle pass through the position where the sensor is *** positions of the sensors deployed to cover the region completely are obtained by solving the sensor deployment *** the positions of the deployed sensors as the waypoints that the vehicle has to travel through,the shortest path connecting all the waypoints can be obtained by solving the travelling salesman *** cooperatively coevolving particle swarm optimization algorithm with multiple update rules is newly developed for the sensor deployment *** simulation results demonstrate the feasibility of the proposed methods.
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