The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization m...
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The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization method is presented to determine the main working parameters of EMSDA on the basis of the built theoretical model. The objective function minimizing the response variance of system under white noise excitation is formulated. The particle swarm optimization algorithm is employed in optimization. The simulated and experimental studies on vibration control by use of EMSDA are conducted. The results show that the electromagnetic shunt damping absorber can attenuate significantly the structural vibration.
In order to achieve precise collision avoidance for large ships, a novel intelligent collision avoidance control approach is presented in this paper. To obtain the precise collision avoidance information capability, a...
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ISBN:
(纸本)9781479931972
In order to achieve precise collision avoidance for large ships, a novel intelligent collision avoidance control approach is presented in this paper. To obtain the precise collision avoidance information capability, a fuzzy set interpretation is developed to handle imprecise information. This allows the introduction of an innovative self-training optimizing search method. The optimizing process is based on the particle swarm optimization algorithm and off-line training data that is obtained from trial manoeuvres based on computer simulations. The resulting controller can decrease the ship operators' burden to deal with bridge data and help them to make timely and precise collision avoidance decision. The results show that the designed intelligent controller performed well to implement the optimizing control of ship collision avoidance.
At present, building energy conservation is a hot topic in urban construction and energy conservation research. Predicting the trend of energy consumption is very meaningful for a whole building energy management. Com...
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ISBN:
(纸本)9781479943678
At present, building energy conservation is a hot topic in urban construction and energy conservation research. Predicting the trend of energy consumption is very meaningful for a whole building energy management. Compared with the other feed-forward neural networks, RBF network learning faster and the ability of function approximation is stronger, but its performance still need to be improved. We use particle swarm optimization algorithm (PSO) to optimize RBF neural network and use the optimized RBF neural network to predict energy consumption in this article. Used the statistical data of the whole society's monthly electricity consumption published online as a sample, and simulated the forecasting method by MATLAB.
In manufacturing process of automobile, people always provide steady illumination during the time when automobile moves on the assembly line. Automobile is moving slowly on the assembly line for surface detection, pai...
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ISBN:
(纸本)9784907764456
In manufacturing process of automobile, people always provide steady illumination during the time when automobile moves on the assembly line. Automobile is moving slowly on the assembly line for surface detection, painting or other operations in the factory, for lower power consumption and giving a satisfaction sufficient to meet a requirement of illumination on the specified surface of automobile, we consider an surface illumination controlling system by establishing a virtual scene for these works. To achieve this target, we provide (i) Illumination Environment Simulation;(ii) Illumination Model;(iii) particle swarm optimization algorithm. The performance of the proposed algorithm shows that we achieved illumination rendering on the surface of automatic vehicle.
Common algorithms of selecting hidden unit data center in RBF neural networks were first discussed in this essay, i.e. k-means algorithm, subtractive clustering algorithm and orthogonal least squares. Meanwhile, a hyb...
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ISBN:
(纸本)9783037859155
Common algorithms of selecting hidden unit data center in RBF neural networks were first discussed in this essay, i.e. k-means algorithm, subtractive clustering algorithm and orthogonal least squares. Meanwhile, a hybrid algorithm mixed of k-means algorithm and particle swarm optimization algorithm was put forward. The algorithm used the position of the particles in particle swarm optimization algorithm to help deal with the defects of local clusters resulted from k-means algorithm and to make optimization with the optimal fitness of k-means particleswarm with the aim to make the final optimal fitness better satisfy the requirements.
The flexible job shop scheduling problem (FJSP) is an extension of the classic job shop scheduling problem (JSP), which breaks through the uniqueness of limit resources, allows a procedure in many machines processing ...
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ISBN:
(纸本)9781479937066
The flexible job shop scheduling problem (FJSP) is an extension of the classic job shop scheduling problem (JSP), which breaks through the uniqueness of limit resources, allows a procedure in many machines processing and one machine processing many kinds of different types of procedures. It is more practical and complex than JSP. The computational complexity of FjSP is much higher, which disables exact solution methods and makes heuristic approaches more qualified. A hybrid optimizationalgorithm, CPSO, based on the cultural algorithm and particle swarm optimization algorithm, is proposed in this paper to solve the FJSP. The objective is to minimize makespan. Computational results show that this hybrid method is able to solve efficiently these kinds of problems.
In this paper, based on particleswarmoptimization (PSO) algorithm to observe the different optimization results by changing the objective function. By comparing indicators of various types of objective function, cle...
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ISBN:
(纸本)9781479958252
In this paper, based on particleswarmoptimization (PSO) algorithm to observe the different optimization results by changing the objective function. By comparing indicators of various types of objective function, clearly showing its intuitive respective advantages and disadvantages. Herein we can derived from the comprehensive objective function is a relatively good target function, stability, accuracy and rapidity performance can better meet the requirements of people.
Bioreactor is one of the prime processing units widely employed to produce important chemical and biochemical compounds. In this paper, a hybrid heuristic algorithm has been attempted to tune PID controller for nonlin...
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ISBN:
(纸本)9781479949816
Bioreactor is one of the prime processing units widely employed to produce important chemical and biochemical compounds. In this paper, a hybrid heuristic algorithm has been attempted to tune PID controller for nonlinear Bioreactor model. The hybrid algorithm is a combination of Bacterial Foraging optimization (BFO) and particleswarmoptimization (PSO) algorithm. Multiobjective performance indexes such as Integral Square Error, peak overshoot are considered to guide this algorithm for discovering best possible value of controller parameters. The controller tuning procedure is individually discussed for both stable and unstable steady state operating region of simulated bio-reactor model. The effectiveness of the proposed scheme has been validated through a comparative study with BFO, PSO based controller tuning methods proposed in the literature. The results show that, the hybrid method provides improved performance in reference tracking and load disturbance rejection with minimal ISE value.
particle swarm optimization algorithm is a simple and effective modern optimizationalgorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence...
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ISBN:
(纸本)9781479951512
particle swarm optimization algorithm is a simple and effective modern optimizationalgorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence proposed. In the iteration of the proposed algorithm, the particles are distinguished to be active or stable according to their velocity information. For the active particles, to maintain the diversity of population, they are replaced by selection from its previous generation's position and its reverse point, which combines the strategy of opposition-based learning. While for the stable particles, to enhance the convergence speed and increase the local search capability, they are improved by conjugate gradient method. The proposed improved PSO algorithm has come through numerical experiments of classic test functions. The results showed that, compared with other improved algorithms, this proposed improved PSO algorithm is feasible and effective.
The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization m...
详细信息
The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization method is presented to determine the main working parameters of EMSDA on the basis of the built theoretical model. The objective function minimizing the response variance of system under white noise excitation is formulated. The particle swarm optimization algorithm is employed in optimization. The simulated and experimental studies on vibration control by use of EMSDA are conducted. The results show that the electromagnetic shunt damping absorber can attenuate significantly the structural vibration.
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