加速遗传算法在衬砌渠道横断面设计中的应用

一般的衬砌渠道横断面设计,需要进行反复试算和查图,计算量大,且精度不理想。可以将圆角梯形渠道渠底底宽计算问题转化为非线性问题后进行衬砌渠道横断面设计,并采用基于实数编码的加速遗传算法求解参数。结果表明这种方法计算精度高,能够满足工程设计需要,切实可行。

OPTIMAL DESIGN OF DUAL STATOR-WINDING INDUCTION GENERATOR WITH PWM CONVERTER

To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load are proposed. The optimization method of excited capacitors to minimize the reactive power of the control winding at a variable speed is given. The calculation capacity of the machine with a diode bridge rectifier load is proposed. To achieve global searching, the integrated method with the improved real-coded genetic algorithm and the twodimensional finite element method （FEM） is introduced. Design results of the sample show that reactive power can be reduced by the method, and the converter capacity can be decreased to 1/3 of output rated power at the speed ratio of 1 ： 3, thus reducing the volume and the mass of the inverter.

ANN Model and Learning Algorithm in Fault Diagnosis for FMS

The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm

On grey relation projection model based on projection pursuit

Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.

Distance Concentration-Based Artificial Immune Algorithm

The diversity, adaptation and memory of biological immune system attract much attention of researchers. Several optimal algorithms based on immune system have also been proposed up to now. The distance concentra- tion-based artificial immune algorithm (DCAIA) is proposed to overcome defects of the classical artificial immune al- gorithm (CAIA) in this paper. Compared with genetic algorithm (GA) and CAIA, DCAIA is good for solving the prob- lem of precocity,holding the diversity of antibody, and enhancing convergence rate.

Neuron PI control for semi-active suspension system of tracked vehicle

A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude,pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square (RMS) of the vertical amplitude decreases by 37.2%,and 45.2% for the pitch angle,38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%,the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.

Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm

A sound speed profile plays an important role in shallow water sound propagation.Concurrent with in-situ measurements,many inversion methods,such as matched-field inversion,have been put forward to invert the sound speed profile from acoustic signals.However,the time cost of matched-field inversion may be very high in replica field calculations.We studied the feasibility and robustness of an acoustic tomography scheme with matched-field processing in shallow water,and described the sound speed profile by empirical orthogonal functions.We analyzed the acoustic signals from a vertical line array in ASIAEX2001 in the East China Sea to invert sound speed profiles with estimated empirical orthogonal functions and a parallel genetic algorithm to speed up the inversion.The results show that the inverted sound speed profiles are in good agreement with conductivity-temperature-depth measurements.Moreover,a posteriori probability analysis is carried out to verify the inversion results.

Method for optimizing manipulator's geometrical parameters and selecting reducers

A geometrical parameters optimization and reducers selection method was proposed for robotic manipulators design. The Lagrangian approach was employed in deriving the dynamic model of a two-DOF manipulator. The flexibility of links and joints was taken into account in the mechanical structure dimensions optimization and reducers selection, in which Timoshenko model was used to discretize the hollow links. Two criteria, i.e. maximization of fundamental frequency and minimization of self-mass/load ratio, were utilized to optimize the manipulators. The NSGA-II (fast elitist nondominated sorting genetic algorithms) was employed to solve the multi-objective optimization problem. How the joints flexibility affects the manipulators design was analyzed and shown in the numerical analysis example. The results indicate that simultaneous consideration of the joints and the links flexibility is very necessary for manipulators optimal design. Finally, several optimal combinations were provided. The effectiveness of the optimization method was proved by comparing with ADAMS simulation results. The self-mass/load ratio error of the two methods is within 10%. The maximum error of the natural frequency by the two methods is 23.74%. The method proposed in this work provides a fast and effective pathway for manipulator design and reducers selection.

Optimization of band gaps of 2D photonic crystals by the rapid generic algorithm

Based on the rapid genetic algorithm(RGA),the band gap structures of square lattices with square scatters are optimized.In the optimizing process,gene codes are used to express square scatters and the fitting function adopts the relative values of the largest absolute photonic band gaps(PBGs).By changing the value of filling factor,three cell forms with large photonic band gaps are obtained.In addition,the comparison between the rapid genetic algorithm and the general genetic algorithm(GGA) is analyzed.

Aerodynamic Optimum Design of Transonic Turbine Cascades Using Genetic Algorithms

This paper presents an aerodynamic optimum design method for transonic turbine cascades based on the Genetic Algorithms coupled to the inviscid flow Euler solver and the boundary-layer calculation.The Genetic Algorithms control the evolution of a population of cascades towards an optimum design.The fitness value of each string is evaluated using the flow solver. The design procedur6 has been developed and the behavior of the genetic algorithms has been tested. The objective functions of the design examples are the minimum mean-square deviation between the aimed pressure and computed pressure and the minimum amount of user expertise.

Multi-objective optimization of the streamlined head of high-speed trains based on the Kriging model

As the running speed of high-speed trains increases, aerodynamic drag becomes the key factor which limits the further increase of the running speed and energy consumption. Aerodynamic lift of the trailing car also becomes the key force which affects the amenity and safety of the train. In the present paper, a simplified CRH380A high-speed train with three carriages is chosen as the model in order to optimize aerodynamic drag of the total train and aerodynamic lift of the trailing car. A constrained mul- ti-objective optimization design of the aerodynamic head shape of high-speed trains based on adaptive non-dominated sorting genetic algorithm is also developed combining local function three-dimensional parametric approach and central Latin hypercube sampling method with maximin criteria based on the iterative local search algorithm. The results show that local function parametric approach can be well applied to optimal design of complex three-dimensional aerodynamic shape, and the adaptive non-dominated sorting genetic algorithm can be more accurate and efficient to find the Pareto front. After optimization the aerodynamic drag of the simplified train with three carriages is reduced by 3.2%, and the lift coefficient of the trailing car by 8.24%, the volume of the streamlined head by 2.16%; the aerodynamic drag of the real prototype CRH380A is reduced by 2.26%, lift coefficient of the trailing car by 19.67%. The variation of aerodynamic performance between the simplified train and the true train is mainly concentrated in the deformation region of the nose cone and tail cone. The optimization approach proposed in the present paper is simple yet efficient, and sheds lights on the constrained multi-objective engineering optimization design of aerodynamic shape of high-speed trains.