Wei Ping Zhao

Fiber Orientation Angles Optimization for Maximum Fundamental Frequency of Laminated Composite Plates by the Genetic Algorithm and Meshless Method

Fiber orientation angles optimization is carried out for maximum fundamental frequency of clamped laminated composite plates using the genetic algorithm. The meshless method is utilized to calculate the fundamental frequency of clamped laminated composite plates. In the present paper, the maximum fundamental frequency is an objective function; design variables are a set of fiber orientation angles in the layers. The examples of square laminated plates are considered. The results for the optimal fiber orientation angles and the maximum fundamental frequencies of the 2-layer plates are presented.

Longitudinal Nonlinear PID Controller Parameter Optimization of Autopilot Using Genetic Algorithm

This paper performed the longitudinal nonlinear PID Controller parameter optimization of general aircraft autopilot based on the longitudinal channel model and genetic algorithm. Proportion, integration and differential gain of nonlinear PID Controller is nonlinear function of controlling error. The objection function involves time integration of error’s absolute value, output of controller and system overshoot. The longitudinal controlling rate optimization of general aircraft autopilot is realized by minimizing the objection function value. Simulation results show that controller designed by the present method is better than traditional PID controller.

Fiber Orientation Angle Optimization for Minimum Stress of Laminated Composite Plates

The genetic algorithm is used to minimize the stress of the laminated composite plates by optimizing the fiber orientation angle. The objective function of optimization problem is the minimum stress in center of laminated composite plates under the external load; optimization variables are fiber orientation angle. The results for the optimal fiber orientation angle and the minimum stress of the 2-layer plates and 3-layer plates are presented.

Tailoring the Fundamental Frequency of Laminated Composite Panels Using Material Properties

Optimization of material properties is performed to maximize the fundamental frequency of the laminated composite panels by means of the genetic algorithm. The global radial basis function collocation method is used to calculate the fundamental frequency of clamped laminated composite panels. In this paper, the objective function of optimization problem is the maximum fundamental frequency; optimization variables are material properties of laminated panels. The results for the optimal material properties and the maximum fundamental frequencies of the 2-layer plates are presented to verify the validity of present method.

Layer Thickness Optimization of Laminated Composite Plates to Maximize the First-Order Natural Frequency

Layer thickness optimization is performed to maximize the first-order natural frequency of clamped laminated composite plates using the genetic algorithm and meshless global radial basis function collocation method. The objective function of optimization problem is the maximum first-order natural frequency; optimization variables are layer thickness. The optimal layer thickness and the maximum first-order natural frequency of the 2-layer plates are presented to demonstrate the accuracy of present method.

Generalized Multiquadrics with Optimal Shape Parameter and Exponent for Deflection and Stress of Functionally Graded Plates

Deflection and stress of simply functionally graded plates are calculated by the meshless collocation method based on generalized multiquadrics radial basis function. The generalized multiquadric radial basis function has the shape parameter c and exponent which have the important effect in the accuracy of the approximation. The deflection and stress of simply functionally graded plates are calculated using the generalized multiquadrics with optimal shape parameter and exponent which is optimized by the genetic algorithm.

Controller Optimization of Quadrotor UAV

Adjusting method of traditional PID controller is complicated. The controller obtained by adjusting method of traditional PID may be not optimal. Therefore, present paper utilized the genetic algorithm to optimize the PID controller parameter of roll channel of quadrotor UAV. According to the feature of lateral stability control model of quadrotor UAV, ascend time of system, steady state error, and weighted overshoot are chosen as objective function. In order to obtain the better control effect, penalty function is used to limit the oscillation of system. Simulation results show that PID controller designed by the genetic algorithm possess the excellent flexibility, adaptability and can produce the better control effect.

Research and Simulation of Image Histogram Matching

This article according to the characteristics of the image enhancement and the histogram of the image properties, using genetic algorithms to improve the image gray-scale. Optimization process is to optimize the shape parameters of a normalized to unit interval doublet Gaussian function. The simulation results show that: the purpose of the image enhancement is pull the distance between object and image in gray-scale coordinates, proving the effectiveness of the methods. Lay the foundation for the binary image and target feature extraction.

Unmanned Helicopter Course PID Controller Parameters Setting and Simulation

In the basis of the rolling angle inside loop controller stability, this paper using genetic algorithm to optimize the parameters of PID, in order to get the flight course outside loop controller parameters constituted by course angle feedback signal. Aiming at the small unmanned helicopter course stability control model features, we choose the rise time of system, the steady-state error and proportion of combination as an optimum target function. To ensure the effect of the controller and reduce the system shock, we introduce system shock times and multiply punishment function. It has better flexibility, adaptability, stability and can guaranty the system controller effect and improves the system capability by adopting the genetic algorithm to develop the PID controller. The simulation results verify the effectiveness of the method that we put forward.

The Threshold Value Segmentation Approach of Images Based on Ant Colony Optimization

This paper briefly introduces the basic principle of threshold partition firstly, and researches an analyses the threshold partition of ant colony optimization based on otsu. The simulation results prove the rapidity and validity of the method which lays the foundation for multi-threshold value segmentation approach.