船载炮的射击误差分析及消除方法

基于船舶在海浪中运动模型，结合炮兵射击学原理，研究了船舶摇摆导致火炮基座运动以及杆臂效应导致子惯导初始对准误差等因素对火炮射击的影响，分析了传递对准消除对准误差角的效果。仿真表明，低射界射击情况下，纵摇和横摇对射击距离的影响随射程增大而减小；对射击方向而言，纵摇的影响随射程增大而减小，而横摇的影响则随射程增大而增大；由安装偏差所造成的杆臂效应产生的误差角对射击的影响也很明显，其影响随船舶振荡运动的幅度的增加而增大；采用基于卡尔曼滤波的传递对准能快速消除船载炮初始对准角误差，从而提高火炮初始装定射角的准确性。     

Research on Motion Estimation Algorithm of Star Point Based on Nonlinear Gaussian Fitting

The energy distribution model of motion blurred star point is analyzed. The distribution of the star point approximates to a two-dimensional (2D) Gaussian distribution under degeneration. Two multi-parameter nonlinear Gaussian fitting methods (GFMs) are proposed, and the relationship between fitting parameters and motion blur parameters is analyzed. Estimation of the parameters of motion blur by fitting parameters is calculated to realize the error compensation of the motion blur. The simulation results show the effectiveness and accuracy.     

Particle Filter and Its Application in the Integrated Train Speed Measurement

Particle filter(PF) can solve the problem of state estimation under strong non-linear non-Gaussian noise condition with respect to traditional Kalman filter(KF) and those improved KFs such as extended KF(EKF) and unscented KF(UKF). However, problems such as particle depletion and particle degradation affect the performance of PF. Optimizing the particle set to high likelihood region with intelligent optimization algorithm results in a more reasonable distribution of the sampling particles and more accurate state estimation. In this paper, a novel bird swarm algorithm based PF(BSAPF) is presented. Firstly, different behavior models are established by emulating the predation, flight, vigilance and follower behavior of the birds. Then, the observation information is introduced into the optimization process of the proposal distribution with the design of fitness function. In order to prevent particles from getting premature(being stuck into local optimum) and increase the diversity of particles, Lévy flight is designed to increase the randomness of particle's movement. Finally,the proposed algorithm is applied to estimate the speed of the train under the condition that the measurement noise of the wheel sensor is non-Gaussian distribution. Simulation study and experimental results both show that BSAPF is more accurate and has more effective particle number as compared with PF and UKF, demonstrating the promising performance of the method.     

智能自适应控制及其在船舶操纵系统中的应用

主要分析了基于模糊控制，专家系统与神经网络的几种智能自适应控制系统的结构，原理，并与传统控制作了比较，介绍了智能自适应控制在船舶操纵系统中的应用情况，最后提出了智能自适应控制理论及应用面临的主要困难与亟需解决的问题。     

PID自动舵的自整定专家系统

提出了一种基于专家系统的PID自动舵,利用专家的经验知识和控制规则调节PID控制舵的参数,从而达到对船舶的平稳控制,仿真结果表明控制性能好且实现成本低.