欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为解决船舶营运中存在的模型参数摄动和外界干扰的不确定性问题，提出一种船舶航向自适应PD控制算法．采用免疫克隆选择算法进行在线船舶模型辨识，将存在不确定干扰和模型摄动的船舶作为一个“黑箱”，将短时间内的船舶状态在线辨识为二阶线性模型，根据系统预定性能要求动态调整PD控制参数，使船舶获得理想输出．对抗体初始种群采用最优模型保留和随机初始化相结合的策略，提高了不确定性问题的在线优化效率．对一个三阶非线性货船的仿真试验表明，该算法有效提高了PD控制器的稳态性能．
英文摘要：
An adaptive PD control algorithm was developed to deal with the problems of model parameter perturbation and external disturbance uncertainty in ship steering. Immune clonal selection algorithm was used in on-line ship model identification. The actual ship with disturbance and model uncertainty, regard- ed as a black box, was identified as a second-order linear model, then PD controller was dynamically tuned according to given system performance together with the identified model, and the ideal output of the ship was obtained. The combination of opti- mal candidate reservation with stochastic initialization was adopted for the initial population to improve the on-line optimization efficiency for dynamical uncertain problem. Simulations on the third-order nonlinear cargo vessel show that the proposed adaptive algorithm greatly improves the steady state performance of PD controller.
同期刊论文项目
同项目期刊论文
Neural-network-based simple adaptive control of uncertain multi-input multi-output non-linear system
A Novel Robust Adaptive-Fuzzy-Tracking Control for a Class of Nonlinear Multi-Input/Multi-Output Sys
Observer-based adaptive fuzzy backstepping dynamic surface control for a class of MIMO nonlinear sys
Adaptive neural output feedback controller design with reduced-order observer for a class of uncerta
Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown t
期刊信息
位置：