摘要
根据KED原理建立了柔性支腿Stewart平台的动力学模型。针对该机构为一非线性、慢时变、强耦合、多输入多输出等特点，提出了一种基于优化神经网络结构的PID控制算法来实现大射电望远镜馈源高精度轨迹跟踪。理论分析和仿真结果表明，该控制算法不仅能满足馈源轨迹跟踪高精度要求，而且具有较强的鲁棒性。
A dynamic model of a flexible Stewart platform is established based on the principle of KED（Kineto Elastio Dynamic Analysis）. In view of the characteristics of nonlinearity, slow time-variant, strong coupling and MIMO of the system, a novel control method based on improved neural-network （PID-NNC） is utihzed to realize the high-precision trajectory tracking of the feed for the large spherical radio telescope. Combining a practical project, an algorithm of neural-network control is introduced to approximate optimal control. The results of theoretical analysis and simulation examples have shown that the tracking accuracy is much better and the control system has strong robustness.
出处
《高技术通讯》
CAS
CSCD
北大核心
2006年第6期586-590,共5页
Chinese High Technology Letters
基金
国家自然科学基金跨科学部交叉重点项目巨型射电天文望远镜（FAST）总体设计与关键技术研究（10433020）和教育部留学回国人员实验室基金（030401）资助项目.
