Primary exploration of nonlinear information fusion control theory

By introducing Information fusion techniques into a control field, a new theory of information fusion control （IFC） is proposed. Based on the theory of information fusion estimation, optimal control of nonlinear discrete control system is investi- gated. All information on control strategy, including ideal control strategy, expected object trajectory and dynamics of system, are regarded as measuring information of control strategy. Therefore, the problem of optimal control is transferred into the one of information fusion estimation. Firstly, the nonlinear information fusion estimation theorems are described. Secondly, an algorithm of nonlinear IFC theory is detailedly deduced. Finally, the simulation results of manipulator shift control are given, which show the feasibility and effectiveness of the presented algorithm.

基于水位、流量预测信息的水闸群调节方法

针对水闸群闭环控制难以稳定运行问题,基于信息融合技术,通过引入明渠水动力学关系、并在系统输入变量上叠加"误差流量",实现分散且孤立的实时监测数据之间的关联,使闸群水流系统具有必要的信息冗余,以实现水闸群的水情信息融合,进而进行动态预测。并基于水位、流量等水情预测信息,通过增加水闸调节输入信息的途径,提出一种改进水闸群调节的方法。通过模拟试验测试并验证了该方法对改进PID调节具有较好的效果。