An extended federated filtering (EFF) algorithm is developed which can be applied to integrated navigation system and integrated attitude determination system. According to both information fusion theories and information conversation principle, it is proposed that information allocation is the inverse process of information fusion in EFF algorithm. The information allocation theorem is given and proved, which lays a theoretical foundation for EFF. Taking a certain satellite integrated attitude determination system as an example, the realization of EFF is discussed in detail. The theoretical analysis and simulation results show that EFF algorithm is less computation than present federated filtering algorithm, and EFF can guarantee both local optimum and global optimum, while present federated filtering can only guarantee global optimum.

By introducing information fusion techniques into optimal preview control, a new theory of Information Fusion Optimal Preview Control (IFOPC) for nonlinear discrete system is proposed in this paper. All information on control system which includes ideal control strategy, expected objective trajectory and dynamics of system, is regarded as measure information of control system. Therefore, the problem of optimal control can be transferred into the problem of information fusion estimate. It should be pointed out that the IFOPC consists of optimal co-state generator and optimal regulator, in which the optimal co-state generator is just a extended Kalman filter. Firstly, the information fusion estimate theorems are described in brief. Secondly, an algorithm of IFOPC is deduced in detail. Thirdly, some key techniques of IFOPC are discussed, which include the selection of preview step number and the determination of Kalman filter initial values. Finally, the validity of the proposed control strategy is confirmed by the simulation of manipulator shift control. The simulation results show good tracking performance of the IFOPC based nonlinear system.

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 investigated. 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.

针对复杂大系统的控制问题，提出了一种基于信息融合估计的最优分散控制方法。基于信息融合估计理论，根据控制站对大系统状态的一步预测信息与测量信息，推导出大系统状态的最优融合估计。通过融合大系统协状态信息以及控制能量的软约束信息，获得控制站输出的最优融合估计，从而利用信息融合技术求解最优分散控制问题。

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分析了基于卡尔曼滤波器的残差检验法对传感器缓变故障检测的不敏感性原因。针对双余度传感器缓变故障检测，采取了先故障判断后故障定位的故障检测策略，并提出了一种基于移动伪正常状态的残差构造方法。数学仿真验证了改进方法比传统方法更能够及时准确地识别双余度传感器缓变故障。