无线网络环境下含乘性噪声多速率系统的状态估计和故障估计研究及应用

本项目拟针对无线网络环境下含乘性噪声多速率系统状态估计和故障估计进行研究。首先建立系统模型，解决含乘性噪声的时变观测时滞系统的最优平滑、Kalman滤波和鲁棒Kalman滤波问题；其次，基于上述算法估计系统状态和故障新息的统计数字特征，然后对系统故障进行检测，并估计故障的幅值；再次，将上述研究扩展到无线网络环境下，考虑网络数据传输过程中的量化误差、诱导时延、随机滞后和数据丢包等不确定性，重点研究无线环境下含乘性噪声的时变观测时滞多速率系统的状态估计和故障估计问题；最后将取得的相关研究成果应用于复杂环境下探测机器人网络平台，进而修正和完善所提理论和方法。.本课题的研究可以初步建立无线网络多速率系统状态估计和故障估计理论，进一步完善和发展无线网络存在乘性噪声、时变观测时滞、不确定性复杂动态时的估计理论体系，具有重要的理论研究价值，而且将对我国工业和军事领域的应用有着重要的实际指导意义。

This project aims to solve the state estimation and fault estimation problems for multi-rate systems with multiplicative noises and time-varying delay under the wireless networks environment. Firstly, the model is intended to build for solving the smoothing, filtering and robust filtering problem for the multi-rate system with multiplicative noises and time-varying delay. Secondly, the proposed optimal smoothing and Kalman filtering methods are employed to estimate the statistical characteristics of the innovation of the process states and faults, based on which the faults are detected and the amplitudes of the faults are calculated. Thirdly, the above study is expanded to the multi-rate systems under the wireless networks environment, and the uncertainties caused by the unknown quantization errors, transmission random delay and induced delay and packet dropout rates are considered. The state estimation and faults detection of the multi-rate systems with multiplicative noises and time-varying delay under the wireless networks environment are emphatically studied. Finally, the related research productions are applied to the networks platform of the mobile robots, and the verification results are used to revise and perfect the proposed theory and methods..The study of this subject can be used to build the preliminary theory of the state estimation and the faults estimation for the multi-rate system under the wireless network environment, and further to perfect and develop the system of estimation theory about the wireless network with multiplicative noise, time-varying delay and uncertainly complex dynamics. This project is greatly meaningful to the theoretical research and has guiding significance to the industrial production and military security.