Research On State Estimation For Networked Quantized Systems

With the rapid development and popularization of Internet and information technology,networked systems have attracted great attention in the past two decades.Compared with traditional point-to-point communication,wireless networks have the advantages of low cost,simple maintenance,and easy expansion.Therefore,they are widely used for information exchange between nodes such as sensors,controllers,and actuators,which allow one to estimate the state of remote distributed networked systems.Due to the limited bandwidth of the shared network,however,the signal must be quantified before transmission to avoid network congestion.Moreover,the unique transmission structure of networked systems also has some shortcoming,such as noise interference,communication constraints,and data loss,which makes the traditional state estimation not applicable to networked systems.In conclusion,it is of profound significance to study the new method of state estimation in the networked quantized systems.This paper aims at theoretical research and algorithm design of state estimation for networked systems with colored noises,communication constraints,and quantized measurements.In order to improve the estimation performance and reduce the conservativeness of the algorithm,the estimation strategy of the network quantization system is designed according to the network transmission characteristics and the structure of the quantizer.The specific research works are as follows: 1.For the networked systems with colored noise and communication constraints,the problems of state estimation under colored noise,quantized error and limited access of nodes are studied.An information scheduling model with colored noise interference and communication constraints is constructed by using the measurement difference method and the Bernoulli stochastic model.Based on norm bounded uncertainty,a robust recursive estimator is designed and the upper bound of the estimation error covariance is obtained.Finally,two simulations are given: one example shows that the proposed robust recursive estimator can better overcome the above problems and achieve accurate state estimation;the other shows the effects of colored noise,quantization density and node access probability on the performance of the robust recursive estimator.2.For the multi-output networked system with bandwidth limitation,the problem of moving horizon state estimation is studied.A new iterative state reset algorithm is designed to overcome under-estimation or over-estimation of the estimator including its initial state.The upper bound of the mean square error of the state reset estimator is obtained based on the norm inequality,and it is proved that the designed state reset estimator has less conservativeness under static conditions.Finally,two simulation examples are given: one example shows that the proposed state reset algorithm can effectively reduce the mean square error of the estimated state in the multi-output system;the other shows that the proposed state reset algorithm is more general than the existing reset algorithm.