The carbon dioxide removal system is the most critical system for controlling CO2 mass concentration in long-term manned spacecraft.In order to ensure the controlling CO2 mass concentration in the cabin within the all...The carbon dioxide removal system is the most critical system for controlling CO2 mass concentration in long-term manned spacecraft.In order to ensure the controlling CO2 mass concentration in the cabin within the allowable range,the state of CO2 removal system needs to be estimated in real time.In this paper,the mathematical model is firstly established that describes the actual system conditions and then the Galerkin-based extended Kalman filter algorithm is proposed for the estimation of the state of CO2.This method transforms partial differential equation to ordinary differential equation by using Galerkin approaching method,and then carries out the state estimation by using extended Kalman filter.Simulation experiments were performed with the qualification of the actual manned space mission.The simulation results show that the proposed method can effectively estimate the system state while avoiding the problem of dimensional explosion,and has strong robustness regarding measurement noise.Thus,this method can establish a basis for system fault diagnosis and fault positioning.展开更多
This paper develops a large-scale small-gain result for dynamic networks composed of infinite-dimensional subsystems. It is assumed that the subsystems are input-to-output stable（IOS）and unboundedness observable（UO...This paper develops a large-scale small-gain result for dynamic networks composed of infinite-dimensional subsystems. It is assumed that the subsystems are input-to-output stable（IOS）and unboundedness observable（UO）, and the large-scale infinite-dimensional system can be proved to be IOS and UO if the proposed small-gain condition is satisfied.展开更多
基金Project(050403)supported by Pre-research Project in the Manned Space Filed of China。
文摘The carbon dioxide removal system is the most critical system for controlling CO2 mass concentration in long-term manned spacecraft.In order to ensure the controlling CO2 mass concentration in the cabin within the allowable range,the state of CO2 removal system needs to be estimated in real time.In this paper,the mathematical model is firstly established that describes the actual system conditions and then the Galerkin-based extended Kalman filter algorithm is proposed for the estimation of the state of CO2.This method transforms partial differential equation to ordinary differential equation by using Galerkin approaching method,and then carries out the state estimation by using extended Kalman filter.Simulation experiments were performed with the qualification of the actual manned space mission.The simulation results show that the proposed method can effectively estimate the system state while avoiding the problem of dimensional explosion,and has strong robustness regarding measurement noise.Thus,this method can establish a basis for system fault diagnosis and fault positioning.
基金supported by the National Science Foundation under Grant No.ECCS-1501044the National Natural Science Foundation under Grant Nos.61374042,61522305,61633007 and 61533007the State Key Laboratory of Intelligent Control and Decision of Complex Systems at BIT
文摘This paper develops a large-scale small-gain result for dynamic networks composed of infinite-dimensional subsystems. It is assumed that the subsystems are input-to-output stable（IOS）and unboundedness observable（UO）, and the large-scale infinite-dimensional system can be proved to be IOS and UO if the proposed small-gain condition is satisfied.
