1 问题的提出 状态空间H=l^2,控制空间U=l^2,状态X∈H,控制U∈L^1[0,T;U],A=[a_(1j)],B=[b_(ij)] 基本假设:A=(a(1j))满足 满足 sum form i=1 to ∞ sum form j=1 to ∞ α_(ij)~2<+∞,B=(b_(ij)满足sum form i=1 to ∞ sum form j=1...1 问题的提出 状态空间H=l^2,控制空间U=l^2,状态X∈H,控制U∈L^1[0,T;U],A=[a_(1j)],B=[b_(ij)] 基本假设:A=(a(1j))满足 满足 sum form i=1 to ∞ sum form j=1 to ∞ α_(ij)~2<+∞,B=(b_(ij)满足sum form i=1 to ∞ sum form j=1 to ∞b_(ij)~2<+∞。 本文的工作是在基本假设下,找有限维系统使其解逼近系统(1)的解,同时保持系统(1)的主要性质。展开更多
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
文摘1 问题的提出 状态空间H=l^2,控制空间U=l^2,状态X∈H,控制U∈L^1[0,T;U],A=[a_(1j)],B=[b_(ij)] 基本假设:A=(a(1j))满足 满足 sum form i=1 to ∞ sum form j=1 to ∞ α_(ij)~2<+∞,B=(b_(ij)满足sum form i=1 to ∞ sum form j=1 to ∞b_(ij)~2<+∞。 本文的工作是在基本假设下,找有限维系统使其解逼近系统(1)的解,同时保持系统(1)的主要性质。
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.
