基于观测器的离散马氏跳变系统的故障估计

Observer-based fault estimation for discrete-time Markovian jump systems

基于观测器的离散马氏跳变系统(D-MJSs)是随机的,但系统待估计的故障是确定性信号,因此很难直接研究该系统的故障估计问题.针对该问题,本文提出一种构造辅助系统方法,通过对随机变量取期望来构造确定性的中间变量,进而建立的中间估计器可以同时估计系统状态和故障.此外,基于一种新的放缩手段,进一步考虑转移概率矩阵(TPM)不确定的情况.所有条件均以线性矩阵不等式(LMIs)给出,并保证状态误差是输入状态稳定的.数值仿真算例验证了所提方法的有效性和优越性.

Observer-based discrete Markov jump systems(D-MJSs)are random,but their faults to be estimated are deterministic signals,so it is difficult to directly study the fault estimation of the system.Here,an approach of constructing auxiliary systems is proposed,which constructs deterministic intermediate variables by taking expectations of random variables,and then the established intermediate estimator can estimate the system state and faults at the same time.In addition,based on a new scaling method,the uncertainty of the Transition Probability Matrix(TPM)is considered.All conditions are given by Linear Matrix Inequalities(LMIs),and the state error is ensured by stable input state.Numerical simulation examples are provided to prove the effectiveness and superiority of the proposed approach.