Event-triggered Fault Detection For Discrete Markov Jump Systems

People have been paying greater attention to the safety and reliability of the controlled system in recent years,as science and technology have progressed.Fault detection technology is a method of determining whether or not a system has a fault.It is now commonly employed in a variety of technical systems.Its primary purpose is to detect faults in the system in time and give an alarm.As a result,the constant improvement of the system’s fault detection technology exploration plays an essential role in assuring the operating system’s safety and stability.In addition,the Markov jump system may be used to correctly depict a group of realistic systems with complicated internal structures and strong random parameter changes since it is a randomized hybrid system,and its application covers a wide range of engineering system fields,including network control systems,economic systems,and power systems.The singular Markov jump system can do a better job of expressing the dynamic properties of the system than the general Markov jump system,so it has gotten a lot of attention and has a lot of practical usefulness.Therefore,in this paper,a filter-based fault detection method for discrete Markov jump systems is proposed.The following is the paper’s primary research work:(1)The related challenges of fault detection for discrete Markov jump systems are investigated,taking into account the presence of stochastic loss of measurement data.To begin,the Bernoulli binary switching sequence is employed to represent a data loss situation,and both the mode-dependent and mode-independent filter conditions are taken into account at the same time.The Lyapunov function is then used to investigate the filter error system,and a suitable condition is discovered to verify that the filter error system is exponentially mean-square stable and satisfy H_?performance requirements.Then,the design approach of the filter is presented.Finally,a simulation example is used to demonstrate that the filter is to be effective.(2)Under network transmission,research is being done on the subject of fault detection for a kind of discrete Markov jump systems with an event-triggered mechanism for dynamic threshold.First,an event-triggered mechanism is adopted to dynamically alter the threshold parameters relying on the disparity in error from the most recently supplied value and the current measurement result,thereby reducing the computational load.Then,Bernoulli stochastic variables are used to describe whether the filter can successfully receive the system jump modes,and using upon this Lyapunov stability theory,a fault detection filter with partially mode-dependent is established to make the filter error system exponentially mean-square stable and satisfy H_?performance requirements.Address the problem to get the filter settings.Finally,to show the effectiveness of the method,a simulation example is offered.(3)The related difficulties of event-triggered asynchronous fault detection are investigated for singular Markov jump system.Frist,in order to account for the asynchronous phenomenon produced by an incorrect match between the system mode and the filter mode,two different Markov chains are employed to represent the system mode and the filter mode respectively,and a fault detection filter(FDF)design technique is offered on this premise.The Lyapunov stability theory is then implemented to the filter error system,and the appropriate condition is stated to assure that the filter error system is regular,causal,stochastically stable and satisfy H_?performance requirements.Following that,by inserting a slack matrix,the predicted parameters of the fault detection filter are available for further study.Finally,two simulation examples are provided to demonstrate the efficacy of the design technique.