Infinite Horizon Input Signal for Active Fault Detection in Controlled Markov Chains

Ivo Punčochář and Miroslav Šimandl


Active fault detection, Controlled Markov chains, Input signal design


The paper deals with the problem of active fault detection with a given fault detector over an infinite time horizon. Systems that can be modeled using two interconnected discrete-time finite-state Markov chains are considered. The first Markov chain is unobservable and describes switching between fault-free and faulty modes. The second one is an observable controlled Markov chain that describes the system dynamics in fault-free and faulty modes. The maximum a posteriori probability fault detector is assumed, and an input signal generator that improves the decision quality is designed. The original problem is reformulated as a perfect state information problem and solved by dynamic programming. An infinite time horizon is considered to reduce off-line computational demands and a perceptron neural network is employed to lower memory requirements for on-line use. The results are illustrated in a numerical example.

Important Links:

Go Back