Reliable H∞ filtering for stochastic spatial–temporal systems with sensor saturations and failures

This study is concerned with the reliable H_∞ filtering problem for a class of stochastic spatial-temporal systems with sensor saturations and failures. Different from the continuous spatial-temporal systems, the dynamic behaviour of the system under consideration evolves in a discrete rectangular region. The aim of this study is to estimate the system states through the measurements received from a set of sensors located at some specified points. In order to cater for more realistic signal transmission process, the phenomena of sensor saturations and sensor failures are taken into account. By using the vector reorganisation approach, the spatial-temporal system is first transformed into an equivalent ordinary differential dynamic system. Then, a filter is constructed and a sufficient condition is obtained under which the filtering error dynamics is asymptotically stable in probability and the H_∞ performance requirement is met. On the basis of the analysis results, the desired reliable H_∞ filter is designed. Finally, an illustrative example is given to show the effectiveness of the proposed filtering scheme.