Spatial PID consensus controllers for distributed filters of distributed parameter systems

This paper considers the spatial penalization of the pairwise state estimate differences as used to enforce consensus in spatially distributed filters. A spatially distributed process, described by a parabolic partial differential equation is assumed to have a network of in-domain sensors. Each spatially distributed filter corresponds to a single sensor in the network and the goal is for these filters to collaboratively reach a consensus on the process state estimate. To enhance the agreement of the spatially distributed filters, the spatial gradient of the pairwise difference of state estimates is used as a means to penalize their disagreement. Additionally, a proportional and an integral penalization of the pairwise differences are also examined in order to produce a spatial proportional–integral–derivative penalization. To address the partial connectivity, certain conditions on the communication topology are given implicitly in terms of the inner product of the state estimation errors and their pairwise differences. Simulation studies provide an insight on the effects of this spatial penalizations.