Distributed state estimation and model predictive control: Application to fault tolerant control

Abstract

In this paper, a distributed and networked control system architecture based on unsupervised and independent Model Predictive Control/Kalman-Filter (MPC/KF) schemes, is proposed. Interconnected subsystems, possibly located at different sites, exchange information via the communication network. For the partial local state measurement, the key component for realistic Distributed Model Control (DMPC) formulation is the state estimations. These state estimations are provided by Kalman filters. In this distributed framework, MPC and KF algorithms may require information from other sub-controllers to achieve their task in a cooperative way. The given distributed and cooperative control system architecture may be suitable for Fault Tolerant Control (FTC) in a network of distributed subsystems. This insight gained the design of such architecture is used to implement FTC under actuator faults.