Data-driven actuator fault identification and accommodation in networked control of spatially-distributed systems

This work presents a methodology for the integrated identification and accommodation of control actuator faults in spatially distributed systems controlled over a resource-limited communication network. A finite-dimensional model-based networked controller that enforces closed-loop stability using minimal sensor-controller communication is initially designed, and an explicit characterization of the networked closed-loop stability region is obtained. Fault identification is carried out using a moving-horizon least-squares parameter estimation scheme embedded in the sensors to estimate on-line the size of the fault using the sampled state and input data. Once the fault is identified and its magnitude estimated and communicated to the controller, a number of possible stability-preserving fault accommodation strategies are devised, including updating the post-fault control model, adjusting the controller design parameters, or a combination of both. The selection of the appropriate accommodation strategy is made on the basis of the estimated fault magnitude and the characterization of the networked closed-loop stability region. Finally, the proposed methodology is illustrated using a representative diffusion-reaction process example.