Integration of controls and diagnostics using neural networks

Controllers capable of performing failure diagnosis have additional diagnostic outputs to detect and isolate sensor and actuator faults. A linear such controller is usually called a four-parameter controller. In this paper; a neural network model of a controller with diagnostic capabilities (CDC) is presented for the first time. This nonlinear neural controller is trained to operate as a traditional controller, while at the same time it provides reproduction of the failure occurring, either at the actuator or the sensor. The cases of actuator and sensor failures are studied independently. Several simulation results concerning a nonlinear plant are provided.