Reconfigurable control of piecewise affine systems with actuator and sensor faults: Stability and tracking

• Published in: Automatica (Oxford) Vol. 47; no. 4; pp. 678 - 691
• Main Authors: Richter, J.H., Heemels, W.P.M.H., van de Wouw, N., Lunze, J.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.04.2011; Elsevier
• Subjects: Actuator faults; Actuators; Adaptative systems; Applied sciences; Computer science; control theory; systems; Control reconfigurability; Control system analysis; Control systems; Control theory. Systems; Exact sciences and technology; Fault-tolerant control; Faults; Input-to-state stability; Modelling and identification; Multivariable control systems; Piecewise affine systems; Reconfiguration; Sensor faults; Sensors; Stability; Tanks; Tracking; Multivariable control systems; Piecewise affine systems; Tracking; Fault-tolerant control; Input-to-state stability; Control reconfigurability; Actuator faults; Sensor faults; Sensor fusion; Continuous time; Modeling; Fault tolerance; Uncertain system; Continuous control; Linear matrix inequality; Reconfigurable architectures; Measurement error; Fault tolerant system; Actuator; MIMO system; Systeme affine in control; Multivariable control; Interconnected power system; Closed feedback; Input to state stability; Data fusion; Fault diagnostic; Multivariable system; Piecewise linearization; Reconfiguration
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2011.01.048

A reconfigurable control approach for continuous-time piecewise affine (PWA) systems subject to actuator and sensor faults is presented. The approach extends the concept of virtual actuators and virtual sensors from linear to PWA systems on the basis of the fault-hiding principle that provides the underlying conceptual idea: the fault is hidden from the nominal controller and the fault effects are compensated. Sufficient linear matrix inequality (LMI) conditions for the existence of virtual actuators and virtual sensors are given that guarantee the recovery of closed-loop stability and the tracking of constant reference inputs. Since LMIs are efficiently solvable, this solution leads to a tractable computational algorithm that solves the reconfiguration problem. The approach is proven to be robust against model uncertainties and inaccurate fault diagnosis, and is evaluated using an example system of interconnected tanks.