Observer-Based Robust Fault Predictive Control for Wind Turbine Time-Delay Systems with Sensor and Actuator Faults

• Published in: Energies (Basel) Vol. 16; no. 2; p. 858
• Main Authors: Bououden, Sofiane, Allouani, Fouad, Abboudi, Abdelaziz, Chadli, Mohammed, Boulkaibet, Ilyes, Barakeh, Zaher Al, Neji, Bilel, Ghandour, Raymond
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-01-2023; MDPI
• Subjects: Actuators; Algorithms; Automatic; Controllers; Design; Disturbances; Engineering Sciences; Fault tolerance; fault-tolerant control; Faults; Linear matrix inequalities; linear matrix inequalities (LMIs); observer-based control; Optimization; Prediction models; Rejection; Robust control; robust model predictive control; sensor and actuator faults; Sensors; State space models; Time delay systems; Turbines; Wind power; wind turbine model; wind turbine model; Linear matrix inequalities (LMIs); Robust model predictive control; Fault-tolerant control; Sensor and actuator faults; Observer-based control
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16020858

This paper presents a novel observer-based robust fault predictive control (OBRFPC) approach for a wind turbine time-delay system subject to constraints, actuator/sensor faults, and external disturbances. The proposed approach is based on an augmented state-space representation that contains state-space variables and estimation errors. The proposed augmented representation is then used to synthesize a robust predictive controller. In addition, an observer is developed and used to estimate both state variables and actuator/sensor faults. To ensure that the proposed approach has disturbance rejection capabilities, the disturbance estimates were merged with the prediction model. In addition, the disturbance rejection capabilities and fault tolerance were insured by formulating the control process as an optimization problem subject to constraints in terms of linear matrix inequalities (LMIs). As a result, the controller gains are acquired by solving an LMI problem to guarantee input-to-state stability in the presence of sensor and actuator faults. A simulation example is conducted on a nonlinear wind turbine (1 MW) model with 3 blades, a horizontal axis, and upwind variable speed subject to actuator/sensor faults in the pitch system. The results demonstrate the ability of the proposed method in dealing with nonlinear systems subject to external disturbances and keeping the control performance acceptable in the presence of actuator/sensor faults.