Model-free Approach for Control, Fault Diagnosis, and Fault-tolerant Control

Download or read book Model-free Approach for Control, Fault Diagnosis, and Fault-tolerant Control written by Younes Al Younes and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objectives of this thesis consist of developing Control, Fault Detection and Diagnosis (FDD) and Fault-Tolerant Control (FTC) techniques based on a the Model-Free (MF) concept recently introduced in the literature. The proposed approaches are implemented, tested and validated on a quadrotor platform. The first step of this work consisted of the modelling of the quadrotor, and then analyzing, designing and implementing new robust control strategies based on the Model-Free Control (MFC) technique recently developed in the literature. The MFC algorithm helps compensating for disturbances and model uncertainties. The advantage of this recent concept is in the simplicity of the design of the controller by adding a control law using ultra-local models to the classical control techniques. To test and validate this new approach, the Linear-Quadratic-Regulator (LQR) and the Nonlinear-Integral-Backstepping (NIB) controllers have been considered by integrating the MFC concept to design a (LQR-MFC) and a (NIB-MFC), respectively. Both algorithms are validated through analytical and experimental procedures and the robustness checked and compared with respect to the initial controllers in the presence of disturbances and model uncertainties.The FDD is a very important step towards the development of FTC techniques. The FDD approach developed in this thesis is based on the residual generation between the measured outputs and the estimated outputs obtained using observers/estimators. Residuals are expected to be close to zero in the fault free case and deviate from zero in the presence of a fault or failure. However, as the residuals are generated using models, they highly depend on the quality of the model used and on the presence of disturbances which may lead to false alarms or to non-detections. A novel “intelligent estimator” inspired from the MF concept has been developed and used in order to improve the residual generation and the fault diagnostic. Two intelligent estimators have been designed by integrating the MF scheme with the state and Thau observers for Multi-Input-Multi-Output (MIMO) systems, where the intelligent Output-Estimator (iOE) represents the integration between the MF technique with the state observer, and the intelligent Thau Output-Estimator (iTOE) represents the augmentation of the MF technique with the Thau Observer. The estimation of the system outputs obtained using the iOE are then used to estimate the actuator and sensor faults. The estimation of the actuator faults is improved by using the ultra-local models. A structured algorithm is then developed and implemented in order to estimate sensor fault magnitudes using the residuals generated by the intelligent estimator. The results obtained from the fault detection and estimation are then used to compensate for the fault effect on the flight control performance. The implemented fault-tolerant control technique compensates for the actuator faults by adjusting the control law based on the fault estimation. In case a sensor fault is detected and estimated, the desired path is regenerated according to the estimated fault magnitude in order to compensate for the fault effect.The proposed algorithms are implemented and tested on the Qball-X4 quadrotor. The results of the real-time flight tests validate the proposed techniques and compensate for sensor and actuator faults. Footages of the flight tests are available online.