Bumpless Transfer Fault-Tolerant Control for Continuous-Time Switched Systems via Learning-Based Fault Reconstruction

This article focuses on the fault reconstruction and bumpless transfer fault-tolerant (FT) control problems for switched linear systems with magnitude-bounded disturbances and actuator faults in continuous-time domain. A new learning-based robust unknown input observer (UIO), not requiring fault differentiability and completely decoupled disturbances, is developed to accomplish fault reconstruction and state estimation. The fault reconstruction value is updated by one iteration learning on the timeline, i.e., the fault at the current moment is reconstructed by learning historical information from the previous moment. Based on the obtained estimation information, an efficient bumpless transfer FT controller is designed to counteract the fault effects and suppress the control bumps. The bumpless transfer constraint is guaranteed via a new inequality transformation method, which improves the anti-disturbance capability of the controller and also decreases the switching bumps. The solvability conditions for the bumpless transfer controller and learning-based UIO are developed under the condition of average dwell time switching. Finally, an application of the inverted pendulum controlled by a direct current motor is presented to reveal the effectiveness and applicability of the developed methods.