LAUSR

Active fault-tolerant control strategy aimed at tracking is studied for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems in the presence of input constraint and additive fault. In the fault-free case, the state space of the system is partitioned based on the presence or absence of inputs. Using the parallel distributed compensation technique, input-to-state stability is proved for the error dynamics. For input constraint satisfaction, a model predictive control based reference-management unit is proposed in the form of an online optimization module that solves a quadratic programming problem. In the faulty case, the fault-free system is used as a reference model that satisfies the input constraint. Then, the concept of virtual actuator is used to make the behavior of the faulty system similar to the behavior of the fault-free system by controlling the performance degradation. In this article, a full-order observer can be used for fault estimation. In order to keep the control input of the faulty system within the admissible range defined for the fault-free system, a constraint-change scenario is considered. After detecting the fault, the constraint on the input of the fault-free system is changed in a way to keep the control input of the faulty system in the specified range. All design criteria are formulated as a linear matrix inequality problem. In order to evaluate the proposed control approach, simulations are performed on two systems: a 3-DoF helicopter and a 2-D overhead crane.