Actuator and Sensor Fault Estimation for Time-Delay Markov Jump Systems With Application to Wheeled Mobile Manipulators

In this paper, fault and state estimation issue for wheeled mobile manipulators with time delay, using a novel sliding mode observer (SMO) approach has been discussed. It is well-known that the traditional SMO method, i.e., the equivalent output error injection technique cannot be simply employed to Markov jump systems (MJSs) to estimate actuator faults. In this paper, we propose a novel SMO to reconstruct the actuator and sensor faults for MJSs with time delay. First, we decouple the actuator faults from the first subsystem by utilizing coordinate transformation technique. Then, construct an augmented plant for the new system and propose a novel reduced-order SMO. By the proposed novel SMO, the state and fault can be reconstructed simultaneously. Finally, an illustrative wheeled mobile manipulator example is given to show the effectiveness of the proposed approach.