This paper is devoted to solve the problems on simultaneous actuator and sensor fault estimations as well as the nonfragile fault-tolerant control (FTC) for a kind of Markovian jump systems with faults and disturbances. First, the considered system is converted to an augmented system by putting the sensor fault into the new state. Then, an adaptive observer is designed for the descriptor system with the actuator fault adjusted by the designed adaptive law. Based on the estimated actuator faults, an output-feedback-based FTC strategy is proposed to stabilize the closed-loop system against actuator and sensor faults, and disturbances, while showing robustness for the control gain perturbations. Sufficient conditions for the existences of the observer and controller are provided in forms of linear matrix inequalities. Finally, a practical application is given to express the validation and effectiveness of the proposed method.

This correspondence paper is concerned with observer design problems for a class of unknown input switched descriptor systems under average dwell time switching signals. The switched descriptor system under consideration is first transformed into a general switched linear system, and then a switched reduced-order observer that can asymptotically estimate the system state without suffering the influence from the unknown inputs is developed. Besides, a high-order sliding mode observer is introduced to obtain the estimations of the output derivatives by using the system measured outputs. On the basis of estimations of the states and output derivatives, an unknown input reconstructing method is provided. Finally, two examples are presented to verify the effectiveness of the proposed approaches.

This paper investigates the event-triggered fixed-time multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy.

Local nonlinear fuzzy systems are useful for control solutions due to their ability to handle unmeasurable/inexact premise variables and reduce computational complexity. However, their estimation problems still require further development. This paper addresses this issue by investigating set-membership estimation for a class of discrete-time local nonlinear uncertain Takagi–Sugeno fuzzy systems with guaranteed performance. We propose a new observer architecture that solves partially decouplable unknown inputs and converts nonlinear error dynamics into a linear parameter-varying type. Using the systematic $\ell _\infty$ -technique, the design conditions in the form of linear matrix inequalities ensure stability and output performance of the state estimation. We also derive a straightforward and effective zonotopic analysis method, considering the fuzzy and local nonlinear context, for less conservative results without using any specific interval set computation. Furthermore, a fast fault detection logic is proposed as an application of the set-membership estimation. Finally, we demonstrate the feasibility and advantages of our approach through three compelling examples, showcasing its efficacy in different scenarios.