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In this article, a novel active fault‐tolerant control (AFTC) design method is developed by using the switching linear parameter varying (LPV) controller with inexact fault‐effect parameters. The LPV controller is not only considered as a gain‐scheduled controller varying with the operating points, but also an AFTC controller varying with the fault‐effect parameters, which can be obtained via the fault estimator in real‐time. The inexact measurement of fault‐effect parameters is considered for the first time in this article. To cover large parameters variation, a class of switched LPV fault‐tolerant controller is designed to work in the multiple partitioned parameters subregions. The dynamic output feedback controller model is constructed to perform the switched LPV fault‐tolerant control task under the mode‐dependent average dwell time constraint. By using the multiple parameter‐dependent Lyapunov function approach, sufficient conditions with less conservatism are obtained, such that the corresponding closed‐loop systems are globally uniformly exponentially stable and satisfy an upper bound of weighted l2‐gain performance indexes. Finally, effectiveness and applicability of the developed approaches are validated via an active magnetic bearing system. [ABSTRACT FROM AUTHOR]

This study deals with a fundamental issue of evaluating the performance of widely used fault detection and diagnosis (FDD) schemes within a closed‐loop framework. The focus is to examine how certain implemented controller would impact on the FDD performance and how such performance can be further improved. For this purpose, the authors consider the FDD problem for a class of linear discrete‐time systems (with and without unknown disturbances) under typical proportional–integral control using observer‐based methods. It is revealed that some existing observer‐based FDD approaches are no longer applicable in the closed‐loop situation due to the feedback control. To solve the problem, by appropriately modifying the structure and re‐designing the parameters of the observers, it is proven that the dynamics of closed‐loop residuals can be made identical with those of the residuals obtained with known control inputs at each time step. A numerical example is provided to show the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This study is concerned with the data‐based control of networked non‐linear control systems with random packet dropouts in both the sensor‐to‐controller and controller‐to‐actuator channels. By taking advantage of the characteristics of networked control systems such as the packet‐based transmission, timestamp technique, as well as smart sensor and actuator, a data‐based networked predictive control (DBNPC) method is proposed to actively compensate for the two‐channel packet dropouts, where only the input and output data of the non‐linear plant are required. A sufficient condition for the stability of the closed‐loop system is developed. Furthermore, the resulting DBNPC system can achieve a zero steady‐state output tracking error for step commands. Finally, extensive simulation results on a networked non‐linear system demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study studies the problem of setpoint output tracking for networked control systems with network‐induced delay, packet disorder and packet dropout. Based on the input–output difference equation model, a novel networked predictive control (NPC) method via static output feedback integral controller (SOFIC) is proposed to actively compensate for the round‐trip time (RTT) delay resulting from the aforementioned communication constraints. It is analysed that the resulting NPC system can achieve a similar tracking performance as that of the corresponding local control system. Based on the performance analysis, a necessary and sufficient condition for the stability of the closed‐loop NPC system is obtained, which is independent of the RTT delay. Both numerical simulations and practical experiments on an internet‐based servo motor system illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]