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This paper is concerned with the design and performance analysis of networked control systems with network-induced delay, packet disorder, and packet dropout. Based on the incremental form of the plant input–output model and an incremental error feedback control strategy, an incremental networked predictive control (INPC) scheme is proposed to actively compensate for the round-trip time delay resulting from the above communication constraints. The output tracking performance and closed-loop stability of the resulting INPC system are considered for two cases: 1) plant-model match case and 2) plant-model mismatch case. For the former case, the INPC system can achieve the same output tracking performance and closed-loop stability as those of the corresponding local control system. For the latter case, a sufficient condition for the stability of the closed-loop INPC system is derived using the switched system theory. Furthermore, for both cases, the INPC system can achieve a zero steady-state output tracking error for step commands. Finally, both numerical simulations and practical experiments on an Internet-based servo motor system illustrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper addresses the design problem of false data injection (FDI) attacks against the output tracking control of networked systems, where the network-induced delays in the feedback and forward channels are considered. The main contributions of this paper are as follows. 1) To actively compensate for the two-channel network-induced delays, a Kalman filter-based networked predictive control scheme is designed for stochastic linear discrete-time systems. 2) From an attacker’s perspective, stealthy FDI attacks are proposed for both the feedback and forward channels so as to disrupt the stability of the resulting closed-loop system while avoiding the detection of a Kalman filter-based attack detector. 3) Both numerical simulations and practical experiments are carried out to show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper addresses the data-based networked control problem for a class of nonlinear systems. Network communication constraints, such as network-induced delay, packet disorder, and packet dropout in both the feedback and forward channels, are considered and further treated as the round-trip time (RTT) delay that is redefined. By using the packet-based transmission mechanism and the model-free adaptive control algorithm, a data-based networked predictive control method is proposed to actively compensate for the random RTT delay. The proposed method does not require any information on the plant model and depends only on the input and output data of the plant. A simple and explicit sufficient condition, which is related to the upper bound of the RTT delays, is derived for the stability of the closed-loop system. Additionally, a zero steady-state output tracking error can be achieved for a step reference input. The effectiveness of the proposed method is demonstrated via simulation and experimental results. [ABSTRACT FROM PUBLISHER]

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]

This paper studies the problem of output tracking for networked control systems with network-induced delay, packet disorder, and packet dropout. The round-trip time (RTT) delay is redefined to describe these communication constraints in a unified way. By including the output tracking error as an additional state, the output tracking problem is converted into the stabilization problem of an augmented system. Based on the observer of the original state increment and the feedback of the output tracking error, a model-based networked predictive output tracking control (NPOTC) scheme is proposed to actively compensate for the random RTT delay. The closed-loop stability is proved to be independent of the RTT delay, and the separation principle for the design of the observer-based state feedback controller is still held in the NPOTC system. A two-stage controller design procedure is presented, which not only guarantees the stability of the closed-loop NPOTC system but also achieves the same output tracking performance as that of the local control system for time-varying reference signals. Both numerical simulations and practical experiments on an Internet-based servo motor system illustrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]