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In this paper, the issue of designing a dynamic event trigger mechanism for an estimator-based networked controller is discussed. Instead of separating the uncertainty estimation module and the control algorithm into two layers as most of the existing works do, the approach proposed in this paper can trigger the estimator and the controller simultaneously. Moreover, this paper is the first to consider nonlinear and state-correlated control gain matrix for both event-triggered observer design and event-triggered controller design. A new dynamically triggered extended state observer is first constructed for uncertain first-order systems with nonlinear and state-correlated control gain matrices. To avoid potential state oscillation, a new uncertainty estimator is then developed on the basis of the proposed observer. To ensure stability of the uncertainty estimator and the estimator-based controller simultaneously, a new dynamical event trigger mechanism that is free of Zeno behaviour is developed. Hardware-in-the-loop experiments based on an omnidirectional robot are also carried out to illustrate the potential of the new techniques in practice. Note to Practitioners—This article discusses the event-based control design of networked systems that can be implemented in areas such as intelligent transportation and robot-based rescue. We addressed two important practical issues in specific. The first one is how to perform adaptive event-based uncertainty estimation for nonlinear first-order systems. While the second question is how to develop a unified dynamic trigger scheme that determines if a new event has arrived based on both the uncertainty estimation error and the tracking error to maintain system stability. The proposed scheme can be attached to the sensor module to reduce the frequency of communication from the sensor to the controller. Based on the results of hardware-in-the-loop experiments, when the time-triggered step size is 8 ms and the desired speed of the rover does not exceed 0.144 m/s, the proposed scheme can reduce around 90% of wireless data transmission without compromising much tracking precision. Meanwhile, a thorough analysis regarding what affects the ratio of the overall saved resources in practice is provided based on the results of comparative experiments.

This article presents a novel model predictive control (MPC) framework with an integrated disturbance observer for cyber-physical systems (CPSs) under denial-of-service (DoS) attacks. Uniquely incorporating a memory module, our MPC approach is tailored to maintain stability and security in CPS during DoS attacks, which typically disrupt communication and degrade performance. Our method stands out by addressing time-varying system uncertainties through the disturbance observer, enhancing robustness under these attack conditions. The effectiveness of our approach is validated through numerical simulations, hardware-in-the-loop experiments, and comparative analyses using an omnidirectional robot, highlighting its practical applicability and advancement over existing methods.