In this article, a double-channel event-triggered control method is developed for nonlinear uncertain interconnected systems using backstepping techniques, which introduces event-triggering mechanisms at both the sensor and controller sides. Using event-triggering mechanism at the sensor side presents a challenge to the backstepping control design as the discontinuous state/output signals received at the controller side result in nondifferentiable virtual control signals. This challenge becomes more pronounced when considering more general types of event-triggering mechanisms. Compared with existing methods, this article proposes a different idea with three innovative features: 1) the proposed event-triggering mechanism does not require the calculation of virtual control signals at the sensor side before transmitting them to the controller side; 2) the output triggering is considered directly, and there is no need to design separate controllers for the two communication scenarios without and with event-triggering, thereby avoiding the effect of errors caused by processing substitutions; and 3) it necessitates the online update of only one parameter estimator, avoiding the issue of over-parameterization. Finally, we validate the effectiveness and advantages of the proposed decentralized event-triggered control approach through a numerical case study.
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http://dx.doi.org/10.1109/TCYB.2025.3545279 | DOI Listing |
In this article, a double-channel event-triggered control method is developed for nonlinear uncertain interconnected systems using backstepping techniques, which introduces event-triggering mechanisms at both the sensor and controller sides. Using event-triggering mechanism at the sensor side presents a challenge to the backstepping control design as the discontinuous state/output signals received at the controller side result in nondifferentiable virtual control signals. This challenge becomes more pronounced when considering more general types of event-triggering mechanisms.
View Article and Find Full Text PDFSci Rep
March 2025
College of Weaponry Engineering, Naval University of Engineering, Wuhan, China, 430033.
This article proposes a prescribed-time trajectory tracking control algorithm for unmanned surface vessels with lumped disturbances, limited communication, and error constraints, utilizing an event-triggered mechanism. Firstly, we present a prescribed-time lumped disturbances observer to accurately estimate the lumped disturbances, including external ocean disturbances, model uncertainties, and unmodeled dynamics. Then, a prescribed-time prescribed performance function is implemented to achieve guaranteed steady-state performance within a predefined time.
View Article and Find Full Text PDFISA Trans
March 2025
School of Automation Science and Electrical Engineering, Beihang University, Beijing, People's Republic of China. Electronic address:
A distributed adaptive consistency controller is designed for PDE modeling multi-flexible manipulators with both actuator delay and communication delay. The input integral is fed back into the controller to avoid the influence of the actuator delay. The adaptive law is designed to observe the ideal signal for the agent without the ideal signal information.
View Article and Find Full Text PDFThe main objective of this study is to develop an intelligent, resilient event-triggered control method for fractional-order multiagent networked systems (FOMANSs) using reinforcement learning (RL) to address challenges resulting from unknown dynamics, actuator faults, and denial-of-service (DoS) attacks. First, the challenge of unknown system dynamics within their environment must be addressed to achieve desired system stability in the face of unknown dynamics or to optimize consensus in FOMANSs. To address this problem, an adaptive learning law is implemented to handle unknown nonlinear dynamics, parameterized by a neural network, which establishes weights for a fuzzy logic system utilized in cooperative tracking protocols.
View Article and Find Full Text PDFThis article investigates the distributed tracking problem of networked cyber-physical systems (CPSs), considering system uncertainties, output constraints, and false data injection (FDI) attacks. Notably, the FDI attacks modeled here are explicitly malicious, meaning they are designed to cause the system to violate prescribed output constraints. Motivated by the lack of constrained-control studies addressing situations where the reference signal does not meet the constraint, we introduce a new form of tracking error, termed barrier tracking error (BTE).
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