Work

Dynamic event-triggered finite-time data-driven sliding-mode control for bridge cranes with quantized data

Year: 2025

Type: article

Abstract: This paper investigates a dynamic event-triggered finite-time data-driven sliding-mode control method for bridge cranes subjected to limited communication resources and quantized data. Firstly, we partially feedback linearize the nonlinear bridge crane system and construct a fast terminal sliding mode surface, on the basis of which we design an adaptive sliding mode controller. Then, we formulate a dynamic event-triggered strategy to alleviate the communication burden by cutting down communication frequencies. Meanwhile, a quantized-based communication scheme is further developed to reduce the communication burden, where the data bit of the communication data is dramatically shrunk. Finally, the convergence of the formulated method is strictly demonstrated, and several simulations verify the effectiveness of the formulated method.

Source: Measurement and Control

DOI: 10.1177/00202940251355054

Authors: Peng Wang, Huarong Zhao, Jie Wu, Hongnian Yu

Institutions: Jiangnan University, Edinburgh Napier University

Language: English

Topic: Dynamics and Control of Mechanical Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,000