Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

This paper proposes a dynamic event triggering mechanism whose triggering characteristics can be designed for a robust sliding mode controller to solve the lateral motion control problem of intelligent electric vehicle in the presence of bounded matched disturbances. The motivation of current work mainly aims to alleviate unnecessary computing and communication of energy-constrained vehicle control systems by a large margin while ensuring its stability and robustness. The main contributions of the paper are summarized as follows. We design a continuous-time robust sliding mode controller which is proved to have the capability to effectively suppress the bounded matched disturbances. We derive a new dynamic event triggering rule, under which the positive minimum value and the evolution characteristics of the inter-event times are able to be designed. We analyze the stability via the Lyapunov theory, exclude Zeno behavior and prove that the semi-global robust event-separation property holds for the above constructed event-triggered control system theoretically. We numerically evaluate the effectiveness of our theoretical results and the advantages of the proposed method which is highlighted in an overtaking case for the intelligent electric vehicle. To the best of our knowledge, this is the first paper which studies lateral motion control of vehicle with the consideration of the robustness not only for the stability but also for the positive minimum inter-event times.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229547PMC
http://dx.doi.org/10.1038/s41598-025-09816-zDOI Listing

Publication Analysis

Top Keywords

sliding mode
12
intelligent electric
12
electric vehicle
12
dynamic event
8
event triggering
8
robust sliding
8
mode controller
8
lateral motion
8
motion control
8
bounded matched
8

Similar Publications

The evaporation of surfactant-laden sessile droplets has widespread applications in both natural and technological contexts. This study explores the evaporation of droplets containing a nonionic surfactant (tristyrylphenol ethoxylates (EOT)), an anionic surfactant (sodium benzenesulfonate with alkyl chain lengths of C-C (NaDDBS)), and their mixtures at / mole ratios of 0.01, 0.

View Article and Find Full Text PDF

This study investigates the phenomenon of mode repulsion in Lamb waves propagating through two coupled plates with an elastic interface. Using a spring-based coupling model and the Scaled Boundary Finite Element Method, the dispersion curves of the coupled system are analyzed under various interface conditions-weak coupling, sliding boundary, and perfect coupling. This research highlights how the mechanical stiffness of the interface influences the separation of modes and the emergence of repulsion regions.

View Article and Find Full Text PDF

Deep learning (DL) has significantly improved the diagnostic accuracy and efficiency of cytopathologists. However, current DL-assisted reading modes have yet to be fully evaluated, and there is limited evidence regarding cytopathologists' preferences and experiences. This study employs a randomized, controlled, four-way crossover design to assess the effectiveness of four different reading modes in cervical cytopathology readings.

View Article and Find Full Text PDF

In this study, the problem of trajectory tracking optimal control of robotic manipulator system subjected to external load disturbances is investigated, and an observer-based discrete fast terminal sliding mode predictive optimal control (FTSMPC) strategy is presented. Firstly, to address the unknown friction torque and load disturbances, a novel discrete-time extended state observer is designed to estimate the lumped disturbances, in which the boundedness of the observation error can be guaranteed through theoretical analysis. Then, with the outputs of the observer, an FTSMPC control approach is designed.

View Article and Find Full Text PDF

This study proposes an improved fast non-singular adaptive super-twisting control scheme based on neural network to address the precise control issues of robot joint modules. Firstly, to facilitate the application of advanced control algorithms, a second-order state-space model of the joint module considering nonlinear friction and stiffness is established using the Lagrangian energy equation method. Then, an improved fast non-singular terminal sliding surface is proposed to avoid singularity and accelerate convergence.

View Article and Find Full Text PDF