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hybrid modeling and predictive control of intelligent vehicle longitudinal velocity considering nonlinear tire dynamics  (Nonlinear Dynamics)

 
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    Nonlinear Dynamics hybrid modeling and predictive control of intelligent vehicle longitudinal velocity considering nonlinear tire dynamics
    Hybrid Modeling And Predictive Control Of Intelligent Vehicle Longitudinal Velocity Considering Nonlinear Tire Dynamics, supplied by Nonlinear Dynamics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/vehicle+nonlinear+dynamics+model/hybrid+modeling+and+predictive+control+of+intelligent+vehicle+longitudinal+velocity+considering+nonlinear+tire+dynamics/10__1007_slash_s12555___024___0295___4-200-11-27
    Average 90 stars, based on 1 article reviews
    hybrid modeling and predictive control of intelligent vehicle longitudinal velocity considering nonlinear tire dynamics - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Research on intelligent vehicle lane changing and obstacle avoidance control based on road adhesion coefficient
    Article Snippet: Aimed at the safety and stability problems of intelligent vehicles under extreme conditions such as low adhesion road surface and emergency lane change and obstacle avoidance, this article designs a lane change and obstacle avoidance controller based on road adhesion coefficient.. Using the nonlinear vehicle dynamics model as the prediction model, using the recursive least squares method to identify the road adhesion coefficient, considering the road adhesion coefficient to plan and adjust in the obstacle avoidance path as well as limit constraint conditions of the model predictive control controller, using model predictive control method for the expectation of intelligent vehicle trajectory tracking, travels tremendously guarantee the security and stability of driving.. The joint CarSim–Simulink simulations results show that under poor road conditions, the trajectory tracking accuracy after optimization is higher and the vehicle is less prone to sideslip and instability.

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    Article Snippet: The stability analysis model differs from vehicle nonlinear dynamics model owing to linearisation.



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