Control of Autonomous Vehicle for Lateral Dynamics using Sliding Mode and Input-to State Stability Methods

Parkash, Aman; Swarup, Akhilesh

doi:10.1109/ic-etite47903.2020.291

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The main purpose of using a look-ahead-based approach sensing system is to enhance the damping effect as given in the paper (Son et al, 2014). Based on the lateral offset error at a look-ahead distance, the following control schemes have been studied: an adaptive controller, that is, self-tuning regulator-based lateral control (Netto et al, 2004), nested PID control (Marino et al, 2011), expert fuzzy controller (Yang and Zheng, 2007), a robust controller, that is, lane-keeping using H∞ control method (Roselli et al, 2017), sliding mode and ISS property-based lane-keeping method (Parkash, and Swarup, 2020), and the backstepping and forwarding design control-based method (Jiang and Astolfi, 2018).…”

Section: Introductionmentioning

confidence: 99%

Application of asymmetric barrier Lyapunov function using ADRC approach for development of autonomous vehicle lateral control

Parkash

Swarup

2022

Journal of Vibration and Control

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This paper presents a control scheme for performance improvement in lane-keeping activity of autonomous vehicle, within guaranteed specified deviations. Such feature will provide better and safe maneuvering for autonomous vehicle. The proposed control scheme consists of Asymmetric Barrier Lyapunov Function (ABLF) based backstepping method for ensuring stability and constraints satisfaction. Since autonomous vehicle dynamics is subjected to unknown disturbances and also the states, it has been shown that the vehicle performance can be improved by the application of Active Disturbance Rejection Control (ADRC) which uses the Extended State Observer (ESO). For the proposed control scheme, the asymptotic stability and convergence of error dynamics have been established. The simulation results have been presented to illustrate the performance robustness and accuracy provided by the proposed control scheme. Further, it has been show that the vehicle motion performance is better in comparison to the performances obtained from two existing control methods.

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Section: Introductionmentioning

confidence: 99%

Application of asymmetric barrier Lyapunov function using ADRC approach for development of autonomous vehicle lateral control

Parkash

Swarup

2022

Journal of Vibration and Control

Self Cite

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“…Through an adaptive learning mechanism, LKAS adjusts itself, taking into account the driver's style and avoiding potential conflicts between steering actuation and driver intervention. LKAS proves particularly useful in long trips or heavy traffic conditions [9].…”

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confidence: 99%

A Comprehensive Analysis of Model Predictive Control for Lane Keeping Assist System

Montoya,

Teixeira,

Murilo

et al. 2023

IEEE Access

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Lane Keeping Assist System (LKAS) enhances comfort and safety while driving. It plays a significant role in the Advanced Driver Assistance System (ADAS) and future Automated Driving (AD). The LKAS solution aims to help the driver keep the vehicle within the road lines, preventing unintentional lane departure. Despite LKAS being an important solution for comfortable driving, robust LKAS steering control is still lacking, requiring constant driver intervention or premature LKAS deactivation. LKAS require optimal control solutions with real-time constraints. This paper comprehensively analyzes Model Predictive Control (MPC) for real-time LKAS applications. Classical and parameterized MPC schemes with distinct Quadratic Programming (QP) solvers are combined to evaluate LKAS closed-loop control performance and realtime constraints. A sideslip and lateral speed bicycle modes were used to evaluate classical, trivial, and exponential MPC schemes. Experimental results highlight the three MPC and QP-appropriate solutions with satisfactory reference tracking without steering command and real-time constraints violation. INDEX TERMS Advanced Driver Assistance Systems, Lane Keeping Assist System, Model Predictive Control, MPC parameterization, Quadratic Programming. I. INTRODUCTIONV EHICLE safety encompasses regulations, actions, and technological solutions designed to prevent traffic accidents [1]. Today, there is a global effort involving multiple sectors, including transport, health, education, etc., to address safety on roads [2]. Carmakers and governments worldwide are actively seeking innovative solutions to enhance the safety of all road users. Active safety systems such as Antilock Braking Systems (ABS), Electronic Stability Control (ESC), Autonomous Emergency Braking (AEBS), and Lane Assist Systems (LAS) are employed to prevent accidents from occurring altogether, sometimes actively assisting the driver in mitigating the impact. These Advanced Driver Assistance Systems (ADAS) are often implemented to be forgiving of human error.

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Non-linear MPC for Longitudinal and Lateral Control of Vehicle’s Platoon with Insert and Exit Manoeuvres

Graffione

Bersani

Sacile

et al. 2022

Informatics in Control, Automation and Robotics

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Control of Autonomous Vehicle for Lateral Dynamics using Sliding Mode and Input-to State Stability Methods

Cited by 3 publications

References 14 publications

Application of asymmetric barrier Lyapunov function using ADRC approach for development of autonomous vehicle lateral control

Application of asymmetric barrier Lyapunov function using ADRC approach for development of autonomous vehicle lateral control

A Comprehensive Analysis of Model Predictive Control for Lane Keeping Assist System

Non-linear MPC for Longitudinal and Lateral Control of Vehicle’s Platoon with Insert and Exit Manoeuvres

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