Adaptive Sliding Mode Control for Autonomous Vehicle Platoon under Unknown Friction Forces

Yadav, Rishabh; Sankaranarayanan, Viswa Narayanan; Roy, S.

doi:10.1109/icar53236.2021.9659441

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…For example, Shukla et al [28] designed a robust adaptive controller for the steer-by-wire system. Yadav et al [29] studied an adaptive sliding mode controller for autonomous vehicle platoon, with their simulation and experimental studies showing that a realistic scenario representing repeated narrow and wide paths for robots leads to significant performance loss for non-switched controllers. Rayguru et al [30] studied an extended high-gain observer.…”

Section: Closed-loop Control Strategymentioning

confidence: 99%

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Wei

2023

Energies

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The paper presents a DSP-based design and control of a three-axis servo motion system that effectively divides control tasks between the master control terminal and four slave drives. The proposed architecture enhances the immediacy of platform positioning and the integration between software and hardware. The paper utilizes a high-accuracy encoder as a reference value for accuracy improvement and integrates firmware via the proposed embedded execution program, thereby reducing the accuracy error of the low-accuracy encoder. The main control core employs a digital signal processor (DSP) for input and output signal reading and writing, digital communication interface processing, and user interface. The slave controller utilizes four digital signal processors to accomplish servo position control in a digital way. The paper employs encoder calibration technology to upgrade the positioning accuracy of the surge axis. Finally, the paper validates the correctness and feasibility of the proposed method through experimental results from a set of adjustable experimental platforms of linear motion stroke and rotary motion stroke. In summary, the paper underscores the integration of hardware and software to attain high-precision and dependable control of the motion system.

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Section: Closed-loop Control Strategymentioning

confidence: 99%

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Wei

2023

Energies

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“…MPC requires the discretization and linearization of system dynamics, which leads to a range of modeling errors. Therefore, [21] designed an adaptive sliding mode controller for use in vehicle formations based on nonholonomic wheeled mobile robots. This controller has the advantage of dealing with the unknown complex behavior of friction, the uncertainty of parameters, and external interference without prior knowledge of parameters and structures.…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Vehicle Trajectory Tracking Control Based on Improved Adaptive MPC

Tan,

Wang,

2024

Sensors

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Intelligent vehicle trajectory tracking exhibits problems such as low adaptability, low tracking accuracy, and poor robustness in complex driving environments with uncertain road conditions. Therefore, an improved method of adaptive model predictive control (AMPC) for trajectory tracking was designed in this study to increase the corresponding tracking accuracy and driving stability of intelligent vehicles under uncertain and complex working conditions. First, based on the unscented Kalman filter, longitudinal speed, yaw speed, and lateral acceleration were considered as the observed variables of the measurement equation to estimate the lateral force of the front and rear tires accurately in real time. Subsequently, an adaptive correction estimation strategy for tire cornering stiffness was designed, an AMPC method was established, and a dynamic prediction time-domain adaptive model was constructed for optimization according to vehicle speed and road adhesion conditions. The improved AMPC method for trajectory tracking was then realized. Finally, the control effectiveness and trajectory tracking accuracy of the proposed AMPC technique were verified via co-simulation using CarSim and MATLAB/Simulink. From the results, a low lateral position error and heading angle error in trajectory tracking were obtained under different vehicle driving conditions and road adhesion conditions, producing high trajectory-tracking control accuracy. Thus, this work provides an important reference for improving the adaptability, robustness, and optimization of intelligent vehicle tracking control systems.

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Introducing Switched Adaptive Control for Self-Reconfigurable Mobile Cleaning Robots

Rayguru

Roy

et al. 2024

IEEE Trans. Automat. Sci. Eng.

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Adaptive Sliding Mode Control for Autonomous Vehicle Platoon under Unknown Friction Forces

Cited by 3 publications

References 27 publications

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Research on Intelligent Vehicle Trajectory Tracking Control Based on Improved Adaptive MPC

Introducing Switched Adaptive Control for Self-Reconfigurable Mobile Cleaning Robots

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