Related Experiment Video
Updated: Aug 27, 2025

Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
EMPC with adaptive APF of obstacle avoidance and trajectory tracking for autonomous electric vehicles
Hongjiu Yang1, Zhengyu Wang1, Yuanqing Xia2
1School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China.
Abstract:
In this paper, event-triggered model predictive control (EMPC) with adaptive artificial potential field (APF) is designed to realize obstacle avoidance and trajectory tracking for autonomous electric vehicles. An adaptive APF cost function is added to achieve obstacle avoidance and guarantee stability. The optimization problem for MPC is feasible by considering a special obstacle avoidance constraint. An event-triggered mechanism is proposed to reduce computational burden and ensure effectiveness of obstacle avoidance. Input and state constraints of autonomous electric vehicles are considered in both feasibility and stability by a robust terminal set. Effectiveness of both obstacle avoidance and trajectory tracking is shown by experimental results on autonomous electric vehicles.
More Related Videos
06:45Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
10:28Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research
Published on: April 21, 2023
Related Concept Videos
PD Controller: Design
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
PI Controller: Design
Time-Domain Interpretation of PD Control
Consider the example of control of motor torque. Initially, a positive...
Rolling Resistance: Problem Solving