학술논문

A nonlinear model predictive controller for autonomous driving
Document Type
Conference
Source
2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE) Innovative Trends in Communication and Computer Engineering (ITCE), 2020 International Conference on. :151-157 Feb, 2020
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Target tracking
Costs
Process control
Bicycles
Predictive models
Market research
Linear programming
Autonomous vehicle
Model predictive control
Nonlinear systems
Multiple shooting
Path tracking
Language
Abstract
Self driving cars have been the focus of several research groups due to the improvement in processing capabilities, and the feasibility to run sophisticated control algorithms in real time. We introduce two NMPC implementations able to guide the vehicle autonomously through acceleration and steering to track a predefined path with reference velocities accurately while paying attention to the comfort of the passengers and moreover capable of running in real time. The two controllers are compared in terms of control effort, accuracy and iteration times, Carsim is then used to show the ability of the controller to drive the vehicle.