Analysis of explicit model predictive control for path-following control

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits th...

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Bibliographic Details
Published in:PloS one 2018-03, Vol.13 (3), p.e0194110-e0194110
Main Authors: Lee, Junho, Chang, Hyuk-Jun
Format: Article
Language:English
Subjects:
Algorithms
Automatic control
Automotive parts
Autonomous vehicles
Computation
Computer applications
Computer simulation
Control methods
Control systems design
Controllers
Design
Electric vehicles
Engineering and Technology
Engineering research
Feedback
Kinematics
Lane keeping
Mathematical models
Neural networks
Optimization
Optimization theory
Physical Sciences
Predictive control
Process control systems
Quadratic programming
Research and Analysis Methods
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Summary:In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0194110