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Full title—Lane-Keeping Control of Autonomous Vehicles Through a Soft-Constrained Iterative LQR
The accurate prediction of smooth steering inputs is crucial for automotive applications because control actions with jitter might cause the vehicle system to become unstable.
To address this problem in automobile lane-keeping control without the use of additional smoothing algorithms, we developed a novel soft-constrained iterative linear–quadratic regulator (soft-CILQR) algorithm by integrating CILQR algorithm and a model predictive control (MPC) constraint relaxation method.
We incorporated slack variables into the state and control barrier functions of the soft-CILQR solver to soften the constraints in the optimization process such that control input stabilization can be achieved in a computationally simple manner.
Full Article: IEEE Transactions on Vehicular Technology, Volume 74, Number 4, April 2025
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