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The goal is to develop an optimized motion control strategy for autonomous driving that addresses delays and computational constraints.

Infinite-time model predictive motion control for autonomous driving considering delay in resource-constrained computing platforms

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The goal is to develop an optimized motion control strategy for autonomous driving that addresses delays and computational constraints.
Developed an infinite horizon solution method for Model Predictive Control (MPC) to manage input delays and variable references.
Eliminated large-scale KKT matrix decomposition to improve computational efficiency and real-time performance.
Implemented the algorithm on a resource-constrained controller with a main frequency of 300 MHz and 5 MB Flash capacity.
Achieved a maximum single-step runtime of 0.4 ms on the controller.
Improved control accuracy and stability with effective consideration of actuator delays.
MPC strategy maintained efficiency comparable to Linear Quadratic Regulator (LQR) while addressing delays.

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Randomized trial demonstrates enhanced motion control accuracy in autonomous driving, indicating superior computational performance.

Ge et al. (2026) studied this question.

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