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Adaptive MPC for ground vehicles: review and implementation
US & West ·
A review of adaptive model predictive control (AMPC) methods for autonomous vehicles is provided. Strategies that dynamically adapt the model, cost function, constraints, or prediction horizon based on real-time data are considered. It is shown that AMPC overcomes the limitations of traditional MPC in dynamic environments.
Why it matters
The review systematizes approaches to adaptive control, which is useful for developing robust control systems under uncertainty.
arXiv:2610.17274v1 Announce Type: new Abstract: Model reduction can substantially reduce the computational burden of model predictive control (MPC) for high-dimensional systems, but a reduced dimension chosen for performance may be insufficient for safety-critical operation.
arXiv:2509.05463v3 Announce Type: replace Abstract: This paper proposes a novel approach to design analog electronic circuits that implement Model Predictive Control (MPC) policies for dynamical systems described by affine models.
arXiv:2604.01730v3 Announce Type: replace-cross Abstract: This paper investigates Koopman operator-based approaches for multivariable control of a two-spool turbofan engine. A physics-based component-level model is developed to generate training data and validate the controllers.
