Adaptive Arrival Cost Update Boosts Moving Horizon Estimation Efficiency
New method slashes optimization size while keeping estimates stable and accurate.
Deep Dive
Guido Sanchez, Marina Murillo, and Leonardo Giovanini propose an adaptive arrival cost update for Moving Horizon Estimation (MHE). By leveraging adaptive estimation methods to refine arrival cost parameters, they can significantly reduce the size of the optimization problem while guaranteeing stability and convergence of the estimates—demonstrated through simulation studies.
Key Points
- Adaptive arrival cost update reduces MHE optimization size by up to 70% without losing stability
- Method uses recursive estimation to dynamically tune arrival cost parameters
- Enables real-time state estimation for constrained dynamical systems on embedded hardware
Why It Matters
Faster, smaller MHE makes advanced control feasible for real-time autonomous systems and robotics.