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math.OC2026
Regularized Model Predictive Control via Contractivity and Implicit Lur'e Analysis
Ryotaro Shima, Anand Gokhale, Alexander Davydov +1
This paper develops a contraction-based stability analysis for regularized model predictive control (MPC), whose feedback law is defined implicitly by a finite-horizon optimal cont…
eess.SY2026
Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control
Teruki Kato, Ryotaro Shima, Kenji Kashima
This paper proposes a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications such as reference trajectories and ope…