Regularity Properties of Optimization-Based Controllers
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Abstract (arXiv)
This paper studies regularity properties of optimization-based controllers, which are obtained by solving optimization problems where the parameter is the system state and the optimization variable is the input to the system. Under a wide range of assumptions on the optimization problem data, we provide an exhaustive collection of results about their regularity, and examine their implications on the existence and uniqueness of solutions and the forward invariance guarantees for the resulting closed-loop systems. We discuss the broad relevance of the results in different areas of systems and controls.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Nov 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 2.
5 papers.
- 2025Modeling and Control of Deep Sign-Definite Dynamics with Application to Hybrid Powertrain Controlcited by 1
- 2024Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputscited by 0
- 2025Off-Policy Reinforcement Learning with Anytime Safety Guarantees via Robust Safe Gradient Flowcited by 0
- 2026Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Controlcited by 0
- 2026Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guaranteescited by 0
- 2026Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guarantees14 Apr 2026
- 2026Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control26 Jan 2026
- 2025Off-Policy Reinforcement Learning with Anytime Safety Guarantees via Robust Safe Gradient Flow1 Oct 2025
- 2025Modeling and Control of Deep Sign-Definite Dynamics with Application to Hybrid Powertrain Control24 Sep 2025
- 2024Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputs5 Mar 2024