mlsanityData to 14 Oct 2026

Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints

arXiv 2301.12099 ↗First posted 28 Jan 2023cs.LG math.OCcited by 6

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Abstract (arXiv)

We study the problem of performance optimization of closed-loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed-loop performance by automatically tuning controller gains or reference setpoints in a model-free manner. However, BO methods have rarely been tested on dynamical systems with unmodeled constraints and time-varying ambient conditions. In this paper, we propose a violation-aware contextual BO algorithm (VACBO) that optimizes closed-loop performance while simultaneously learning constraint-feasible solutions under time-varying ambient conditions. Unlike classical constrained BO methods which allow unlimited constraint violations, or 'safe' BO algorithms that are conservative and try to operate with near-zero violations, we allow budgeted constraint violations to improve constraint learning and accelerate optimization. We demonstrate the effectiveness of our proposed VACBO method for energy minimization of industrial vapor compression systems under time-varying ambient temperature and humidity.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 20 of its 47 references that are in the map. First posted on arXiv 28 Jan 2023.

Builds on

20 of 47 references.

References · 20

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8 more
  1. 2021VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraintscited by 10
  2. 2022Lower Bounds on the Worst-Case Complexity of Efficient Global Optimizationcited by 7
  3. 2019Waypoint Optimization Using Bayesian Optimization: A Case Study in Airborne Wind Energy Systemscited by 6
  4. 2020Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failurescited by 6
  5. 2018A data-driven robust optimization approach to scenario-based stochastic model predictive controlcited by 4
  6. 2020Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimizationcited by 3
  7. 2022CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraintscited by 3
  8. 2019Closed-loop Model Selection for Kernel-based Models using Bayesian Optimizationcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 0; 2025: 1; 2026: 1.

6 papers.

  1. 2023Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraintscited by 3
  2. 2023Data-driven adaptive building thermal controller tuning with constraints: A primal-dual contextual Bayesian optimization approachcited by 3
  3. 2023Bayesian Optimization of Expensive Nested Grey-Box Functionscited by 1
  4. 2025What price to pay? Auto-tuning a building MPC controller for optimal economic costcited by 1
  5. 2023Multi-Agent Bayesian Optimization with Coupled Black-Box and Affine Constraintscited by 0
  6. 2026Exploiting Hierarchical Controller Structure in Contextual Parameter Learning for Humanoid Loco-Manipulationcited by 0