mlsanityData to 14 Oct 2026

Local Bayesian Optimization for Controller Tuning with Crash Constraints

arXiv 2411.16267 ↗First posted 25 Nov 2024eess.SY cs.LG cs.SYcited by 3

Not on the map. Why?

Abstract (arXiv)

Controller tuning is crucial for closed-loop performance but often involves manual adjustments. Although Bayesian optimization (BO) has been established as a data-efficient method for automated tuning, applying it to large and high-dimensional search spaces remains challenging. We extend a recently proposed local variant of BO to include crash constraints, where the controller can only be successfully evaluated in an a-priori unknown feasible region. We demonstrate the efficiency of the proposed method through simulations and hardware experiments. Our findings showcase the potential of local BO to enhance controller performance and reduce the time and resources necessary for tuning.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 19 of its 32 references that are in the map. First posted on arXiv 25 Nov 2024.

Builds on

19 of 32 references.

References · 19

  1. 2016Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Roboticscited by 134
  2. 2021Local policy search with Bayesian optimizationcited by 38
  3. 2018A survey on policy search algorithms for learning robot controllers in a handful of trialscited by 35
  4. 2016Automatic LQR Tuning Based on Gaussian Process Global Optimizationcited by 30
  5. 2022Local Bayesian optimization via maximizing probability of descentcited by 30
  6. 2021GoSafe: Globally Optimal Safe Robot Learningcited by 27
  7. 2019Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuningcited by 24
  8. 2020Noisy-Input Entropy Search for Efficient Robust Bayesian Optimizationcited by 24
  9. 2023The Behavior and Convergence of Local Bayesian Optimizationcited by 20
  10. 2020Robot Learning with Crash Constraintscited by 15
  11. 2020Safety-Aware Cascade Controller Tuning Using Constrained Bayesian Optimizationcited by 15
  12. 2022On Controller Tuning with Time-Varying Bayesian Optimizationcited by 13
7 more
  1. 2018Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimizationcited by 10
  2. 2021C-GLISp: Preference-Based Global Optimization under Unknown Constraints with Applications to Controller Calibrationcited by 5
  3. 2020Cascade Control: Data-Driven Tuning Approach Based on Bayesian Optimizationcited by 4
  4. 2022Benchmark of Bayesian Optimization and Metaheuristics for Control Engineering Tuning Problems with Crash Constraintscited by 3
  5. 2020Robust Parametrization of a Model Predictive Controller for a CNC Machining Center Using Bayesian Optimizationcited by 1
  6. 2022Joint Constrained Bayesian Optimization of Planning, Guidance, Control, and State Estimation of an Autonomous Underwater Vehiclecited by 1
  7. 2022What is the Best Way to Optimally Parameterize the MPC Cost Function for Vehicle Guidance?cited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026BayeSQP: Bayesian Optimization through Sequential Quadratic Programmingcited by 5
  2. 2026SLO-Guard: Crash-Aware, Budget-Consistent Autotuning for SLO-Constrained LLM Servingcited by 0
  3. 2026Local Preferential Bayesian Optimizationcited by 0