Constraint Selection in Optimization-Based Controllers

Human-machine collaboration often involves constrained optimization problems for decision-making processes. However, when the machine is a dynamical system with a continuously evolving state, infeasibility due to multiple conflicting constraints can lead to dangerous outcomes. In this work, we propose a heuristic-based method that resolves infeasibility at every time step by selectively disregarding a subset of soft constraints based on the past values of the Lagrange multipliers. Compared to existing approaches, our method requires the solution of a smaller optimization problem to determine feasibility, resulting in significantly faster computation. Through a series of simulations, we demonstrate that our algorithm achieves performance comparable to state-of-the-art methods while offering improved computational efficiency.

@article{lee2025_2505.05502,
  title={ Constraint Selection in Optimization-Based Controllers },
  author={ Haejoon Lee and Panagiotis Rousseas and Dimitra Panagou },
  journal={arXiv preprint arXiv:2505.05502},
  year={ 2025 }
}