---
res:
  bibo_abstract:
  - Model Predictive Control evolved as the state of the art paradigm for safety critical
    control tasks. Control-as-Inference approaches thereof model the constrained optimization
    problem as a probabilistic inference problem. The constraints have to be implemented
    into the inference model. A recently introduced physics-informed Gaussian Process
    method uses Control-as-Inference with a Gaussian likelihood for state constraint
    modeling, but lacks guarantees of open-loop constraint satisfaction. We mitigate
    the lack of guarantees via an additional sampling step using Hamiltonian Monte
    Carlo sampling in order to obtain safe rollouts of the open-loop dynamics which
    are then used to obtain an approximation of the truncated normal distribution
    which has full probability mass in the safe area. We provide formal guarantees
    of constraint satisfaction while maintaining the ODE structure of the Gaussian
    Process on a discretized grid. Moreover, we show that we are able to perform optimization
    of a quadratic cost function by closed form Gaussian Process computations only
    and introduce the Matérn kernel into the inference model.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Jörn
      foaf_name: Tebbe, Jörn
      foaf_surname: Tebbe
      foaf_workInfoHomepage: http://www.librecat.org/personId=85958
  - foaf_Person:
      foaf_givenName: Andreas
      foaf_name: Besginow, Andreas
      foaf_surname: Besginow
      foaf_workInfoHomepage: http://www.librecat.org/personId=61743
  - foaf_Person:
      foaf_givenName: Markus
      foaf_name: Lange-Hegermann, Markus
      foaf_surname: Lange-Hegermann
      foaf_workInfoHomepage: http://www.librecat.org/personId=71761
  bibo_doi: 10.1016/j.ejcon.2026.101600
  dct_date: 2026^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/0947-3580
  - http://id.crossref.org/issn/1435-5671
  dct_language: eng
  dct_publisher: Elsevier BV@
  dct_title: Physics-informed Gaussian Processes as Linear Model Predictive Controller
    with Constraint Satisfaction@
...