Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Safe and stable control synthesis for uncertain system models via distributionally robust optimization
K. Long, Y. Yi, J. Cortés, N. Atanasov
Proceedings of the American Control Conference, San Diego, 2023, pp. 4651-4658
Abstract
This paper considers enforcing safety and stability of
dynamical systems in the presence of model uncertainty.
Safety and stability constraints may be specified using a
control barrier function (CBF) and a control Lyapunov
function (CLF), respectively. To take model uncertainty
into account, robust and chance formulations of the
constraints are commonly considered. However, this requires
known error bounds or a known distribution for the model
uncertainty, and the resulting formulations may suffer from
over-conservatism or over-confidence. In this paper, we
assume that only a finite set of model parametric
uncertainty samples is available and formulate a
distributionally robust chance-constrained program (DRCCP)
for control synthesis with CBF safety and CLF stability
guarantees. To enable the efficient computation of control
inputs during online execution, we provide a reformulation
of the DRCCP as a second-order cone program (SOCP). Our
formulation is evaluated in an adaptive cruise control
example in comparison to 1) a baseline CLF-CBF quadratic
programming approach, 2) a robust approach that assumes
known error bounds of the system uncertainty, and 3) a
chance-constrained approach that assumes a known Gaussian
Process distribution of the uncertainty.
pdf
Mechanical and Aerospace Engineering,
University of California, San Diego
9500 Gilman Dr,
La Jolla, California, 92093-0411
Ph: 1-858-822-7930
Fax: 1-858-822-3107
cortes at ucsd.edu
Skype id:
jorgilliyo