58 citations · 99 across the 9 of their papers we have counts for
11 papers
Optimal energy conversion -- A port-Hamiltonian approach
Guanru Pan, Karl Worthmann, Manuel Schaller +1
This paper studies optimal energy conversion in port-Hamiltonian systems. We analyze state- and control-constrained finite-horizon optimal control problems that maximize energy con…
Uncertainty Propagation under Residual Disturbances: A Smart-Home Case Study
Guanru Pan, Dirk Reinhardt, Sebastien Gros +1
This paper presents a data-driven framework for uncertainty propagation under unmeasured or statistically unmodeled (unstructured) disturbances. We consider residual disturbances,…
Concave Comparison Functions for Accelerating Constrained Lyapunov Decay
Shuyuan Fan, Guanru Pan, Herbert Werner
What limits how fast a Lyapunov function can decay under input bounds? We address this question by showing how the shape of Lyapunov comparison functions governs guaranteed decay f…
A Stochastic Fundamental Lemma with Reduced Disturbance Data Requirements
Ruchuan Ou, Guanru Pan, Timm Faulwasser
Recently, the fundamental lemma by Willems et al. has been extended towards stochastic LTI systems subject to process disturbances. Using this lemma requires previously recorded da…
Distributionally robust uncertainty quantification via data-driven stochastic optimal control
Guanru Pan, Timm Faulwasser
This paper studies optimal control problems of unknown linear systems subject to stochastic disturbances of uncertain distribution. Uncertainty about the stochastic disturbances is…
Towards data-driven stochastic predictive control
Guanru Pan, Ruchuan Ou, Timm Faulwasser
Data-driven predictive control based on the fundamental lemma by Willems et al. is frequently considered for deterministic LTI systems subject to measurement noise. However, little…
Data-driven Stochastic Output-Feedback Predictive Control: Recursive Feasibility through Interpolated Initial Conditions
Guanru Pan, Ruchuan Ou, Timm Faulwasser
The paper investigates data-driven output-feedback predictive control of linear systems subject to stochastic disturbances. The scheme relies on the recursive solution of a suitabl…
On Data-Driven Stochastic Output-Feedback Predictive Control
Guanru Pan, Ruchuan Ou, Timm Faulwasser
The fundamental lemma by Jan C. Willems and co-authors enables the representation of all input-output trajectories of a linear time-invariant system by measured input-output data.…
NMPC in Active Subspaces: Dimensionality Reduction with Recursive Feasibility Guarantees
Guanru Pan, Timm Faulwasser
Dimensionality reduction of decision variables is a practical and classic method to reduce the computational burden in linear and Nonlinear Model Predictive Control (NMPC). Availab…
Behavioral Theory for Stochastic Systems? A Data-driven Journey from Willems to Wiener and Back Again
Timm Faulwasser, Ruchuan Ou, Guanru Pan +2
The fundamental lemma by Jan C. Willems and co-workers, which is deeply rooted in behavioral systems theory, has become one of the supporting pillars of the recent progress on data…
On a Stochastic Fundamental Lemma and Its Use for Data-Driven Optimal Control
Guanru Pan, Ruchuan Ou, Timm Faulwasser
Data-driven control based on the fundamental lemma by Willems et al. is frequently considered for deterministic LTI systems subject to measurement noise. However, besides measureme…