Sebastien Gros

Control and Systems Engineering · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 23 citations into it; #2,991 of 8,257 by trust here, #6,764 by citations
• Numerical Analysis — 10 citations into it
• Reinforcement Learning — 10 citations into it
• Computational Theory and Mathematics — 8 citations into it; #4,968 of 12,182 by trust here, #10,901 by citations

Whom Sebastien Gros trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Moritz Diehl
2. David Q. Mayne
3. Toshiyuki Ohtsuka
4. Jorge Nocedal
5. Hans Joachim Ferreau
6. Ben J. A. Kröse
7. Hans Georg Bock
8. Andreas Griewank
9. Victor M. Zavala
10. Ernst Hairer

Who trusts Sebastien Gros overall

1. Shangding Gu
2. Max Schwenzer
3. Julian Berberich

Papers from Sebastien Gros's perspective

Ordered by how strongly the researchers Sebastien Gros trusts endorse each paper. Same corpus, a different order for every researcher.

1. Real-time optimization and nonlinear model predictive control of processes governed by differential-algebraic equations
2. ACADO toolkit—An open‐source framework for automatic control and dynamic optimization
3. A continuation/GMRES method for fast computation of nonlinear receding horizon control (at - Automatisierungstechnik)
4. A Real-Time Iteration Scheme for Nonlinear Optimization in Optimal Feedback Control (SIAM Journal of Control and Optimization)
5. Nominal stability of real-time iteration scheme for nonlinear model predictive control
6. Real-Time Optimization for Large Scale Nonlinear Processes
7. Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition
8. Policy Gradient Methods for Reinforcement Learning with Function Approximation
9. Numerical optimization
10. Numerical Optimization (Springer Series in Operations Research and Financial Engineering)

Their papers

• Safe Reinforcement Learning Using Robust MPC (2019) — 342 citations
• From linear to nonlinear MPC: bridging the gap via the real-time iteration (2020) — 351 citations