collaborators

6 papers

q-fin.MF2025

Generative Market Equilibrium Models with Stable Adversarial Learning via Reinforcement

Anastasis Kratsios, Xiaofei Shi, Qiang Sun +1

We present a general computational framework for solving continuous-time financial market equilibria under minimal modeling assumptions while incorporating realistic financial fric…

eess.SY2025

Dynamical Simulation Model of the Pyro-Process in Cement Clinker Production

Jan Lorenz Svensen, Wilson Ricardo Leal da Silva, Zhanhao Zhang +2

This study presents a dynamic simulation model for the pyro-process of clinker production in cement plants. The study aims to construct a simulation model capable of replicating th…

math.OC2025

Numerical Discrete-Time Implementation of Continuous-Time Linear-Quadratic Model Predictive Control

Zhanhao Zhang, Anders Hilmar Damm Christensen, Steen Hørsholt +1

This study presents the design, discretization and implementation of the continuous-time linear-quadratic model predictive control (CT-LMPC). The control model of the CT-LMPC is pa…

math.OC2024

Numerical Discretization Methods for the Discounted Linear Quadratic Control Problem

Zhanhao Zhang, Steen Hørsholt, John Bagterp Jørgensen

This study focuses on the numerical discretization methods for the continuous-time discounted linear-quadratic optimal control problem (LQ-OCP) with time delays. By assuming piecew…

eess.SY2024

Numerical Discretization Methods for the Extended Linear Quadratic Control Problem

Zhanhao Zhang, Jan Lorenz Svensen, Morten Wahlgreen Kaysfeld +3

In this study, we introduce numerical methods for discretizing continuous-time linear-quadratic optimal control problems (LQ-OCPs). The discretization of continuous-time LQ-OCPs is…

eess.SY2024

Numerical Discretization Methods for Linear Quadratic Control Problems with Time Delays

Zhanhao Zhang, Steen Hørsholt, John Bagterp Jørgensen

This paper presents the numerical discretization methods of the continuous-time linear-quadratic optimal control problems (LQ-OCPs) with time delays. We describe the weight matrice…