3 papers
eess.SY2025
Neural Co-state Projection Regulator: A Model-free Paradigm for Real-time Optimal Control with Input Constraints
Lihan Lian, Uduak Inyang-Udoh
Learning-based approaches, notably Reinforcement Learning (RL), have shown promise for solving optimal control tasks without explicit system models. However, these approaches are o…
eess.SY2025
Neural Co-state Regulator: A Data-Driven Paradigm for Real-time Optimal Control with Input Constraints
Lihan Lian, Yuxin Tong, Uduak Inyang-Udoh
We propose a novel unsupervised learning framework for solving nonlinear optimal control problems (OCPs) with input constraints in real-time. In this framework, a neural network (N…
eess.SY2025
Co-state Neural Network for Real-time Nonlinear Optimal Control with Input Constraints
Lihan Lian, Uduak Inyang-Udoh
In this paper, we propose a method to solve nonlinear optimal control problems (OCPs) with constrained control input in real-time using neural networks (NNs). We introduce what we…