Approximate infinite-horizon predictive control
Author:
Affiliation:
1. Technische Universitt Chemnitz,Laboratory for Automatic Control and System Dynamics,Chemnitz,Germany,09107
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9992315/9992317/09992741.pdf?arnumber=9992741
Reference24 articles.
1. Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach
2. Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof
3. Stability and feasibility of state constrained MPC without stabilizing terminal constraints
4. A quasi-infinite horizon nonlinear model predictive control scheme with guaranteed stability
5. Model predictive control: for want of a local control Lyapunov function, all is not lost
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1. Neural Horizon Model Predictive Control - Increasing Computational Efficiency with Neural Networks;2024 American Control Conference (ACC);2024-07-10
2. Predictive Control with Terminal Costs Based on Online Learning Using Value Iteration;2024 European Control Conference (ECC);2024-06-25
3. Analysis and design of model predictive control frameworks for dynamic operation—An overview;Annual Reviews in Control;2024
4. Predictive Control with Learning-Based Terminal Costs Using Approximate Value Iteration;IFAC-PapersOnLine;2023
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