Integral reinforcement learning‐based approximate minimum time‐energy path planning in an unknown environment
From MaRDI portal
Publication:6089846
DOI10.1002/rnc.5122zbMath1526.93176OpenAlexW3091880708MaRDI QIDQ6089846
Yan Wan, Unnamed Author, Frank L. Lewis, Unnamed Author
Publication date: 13 November 2023
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.5122
Applications of optimal control and differential games (49N90) Automated systems (robots, etc.) in control theory (93C85)
Related Items (1)
Cites Work
- Unnamed Item
- Optimal tracking control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning
- Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems
- Adaptive optimal control for continuous-time linear systems based on policy iteration
- Shortest paths of bounded curvature in the plane
- Nonlinear \(H_2/H_\infty\) constrained feedback control. A practical design approach using neural networks
- Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach
- Online adaptive algorithm for optimal control with integral reinforcement learning
- On-line estimation and path planning for multiple vehicles in an uncertain environment
- On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents
- Inter‐sample avoidance in trajectory optimizers using mixed‐integer linear programming
- Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers
This page was built for publication: Integral reinforcement learning‐based approximate minimum time‐energy path planning in an unknown environment