Optimal control, MPC and MPC-like algorithms for wave energy systems: An overview
Abstract Model predictive control (MPC) has achieved considerable success in the process
industries, with its ability to deal with linear and nonlinear models, while observing system …
industries, with its ability to deal with linear and nonlinear models, while observing system …
Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions
This article is a survey paper on solving spacecraft trajectory optimization problems. The
solving process is decomposed into four key steps of mathematical modeling of the problem …
solving process is decomposed into four key steps of mathematical modeling of the problem …
Optimal charging of Li-ion batteries with coupled electro-thermal-aging dynamics
Fast and safe charging protocols are crucial for enhancing the practicality of batteries,
especially for mobile applications, such as smartphones and electric vehicles. This paper …
especially for mobile applications, such as smartphones and electric vehicles. This paper …
GPOPS-II: A MATLAB software for solving multiple-phase optimal control problems using hp-adaptive Gaussian quadrature collocation methods and sparse nonlinear …
A general-purpose MATLAB software program called GPOPS--II is described for solving
multiple-phase optimal control problems using variable-order Gaussian quadrature …
multiple-phase optimal control problems using variable-order Gaussian quadrature …
Data-driven excavation trajectory planning for unmanned mining excavator
In autonomous mining scenarios, excavation trajectory planning plays a significant role
since it considerably influences the working performance of the unmanned mining excavator …
since it considerably influences the working performance of the unmanned mining excavator …
A ph mesh refinement method for optimal control
A mesh refinement method is described for solving a continuous‐time optimal control
problem using collocation at Legendre–Gauss–Radau points. The method allows for …
problem using collocation at Legendre–Gauss–Radau points. The method allows for …
Model-based reinforcement learning for approximate optimal regulation
Reinforcement learning (RL)-based online approximate optimal control methods applied to
deterministic systems typically require a restrictive persistence of excitation (PE) condition …
deterministic systems typically require a restrictive persistence of excitation (PE) condition …
Convergence of the forward-backward sweep method in optimal control
M McAsey, L Mou, W Han - Computational Optimization and Applications, 2012 - Springer
Abstract The Forward-Backward Sweep Method is a numerical technique for solving optimal
control problems. The technique is one of the indirect methods in which the differential …
control problems. The technique is one of the indirect methods in which the differential …
Optimal charging of li-ion batteries via a single particle model with electrolyte and thermal dynamics
This article seeks to derive insight on battery charging control using electrochemistry
models. Directly using full order complex multi-partial differential equation (PDE) …
models. Directly using full order complex multi-partial differential equation (PDE) …
[HTML][HTML] Adaptive mesh refinement method for optimal control using nonsmoothness detection and mesh size reduction
An adaptive mesh refinement method for solving optimal control problems is developed. The
method employs orthogonal collocation at Legendre–Gauss–Radau points, and adjusts …
method employs orthogonal collocation at Legendre–Gauss–Radau points, and adjusts …