Radial basis function neural networks for optimal control with model reduction and transfer learning
This paper proposes a method to compute the solutions of linear optimal control expressed
in terms of the radial basis function neural networks with Gaussian activation functions for …
in terms of the radial basis function neural networks with Gaussian activation functions for …
Robustness improvement of optimal control in terms of RBFNN with empirical model reduction and transfer learning
This paper proposes a method to compute solutions of optimal controls for dynamic systems
in terms of radial basis function neural networks (RBFNN) with Gaussian neurons. The …
in terms of radial basis function neural networks (RBFNN) with Gaussian neurons. The …
[图书][B] Optimal Control with Model Reduction and Machine Learning
A Zhao - 2023 - search.proquest.com
Different challenges exist in the area of control, including but not limited to the high
computational cost, model uncertainty, disturbances, nonlinearity, multi-objective …
computational cost, model uncertainty, disturbances, nonlinearity, multi-objective …