Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Artificial Intelligence and Robotics

Neural network

2023

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Simulation And Research Of Manipulator Motion Strategy Based On Adaptive Dynamic Programming, Ming Li, Qun Xu, Yan Wang, Zhicheng Ji Oct 2023

Simulation And Research Of Manipulator Motion Strategy Based On Adaptive Dynamic Programming, Ming Li, Qun Xu, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the difficulty of manipulator to realize high-precision motion tracking in complex and harsh environment, a strategy method based on the combination of adaptive dynamic programming (ADP) and sliding mode admittance control is proposed. The unknown environment is modeled as a linear model and based on quasi, a sliding mode admittance controller is derived to resist disturbance interference. An optimal control method that combines ADP with sliding mode admittance controller is proposed, in which the definition of R-matrix in value function is optimized and improved to further improve the tracking accuracy. The neural network based on ADP is …


Machine Learning Strategies For Potential Development In High-Entropy Driven Nickel-Based Superalloys, Marium Mostafiz Mou Jan 2023

Machine Learning Strategies For Potential Development In High-Entropy Driven Nickel-Based Superalloys, Marium Mostafiz Mou

MSU Graduate Theses

In this study, I developed Deep Learning interatomic potentials to model a multi-phase and multi-component system of Ni-based Superalloys. The system has up to three major phase constituents, namely Gamma, Gamma Prime, and Transition-metal rich Carbide. I utilized invariant scalar-based and/or equivariant, tensor-based neural network (NN) approach as implemented in DEEPMD, NEQUIP/ALLEGRO codes, respectively, and Moment Tensor Potential (MTP). For the training and validation sets, I employed the ab-initio molecular dynamics (AIMD) trajectory results and ground state DFT calculations, including the energy, force, and virial database from highly diverse compositions, temperatures, and pressures following a “High Entropy Strategy.” The Deep …