Shu Li

Orcid: 0000-0002-5828-3010

Affiliations:
  • Harbin Institute of Technology, State Key Laboratory of Robotics and System, China
  • Liaoning University of Technology, College of Science, Jinzhou, China (former)


According to our database1, Shu Li authored at least 18 papers between 2015 and 2022.

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Timeline

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Bibliography

2022
Adaptive Fuzzy Finite-Time Tracking Control for Nonstrict Full States Constrained Nonlinear System With Coupled Dead-Zone Input.
IEEE Trans. Cybern., 2022

A 2-year locomotive exploration and scientific investigation of the lunar farside by the Yutu-2 rover.
Sci. Robotics, 2022

Velocity Following Control of a Pseudo-Driven Wheel for Reducing Internal Forces Between Wheels.
IEEE Robotics Autom. Lett., 2022

2021
Adaptive Neural Network-Based Finite-Time Tracking Control for Nonstrict Nonaffined MIMO Nonlinear Systems.
IEEE Trans. Syst. Man Cybern. Syst., 2021

Adaptive Neural Network-Based Finite-Time Online Optimal Tracking Control of the Nonlinear System With Dead Zone.
IEEE Trans. Cybern., 2021

2020
Reinforcement Learning Neural Network-Based Adaptive Control for State and Input Time-Delayed Wheeled Mobile Robots.
IEEE Trans. Syst. Man Cybern. Syst., 2020

Adaptive Partial Reinforcement Learning Neural Network-Based Tracking Control for Wheeled Mobile Robotic Systems.
IEEE Trans. Syst. Man Cybern. Syst., 2020

Definition and Application of Variable Resistance Coefficient for Wheeled Mobile Robots on Deformable Terrain.
IEEE Trans. Robotics, 2020

ADP-Based Online Tracking Control of Partially Uncertain Time-Delayed Nonlinear System and Application to Wheeled Mobile Robots.
IEEE Trans. Cybern., 2020

Adaptive NN-based finite-time tracking control for wheeled mobile robots with time-varying full state constraints.
Neurocomputing, 2020

2019
Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems With Unknown Nonaffine Dead-Zone Input.
IEEE Trans. Neural Networks Learn. Syst., 2019

2018
Adaptive neural network tracking control-based reinforcement learning for wheeled mobile robots with skidding and slipping.
Neurocomputing, 2018

Adaptive NN-Based Tracking Control for Partial Uncertain Time-Delayed WMR System.
Proceedings of the IEEE International Conference on Real-time Computing and Robotics, 2018

2017
Adaptive Neural Network-Based Tracking Control for Full-State Constrained Wheeled Mobile Robotic System.
IEEE Trans. Syst. Man Cybern. Syst., 2017

Neural Approximation-Based Adaptive Control for a Class of Nonlinear Nonstrict Feedback Discrete-Time Systems.
IEEE Trans. Neural Networks Learn. Syst., 2017

2016
Adaptive control of nonlinear systems with full state constraints using Integral Barrier Lyapunov Functionals.
Neurocomputing, 2016

Neural network-based adaptive control for a class of chemical reactor systems with non-symmetric dead-zone.
Neurocomputing, 2016

2015
Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with unknown time-delay.
Neurocomputing, 2015


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