H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 70 Citations 16,469 342 World Ranking 268 National Ranking 148

Research.com Recognitions

Awards & Achievements

2005 - IEEE Fellow For contributions to nonlinear dynamical systems and recurrent neural networks.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Control theory
  • Artificial neural network

His primary areas of study are Artificial neural network, Mathematical optimization, Optimal control, Control theory and Dynamic programming. The Artificial neural network study combines topics in areas such as Stability, Control theory and Computer network. His work in the fields of Mathematical optimization, such as Bellman equation, intersects with other areas such as Approximation error.

His research integrates issues of Iterative method, Adaptive control, Nonlinear system, Intelligent control and Reinforcement learning in his study of Optimal control. His Nonlinear system research is multidisciplinary, incorporating elements of Dynamical system and Algorithm. His study in Dynamic programming is interdisciplinary in nature, drawing from both Iterative learning control, Control, Dual control theory and Discrete time and continuous time.

His most cited work include:

  • Adaptive Dynamic Programming: An Introduction (614 citations)
  • Neural-Network-Based Near-Optimal Control for a Class of Discrete-Time Affine Nonlinear Systems With Control Constraints (462 citations)
  • A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks (378 citations)

What are the main themes of his work throughout his whole career to date?

Artificial neural network, Control theory, Optimal control, Nonlinear system and Dynamic programming are his primary areas of study. His Artificial neural network research is multidisciplinary, incorporating perspectives in Algorithm, Bounded function and Adaptive system. His Optimal control study contributes to a more complete understanding of Mathematical optimization.

His Mathematical optimization research incorporates elements of Q-learning, Convergence and Discrete time and continuous time. His work deals with themes such as Stability, Zero-sum game, Observer, Actuator and System dynamics, which intersect with Nonlinear system. His Dynamic programming research integrates issues from Intelligent control, Tracking error, Approximation algorithm and Bellman equation.

He most often published in these fields:

  • Artificial neural network (54.67%)
  • Control theory (48.57%)
  • Optimal control (45.52%)

What were the highlights of his more recent work (between 2016-2021)?

  • Optimal control (45.52%)
  • Artificial neural network (54.67%)
  • Control theory (48.57%)

In recent papers he was focusing on the following fields of study:

Derong Liu focuses on Optimal control, Artificial neural network, Control theory, Dynamic programming and Nonlinear system. Optimal control is a subfield of Mathematical optimization that he tackles. The study incorporates disciplines such as Lyapunov stability, Stability, Tracking error, Adaptive system and Trajectory in addition to Artificial neural network.

His research investigates the connection between Control theory and topics such as Control that intersect with issues in Tracking. His Dynamic programming study combines topics from a wide range of disciplines, such as Bellman equation, Convergence, Discrete time and continuous time, Approximation algorithm and Monotonic function. His work on Adaptive control as part of general Nonlinear system research is often related to Scheme, thus linking different fields of science.

Between 2016 and 2021, his most popular works were:

  • Adaptive Critic Nonlinear Robust Control: A Survey (128 citations)
  • Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy Control in Smart Residential Microgrids (86 citations)
  • Residential energy scheduling for variable weather solar energy based on adaptive dynamic programming (77 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Control theory
  • Artificial neural network

His main research concerns Optimal control, Artificial neural network, Control theory, Nonlinear system and Dynamic programming. His Optimal control research is multidisciplinary, relying on both Gradient descent, Differential game, Function, Upper and lower bounds and Adaptive system. His Artificial neural network study combines topics in areas such as Control engineering, Tracking error, Electric power system and Trajectory.

His studies in Nonlinear system integrate themes in fields like Control theory, Mathematical optimization, Robustness and Reinforcement learning. His Mathematical optimization research includes themes of Scheduling, Job shop scheduling, Discrete time and continuous time and State space. His biological study spans a wide range of topics, including Convergence, Zero-sum game, Microgrid and Bellman equation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Adaptive Dynamic Programming: An Introduction

Fei-Yue Wang;Huaguang Zhang;Derong Liu.
IEEE Computational Intelligence Magazine (2009)

772 Citations

Neural-Network-Based Near-Optimal Control for a Class of Discrete-Time Affine Nonlinear Systems With Control Constraints

Huaguang Zhang;Yanhong Luo;Derong Liu.
IEEE Transactions on Neural Networks (2009)

522 Citations

A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2014)

452 Citations

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

Frank L. Lewis;Derong Liu.
(2012)

438 Citations

Networked Control Systems: Theory and Applications

Fei-Yue Wang;Derong Liu.
(2008)

391 Citations

Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems

Derong Liu;Qinglai Wei.
IEEE Transactions on Neural Networks (2014)

371 Citations

An iterative adaptive dynamic programming method for solving a class of nonlinear zero-sum differential games

Huaguang Zhang;Qinglai Wei;Derong Liu.
Automatica (2011)

343 Citations

Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2008)

338 Citations

Fuzzy Modeling and Fuzzy Control

Derong Liu;Huaguang Zhang.
(2006)

321 Citations

Optimal control of unknown nonaffine nonlinear discrete-time systems based on adaptive dynamic programming

Ding Wang;Derong Liu;Qinglai Wei;Dongbin Zhao.
Automatica (2012)

303 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Contact us

Top Scientists Citing Derong Liu

Huaguang Zhang

Huaguang Zhang

Northeastern University

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Zhanshan Wang

Zhanshan Wang

Northeastern University

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Huazhong University of Science and Technology

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Dongbin Zhao

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Chinese Academy of Sciences

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Jinde Cao

Jinde Cao

Southeast University

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Zhong-Ping Jiang

Zhong-Ping Jiang

New York University

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Qinglai Wei

Qinglai Wei

Chinese Academy of Sciences

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Shaocheng Tong

Shaocheng Tong

Liaoning University of Technology

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Tingwen Huang

Tingwen Huang

Texas A&M University at Qatar

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C. L. Philip Chen

C. L. Philip Chen

University of Macau

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Zidong Wang

Zidong Wang

Brunel University London

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Guang-Hong Yang

Guang-Hong Yang

Northeastern University

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Yan-Jun Liu

Yan-Jun Liu

Liaoning University of Technology

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