Lunan Zheng

About

Lunan Zheng is a leading researcher in neural dynamics and robotics, specializing in the design of recurrent neural networks (RNNs) for solving time-varying optimization problems. His major contributions center on developing novel varying-parameter convergent-differential neural networks (VP-CDNN) and power-type varying-parameter RNNs, which dramatically improve the speed and robustness of solving time-varying quadratic programming (TVQP) problems. These innovations have direct applications in redundant robot manipulator control, enabling efficient repetitive motion planning and mutual-collision-avoidance for dual-arm cooperative tasks. Zheng’s work is highly influential, with his top-cited paper, "A New Varying-Parameter Convergent-Differential Neural-Network for Solving Time-Varying Convex QP Problem," garnering 187 citations, and three additional papers each exceeding 90 citations. Notably, his 2017 study comparing three RNNs and numerical methods for repetitive motion planning has been cited 185 times, underscoring its impact on robotics. Zheng has also advanced theoretical analysis, including robustness studies of power-type VPNN and integral RNNs for Sylvester equations. His research bridges cutting-edge neural network theory with practical robotic systems, making him a key figure in intelligent control and optimization.

Research Focus

Key Achievements

Top Papers

1. 1
   A New Varying-Parameter Convergent-Differential Neural-Network for Solving Time-Varying Convex QP Problem Constrained by Linear-Equality

   187 citations · 2018
2. 2
   Three Recurrent Neural Networks and Three Numerical Methods for Solving a Repetitive Motion Planning Scheme of Redundant Robot Manipulators

   185 citations · 2017
3. 3
   Robustness Analysis of a Power-Type Varying-Parameter Recurrent Neural Network for Solving Time-Varying QM and QP Problems and Applications

   101 citations · 2018
4. 4
   Mutual-Collision-Avoidance Scheme Synthesized by Neural Networks for Dual Redundant Robot Manipulators Executing Cooperative Tasks

   94 citations · 2020
5. 5
   Power-Type Varying-Parameter RNN for Solving TVQP Problems: Design, Analysis, and Applications

   90 citations · 2018
6. 6
   Design and Analysis of a Novel Integral Recurrent Neural Network for Solving Time-Varying Sylvester Equation

   37 citations · 2019
7. 7
   A Punishment Mechanism-Combined Recurrent Neural Network to Solve Motion-Planning Problem of Redundant Robot Manipulators

   34 citations · 2021
8. 8
   Design, Analysis, and Application of a Discrete Error Redefinition Neural Network for Time-Varying Quadratic Programming

   19 citations · 2023
9. 9
   A review on varying-parameter convergence differential neural network

   14 citations · 2022
10. 10
    A gain-adjustment neural network based time-varying underdetermined linear equation solving method

    6 citations · 2021

Key Collaborators

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