H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 36 Citations 4,999 163 World Ranking 2340 National Ranking 265

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Artificial intelligence
  • Mechanical engineering

Jing Na spends much of his time researching Control theory, Adaptive control, Nonlinear system, Estimation theory and Control engineering. Lyapunov function, Tracking error, Torque, System dynamics and Robustness are among the areas of Control theory where the researcher is concentrating his efforts. His work on Backstepping as part of general Adaptive control study is frequently linked to Rate of convergence, therefore connecting diverse disciplines of science.

Jing Na interconnects Artificial neural network, Overshoot and Active suspension, Suspension in the investigation of issues within Nonlinear system. He works mostly in the field of Artificial neural network, limiting it down to concerns involving Dead zone and, occasionally, Synchronous motor. As a part of the same scientific family, he mostly works in the field of Estimation theory, focusing on Vehicle dynamics and, on occasion, Gradient descent.

His most cited work include:

  • Adaptive Prescribed Performance Motion Control of Servo Mechanisms with Friction Compensation (290 citations)
  • Robust adaptive finite-time parameter estimation and control for robotic systems (166 citations)
  • Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence (151 citations)

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

Jing Na mainly investigates Control theory, Nonlinear system, Adaptive control, Artificial neural network and Estimation theory. His Control theory study frequently draws connections between related disciplines such as Control engineering. His Nonlinear system study incorporates themes from Control system and Observer.

His Adaptive control study combines topics in areas such as Reference model, Transient response, Adaptive algorithm and System dynamics. He works mostly in the field of Artificial neural network, limiting it down to topics relating to Servomechanism and, in certain cases, Servo and Servomotor, as a part of the same area of interest. His biological study deals with issues like Vehicle dynamics, which deal with fields such as Torque.

He most often published in these fields:

  • Control theory (83.72%)
  • Nonlinear system (36.28%)
  • Adaptive control (33.49%)

What were the highlights of his more recent work (between 2019-2021)?

  • Control theory (83.72%)
  • Nonlinear system (36.28%)
  • Control system (11.16%)

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

Jing Na mostly deals with Control theory, Nonlinear system, Control system, Adaptive control and Estimation theory. His research integrates issues of Artificial neural network and Filter in his study of Control theory. His Nonlinear system research focuses on Fuzzy logic and how it connects with Adaptive algorithm.

His Control system research incorporates themes from Stability, CarSim and Observer. The Adaptive control study combines topics in areas such as Trajectory and Reference model. His Estimation theory study which covers Servomotor that intersects with Backstepping.

Between 2019 and 2021, his most popular works were:

  • USDE-Based Sliding Mode Control for Servo Mechanisms With Unknown System Dynamics (39 citations)
  • Adaptive Finite-Time Fuzzy Control of Nonlinear Active Suspension Systems With Input Delay (39 citations)
  • Neural-Network-Based Adaptive Funnel Control for Servo Mechanisms With Unknown Dead-Zone (39 citations)

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

  • Control theory
  • Artificial intelligence
  • Mechanical engineering

His primary areas of investigation include Control theory, Nonlinear system, Servomotor, Estimation theory and Adaptive control. His work carried out in the field of Control theory brings together such families of science as Artificial neural network and Filter. CarSim, Suspension, Active suspension and Adaptive algorithm is closely connected to Fuzzy logic in his research, which is encompassed under the umbrella topic of Nonlinear system.

While the research belongs to areas of Servomotor, he spends his time largely on the problem of Servomechanism, intersecting his research to questions surrounding Backstepping. His Adaptive control research is multidisciplinary, incorporating elements of Vehicle dynamics and Fuzzy control system. The concepts of his Tracking error study are interwoven with issues in Control system and System dynamics.

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.

Best Publications

Adaptive Prescribed Performance Motion Control of Servo Mechanisms with Friction Compensation

Jing Na;Qiang Chen;Xuemei Ren;Yu Guo.
IEEE Transactions on Industrial Electronics (2014)

346 Citations

Robust adaptive finite-time parameter estimation and control for robotic systems

Jing Na;Muhammad Nasiruddin Mahyuddin;Guido Herrmann;Xuemei Ren.
International Journal of Robust and Nonlinear Control (2015)

201 Citations

Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence

Chenguang Yang;Yiming Jiang;Wei He;Jing Na.
IEEE Transactions on Industrial Electronics (2018)

197 Citations

Adaptive Control for Nonlinear Pure-Feedback Systems With High-Order Sliding Mode Observer

Jing Na;Xuemei Ren;Dongdong Zheng.
IEEE Transactions on Neural Networks (2013)

191 Citations

Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.

Yingbo Huang;Jing Na;Xing Wu;Xiaoqin Liu.
Isa Transactions (2015)

159 Citations

Adaptive neural dynamic surface control for servo systems with unknown dead-zone

Jing Na;Jing Na;Xuemei Ren;Guido Herrmann;Zhi Qiao.
Control Engineering Practice (2011)

120 Citations

Active Adaptive Estimation and Control for Vehicle Suspensions With Prescribed Performance

Jing Na;Yingbo Huang;Xing Wu;Guanbin Gao.
IEEE Transactions on Control Systems and Technology (2018)

111 Citations

Online adaptive approximate optimal tracking control with simplified dual approximation structure for continuous-time unknown nonlinear systems

Jing Na;Guido Herrmann.
IEEE/CAA Journal of Automatica Sinica (2014)

108 Citations

Adaptive prescribed performance control of nonlinear systems with unknown dead zone

Jing Na.
International Journal of Adaptive Control and Signal Processing (2013)

101 Citations

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

Yongfeng Lv;Jing Na;Qinmin Yang;Xing Wu.
International Journal of Control (2016)

99 Citations

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Best Scientists Citing Jing Na

Feng Ding

Feng Ding

Jiangnan University

Publications: 56

Ding Wang

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Beijing University of Technology

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Liaoning University of Technology

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Shuai Li

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Swansea University

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Derong Liu

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Shaocheng Tong

Liaoning University of Technology

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Xiaoping Liu

Xiaoping Liu

Lakehead University

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Yunong Zhang

Yunong Zhang

Sun Yat-sen University

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Tasawar Hayat

Tasawar Hayat

Quaid-i-Azam University

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Huanqing Wang

Huanqing Wang

Carleton University

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C. L. Philip Chen

C. L. Philip Chen

University of Macau

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Ahmad Taher Azar

Ahmad Taher Azar

Prince Sultan University

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Quanmin Zhu

Quanmin Zhu

University of the West of England

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Chenguang Yang

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South China University of Technology

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Rathinasamy Sakthivel

Rathinasamy Sakthivel

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Peng Shi

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