H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 84 Citations 25,682 423 World Ranking 115 National Ranking 64

Research.com Recognitions

Awards & Achievements

2008 - IEEE Fellow For contributions to nonlinear control theory and underactuated mechanical systems

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Artificial intelligence
  • Computer network

Control theory, Nonlinear system, Lyapunov function, Backstepping and Control engineering are his primary areas of study. His study in Control theory, Nonlinear control, Adaptive control, Exponential stability and Robust control falls within the category of Control theory. In the field of Nonlinear system, his study on Small-gain theorem overlaps with subjects such as Parametric statistics.

His work carried out in the field of Lyapunov function brings together such families of science as State and Stability theory. His work deals with themes such as Control system, Integrator and Motion control, which intersect with Backstepping. His research in Control engineering intersects with topics in Tracking and Mobile robot, Nonholonomic system.

His most cited work include:

  • Small-gain theorem for ISS systems and applications (1118 citations)
  • Input-to-state stability for discrete-time nonlinear systems (954 citations)
  • Tracking control of mobile robots: a case study in backstepping (742 citations)

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

His primary scientific interests are in Control theory, Nonlinear system, Nonlinear control, Control engineering and Control theory. Lyapunov function, Robust control, Exponential stability, Backstepping and Adaptive control are subfields of Control theory in which his conducts study. His work in Adaptive control addresses issues such as Dynamic programming, which are connected to fields such as System dynamics and Adaptive system.

His study looks at the relationship between Nonlinear system and fields such as Mathematical optimization, as well as how they intersect with chemical problems. His Nonlinear control research includes themes of Sliding mode control and Feedback linearization. He works mostly in the field of Control engineering, limiting it down to concerns involving Control and, occasionally, Multi-agent system.

He most often published in these fields:

  • Control theory (78.61%)
  • Nonlinear system (48.95%)
  • Nonlinear control (21.07%)

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

  • Control theory (78.61%)
  • Nonlinear system (48.95%)
  • Dynamic programming (13.29%)

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

Zhong-Ping Jiang mainly focuses on Control theory, Nonlinear system, Dynamic programming, Control theory and Optimal control. His studies in Control theory integrate themes in fields like Control, Multi-agent system and Bounded function. His Nonlinear system study integrates concerns from other disciplines, such as Control engineering, Control system and Event triggered.

His studies deal with areas such as Cooperative Adaptive Cruise Control, Adaptive control, Approximation algorithm and Adaptive system as well as Dynamic programming. He interconnects Lyapunov function and Platoon in the investigation of issues within Control theory. His research integrates issues of Data-driven, Linear system, System dynamics and Reinforcement learning in his study of Optimal control.

Between 2016 and 2021, his most popular works were:

  • Robust Adaptive Dynamic Programming (88 citations)
  • Data-Driven Adaptive Optimal Control of Connected Vehicles (65 citations)
  • Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems (54 citations)

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

  • Control theory
  • Artificial intelligence
  • Computer network

Zhong-Ping Jiang mainly investigates Control theory, Nonlinear system, Dynamic programming, Optimal control and Control theory. He combines subjects such as Control engineering and Reinforcement learning with his study of Control theory. His Nonlinear system research includes elements of Stability and Complex system.

His Dynamic programming study combines topics in areas such as Data-driven and Dynamical systems theory. The study incorporates disciplines such as Multi-agent system, Platoon and Cyber-physical system in addition to Control theory. In his research on the topic of Small-gain theorem, Lyapunov function is strongly related with Structure.

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

Small-gain theorem for ISS systems and applications

Zhong-Ping Jiang;Andrew R. Teel;Laurent Praly.
Mathematics of Control, Signals, and Systems (1994)

1295 Citations

Input-to-state stability for discrete-time nonlinear systems

Zhong-Ping Jiang;Yuan Wang.
Automatica (2001)

1066 Citations

Tracking control of mobile robots: a case study in backstepping

Zhong-Ping Jiang;Henk Nijmeijer;Henk Nijmeijer.
Automatica (1997)

1040 Citations

Design of Robust Adaptive Controllers for Nonlinear Systems with Dynamic Uncertainties

Zhong-Ping Jiang;Laurent Praly.
Automatica (1998)

610 Citations

A recursive technique for tracking control of nonholonomic systems in chained form

Zhong-Ping Jiang;H. Nijmeijer;H. Nijmeijer.
IEEE Transactions on Automatic Control (1999)

563 Citations

A Lyapunov formulation of the nonlinear small-gain theorem for interconnected ISS systems

Zhong-Ping Jiang;Iven M. Y. Mareels;Yuan Wang.
Automatica (1996)

539 Citations

Decentralized adaptive output-feedback stabilization for large-scale stochastic nonlinear systems

Shu-Jun Liu;Ji-Feng Zhang;Zhong-Ping Jiang.
Automatica (2007)

451 Citations

Computational adaptive optimal control for continuous-time linear systems with completely unknown dynamics

Yu Jiang;Zhong-Ping Jiang.
Automatica (2012)

445 Citations

Event-based consensus of multi-agent systems with general linear models

Wei Zhu;Wei Zhu;Zhong-Ping Jiang;Gang Feng.
Automatica (2014)

426 Citations

A Distributed Control Approach to A Robust Output Regulation Problem for Multi-Agent Linear Systems

Xiaoli Wang;Yiguang Hong;Jie Huang;Zhong-Ping Jiang.
IEEE Transactions on Automatic Control (2010)

416 Citations

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