What is he best known for?
The fields of study he is best known for:
- Control theory
- Mathematical analysis
- Algebra
His primary scientific interests are in Control theory, Nonlinear system, Lyapunov function, Exponential stability and Synchronization networks.
Jun Zhao merges Control theory with Dwell time in his study.
Many of his studies on Nonlinear system apply to Bounded function as well.
His research integrates issues of Exponential function, Adaptive control and Lyapunov krasovskii in his study of Lyapunov function.
His Exponential stability research is multidisciplinary, incorporating perspectives in Integrator, Passivity and State.
His studies deal with areas such as Topology, Topology, Lorenz system, Trajectory and Complex network as well as Synchronization networks.
His most cited work include:
- Stability and L2-gain analysis for switched delay systems: A delay-dependent method (676 citations)
- On stability, L2-gain and H∞ control for switched systems (581 citations)
- Brief paper: Backstepping design for global stabilization of switched nonlinear systems in lower triangular form under arbitrary switchings (347 citations)
What are the main themes of his work throughout his whole career to date?
Jun Zhao mostly deals with Control theory, Nonlinear system, Lyapunov function, Dwell time and Control theory.
Control theory is often connected to Control engineering in his work.
His biological study spans a wide range of topics, including Stability and Tracking.
In general Nonlinear system study, his work on Backstepping often relates to the realm of Cascade, thereby connecting several areas of interest.
Jun Zhao works mostly in the field of Lyapunov function, limiting it down to topics relating to Robust control and, in certain cases, Variable structure control and Sliding mode control.
His Exponential stability study combines topics in areas such as Control system, Full state feedback, Hybrid system and Stability theory.
He most often published in these fields:
- Control theory (105.81%)
- Nonlinear system (46.21%)
- Lyapunov function (39.14%)
What were the highlights of his more recent work (between 2016-2021)?
- Control theory (105.81%)
- Nonlinear system (46.21%)
- Lyapunov function (39.14%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Control theory, Nonlinear system, Lyapunov function, Dwell time and Control theory.
In his research, Control engineering is intimately related to Control, which falls under the overarching field of Control theory.
When carried out as part of a general Nonlinear system research project, his work on Backstepping is frequently linked to work in Class, therefore connecting diverse disciplines of study.
His study on Lyapunov function also encompasses disciplines like
- Domain most often made with reference to Actuator,
- Discrete time and continuous time that connect with fields like Symmetric matrix.
He interconnects Stochastic stability, Tracking and Event triggered in the investigation of issues within Control theory.
His Exponential stability research incorporates elements of Linear matrix inequality and State.
Between 2016 and 2021, his most popular works were:
- Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems (32 citations)
- H∞ output tracking control for a class of switched LPV systems and its application to an aero‐engine model (28 citations)
- Adaptive neural control for switched non‐linear systems with multiple tracking error constraints (22 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Mathematical analysis
- Algebra
His main research concerns Control theory, Lyapunov function, Nonlinear system, Dwell time and Adaptive control.
Control engineering is closely connected to Control in his research, which is encompassed under the umbrella topic of Control theory.
His work in Lyapunov function addresses issues such as Actuator, which are connected to fields such as Domain.
His work on Backstepping as part of general Nonlinear system research is frequently linked to Mathematical model and Transition function, bridging the gap between disciplines.
The study incorporates disciplines such as Closed loop, Tracking model, Parameterized complexity, Reference model and Integrator in addition to Adaptive control.
His Linear system research is multidisciplinary, incorporating elements of Control system and Stability conditions.
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