What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Nonlinear system
Huai-Ning Wu mainly focuses on Control theory, Nonlinear system, Artificial neural network, Fuzzy control system and Fuzzy logic.
He has researched Control theory in several fields, including Node and Network model.
His Nonlinear system study incorporates themes from Partial differential equation, Mathematical optimization, Actuator and Reinforcement learning.
His biological study spans a wide range of topics, including Passivity, Synchronization networks, Synchronization and Reaction–diffusion system.
His Fuzzy control system study integrates concerns from other disciplines, such as Control system, Robust control, Compensation, Discrete time and continuous time and Open-loop controller.
His Fuzzy logic research is multidisciplinary, incorporating perspectives in Stability and Chaotic, Lorenz system.
His most cited work include:
- New Approach to Delay-Dependent Stability Analysis and Stabilization for Continuous-Time Fuzzy Systems With Time-Varying Delay (218 citations)
- Mode-independent robust stabilization for uncertain Markovian jump nonlinear systems via fuzzy control (192 citations)
- Off-Policy Reinforcement Learning for $ H_\infty $ Control Design (180 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Control theory, Nonlinear system, Fuzzy logic, Exponential stability and Fuzzy control system.
His study in Control theory, Linear matrix inequality, Lyapunov function, Parabolic partial differential equation and Distributed parameter system falls under the purview of Control theory.
The study incorporates disciplines such as Partial differential equation, Mathematical optimization, Ode, Applied mathematics and Ordinary differential equation in addition to Nonlinear system.
Huai-Ning Wu interconnects Full state feedback, Pointwise, Stability and Piecewise in the investigation of issues within Fuzzy logic.
His research investigates the connection between Exponential stability and topics such as Artificial neural network that intersect with issues in Adaptive system, Reinforcement learning, Network model and Adaptive control.
His Fuzzy control system research integrates issues from Control system, Nonlinear control, Fuzzy number, Tracking error and Optimization problem.
He most often published in these fields:
- Control theory (73.84%)
- Nonlinear system (41.35%)
- Fuzzy logic (32.49%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (73.84%)
- Nonlinear system (41.35%)
- Exponential stability (30.38%)
In recent papers he was focusing on the following fields of study:
Control theory, Nonlinear system, Exponential stability, Fuzzy logic and Fuzzy control system are his primary areas of study.
His Control theory research includes themes of Artificial neural network and Human-in-the-loop.
His work carried out in the field of Nonlinear system brings together such families of science as Data-driven, Linear system, Optimal control and Reinforcement learning.
His Exponential stability research is multidisciplinary, incorporating elements of Parabolic partial differential equation, Linear matrix inequality, Lyapunov function, Applied mathematics and Piecewise.
His research combines Control theory and Fuzzy logic.
His work deals with themes such as Ode and Distributed parameter system, which intersect with Fuzzy control system.
Between 2019 and 2021, his most popular works were:
- Event-Triggered Optimal Control With Performance Guarantees Using Adaptive Dynamic Programming (29 citations)
- Finite-Time Synchronization and ${\mathcal{H}}_{\infty}$ Synchronization of Multiweighted Complex Networks With Adaptive State Couplings (25 citations)
- Finite-Time Passivity of Adaptive Coupled Neural Networks With Undirected and Directed Topologies (17 citations)
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