What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Statistics
Lihua Xie mainly focuses on Control theory, Linear system, Discrete time and continuous time, Mathematical optimization and Multi-agent system.
His Control theory research integrates issues from Bounded function and Riccati equation.
His studies deal with areas such as Control system, Quadratic equation, Exponential stability, Kalman filter and Robustness as well as Linear system.
His Discrete time and continuous time research includes themes of Discrete system, Markov process and Linear filter.
His Mathematical optimization research is multidisciplinary, incorporating elements of Algorithm, Upper and lower bounds and Lipschitz continuity.
His Multi-agent system research integrates issues from Network topology, Rate of convergence, Special case and Topology.
His most cited work include:
- Output feedback H∞ control of systems with parameter uncertainty (1347 citations)
- Robust control of a class of uncertain nonlinear systems (1195 citations)
- The sector bound approach to quantized feedback control (1175 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Control theory, Mathematical optimization, Linear system, Algorithm and Multi-agent system.
His study in Control theory, Nonlinear system, Discrete time and continuous time, Control system and Robust control is carried out as part of his Control theory studies.
Robust control is a subfield of Robustness that Lihua Xie investigates.
His studies deal with areas such as Convergence, Estimator, Convex function and Convex optimization as well as Mathematical optimization.
Lihua Xie combines subjects such as Kalman filter, Linear matrix inequality, Exponential stability and Applied mathematics with his study of Linear system.
His Multi-agent system study integrates concerns from other disciplines, such as Network topology and Protocol.
He most often published in these fields:
- Control theory (48.59%)
- Mathematical optimization (18.36%)
- Linear system (12.71%)
What were the highlights of his more recent work (between 2017-2021)?
- Control theory (48.59%)
- Mathematical optimization (18.36%)
- Artificial intelligence (7.72%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Control theory, Mathematical optimization, Artificial intelligence, Control theory and Algorithm.
His Control theory study combines topics from a wide range of disciplines, such as Multi-agent system, Consensus and State.
His Mathematical optimization research focuses on Regret and how it relates to Inequality.
His studies in Artificial intelligence integrate themes in fields like Machine learning, Ranging and Computer vision.
His biological study spans a wide range of topics, including Control, Optimal control, Markov process and Trajectory.
Lihua Xie has included themes like Estimator and Graph in his Algorithm study.
Between 2017 and 2021, his most popular works were:
- Adaptive Trajectory Tracking Control of a Fully Actuated Surface Vessel With Asymmetrically Constrained Input and Output (139 citations)
- Error-Constrained LOS Path Following of a Surface Vessel With Actuator Saturation and Faults (102 citations)
- Convergence of Asynchronous Distributed Gradient Methods Over Stochastic Networks (96 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Control theory
Lihua Xie mainly investigates Mathematical optimization, Artificial intelligence, Control theory, Convex function and Topology.
His research integrates issues of Multi-agent system, Regret, Model predictive control and Inequality in his study of Mathematical optimization.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Computer vision and Pattern recognition.
His work deals with themes such as Convergence and Bounded function, which intersect with Control theory.
His Convex function research also works with subjects such as
- Convex optimization that connect with fields like Quantization and Algorithm design,
- Distributed algorithm which intersects with area such as Rate of convergence.
His Topology study combines topics in areas such as Fading, Discrete time and continuous time, Enhanced Data Rates for GSM Evolution, Graph and Laplace operator.
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