Guo-Ping Liu

What is he best known for?

The fields of study he is best known for:

• Control theory
• Artificial intelligence
• Operating system

His main research concerns Control theory, Control system, Control engineering, Model predictive control and Networked control system. His study in Control theory concentrates on Linear matrix inequality, Stability, Nonlinear system, Lyapunov function and Linear system. His Linear matrix inequality research includes elements of Lyapunov functional and Delay dependent.

His studies in Control system integrate themes in fields like Genetic algorithm and Interval. The concepts of his Model predictive control study are interwoven with issues in Quantization and Computer engineering. His Networked control system research incorporates themes from Stability criterion, Compensation, Automatic control, Real-time computing and Transmission delay.

His most cited work include:

• Technical Communique: Delay-dependent criteria for robust stability of time-varying delay systems (921 citations)
• Parameter-dependent Lyapunov functional for stability of time-delay systems with polytopic-type uncertainties (679 citations)
• Delay-dependent robust stability criteria for uncertain neutral systems with mixed delays (678 citations)

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

Guo-Ping Liu mostly deals with Control theory, Control system, Model predictive control, Control engineering and Networked control system. His study in Network packet extends to Control theory with its themes. His research investigates the link between Control system and topics such as Stability criterion that cross with problems in Linear matrix inequality.

His Model predictive control research integrates issues from Multi-agent system, Network delay and Constant. His research investigates the connection between Multi-agent system and topics such as Protocol that intersect with issues in Consensus and Topology. His studies deal with areas such as Matrix and Eigenvalues and eigenvectors as well as Linear system.

He most often published in these fields:

• Control theory (79.41%)
• Control system (35.64%)
• Model predictive control (29.41%)

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

• Control theory (79.41%)
• Control system (35.64%)
• Model predictive control (29.41%)

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

His primary areas of investigation include Control theory, Control system, Model predictive control, Multi-agent system and Network packet. His Control research extends to the thematically linked field of Control theory. His Control system research is multidisciplinary, incorporating elements of Kalman filter, Time delays, Real-time computing and Embedded system.

Guo-Ping Liu has included themes like Tracking error, State and Mobile robot in his Model predictive control study. Guo-Ping Liu has researched Multi-agent system in several fields, including Distributed computing, Network topology, Protocol and Topology. His study in Network packet is interdisciplinary in nature, drawing from both State-space representation, Process, Linear system and Networked control system.

Between 2016 and 2021, his most popular works were:

• A Robust High-Accuracy Ultrasound Indoor Positioning System Based on a Wireless Sensor Network. (65 citations)
• Variance-Constrained Recursive State Estimation for Time-Varying Complex Networks With Quantized Measurements and Uncertain Inner Coupling (53 citations)
• A Survey on Formation Control of Small Satellites (39 citations)

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

• Control theory
• Artificial intelligence
• Operating system

Guo-Ping Liu mainly focuses on Control theory, Multi-agent system, Model predictive control, Networked control system and Network packet. Control theory connects with themes related to Constant in his study. The study incorporates disciplines such as Stability, Distributed computing, Protocol and Topology in addition to Multi-agent system.

His work in Model predictive control addresses subjects such as Network topology, which are connected to disciplines such as Matrix, Algorithm and Upper and lower bounds. Control system and Control engineering are inextricably linked to his Networked control system research. His Network packet research includes themes of Finite time, Time delays and Control.