What is he best known for?
The fields of study he is best known for:
- Control theory
- Statistics
- Artificial intelligence
Steven X. Ding focuses on Control theory, Fault detection and isolation, Robustness, Control engineering and Residual.
His studies link Fuzzy logic with Control theory.
His Fault detection and isolation study integrates concerns from other disciplines, such as Control system, Linear system, Discrete time and continuous time, Lyapunov function and Actuator.
The various areas that Steven X. Ding examines in his Robustness study include Optimization problem and Model matching.
His biological study spans a wide range of topics, including Data-driven, Control reconfiguration, Fault tolerance, Feedback control and Realization.
Steven X. Ding focuses mostly in the field of Residual, narrowing it down to topics relating to Constant false alarm rate and, in certain cases, Randomized algorithm, Algorithm design, Generalized canonical correlation and Resource allocation.
His most cited work include:
- Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools (1477 citations)
- A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches (1091 citations)
- A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process (831 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Fault detection and isolation, Control theory, Residual, Control engineering and Control system.
His work investigates the relationship between Fault detection and isolation and topics such as Robustness that intersect with problems in Linear matrix inequality and Discrete time and continuous time.
His Control theory research includes themes of Fault tolerance and Fuzzy logic.
He has included themes like Optimization problem, Mathematical optimization, Computation and Parity space in his Residual study.
His Control engineering research is multidisciplinary, incorporating perspectives in Data-driven, Control and Process control.
His Control system research includes elements of Automatic control, Real-time computing, Distributed computing and Network packet.
He most often published in these fields:
- Fault detection and isolation (55.17%)
- Control theory (53.83%)
- Residual (24.52%)
What were the highlights of his more recent work (between 2018-2021)?
- Fault detection and isolation (55.17%)
- Control theory (53.83%)
- Residual (24.52%)
In recent papers he was focusing on the following fields of study:
Steven X. Ding spends much of his time researching Fault detection and isolation, Control theory, Residual, Algorithm and Fault tolerance.
His Fault detection and isolation research is multidisciplinary, incorporating elements of Data mining, Data-driven, Constant false alarm rate, Benchmark and Robustness.
His Control theory study combines topics from a wide range of disciplines, such as Multiplicative function and Fuzzy logic.
His Residual research is multidisciplinary, relying on both Control system, Inverter and Minimax.
The study incorporates disciplines such as Control engineering, Control, Automatic control and Degradation in addition to Control system.
His Algorithm research incorporates themes from Covariance, Discrete time and continuous time and Metric.
Between 2018 and 2021, his most popular works were:
- Performance-based fault detection and fault-tolerant control for automatic control systems (41 citations)
- On robust Kalman filter for two-dimensional uncertain linear discrete time-varying systems: A least squares method (34 citations)
- A Distributed Canonical Correlation Analysis-Based Fault Detection Method for Plant-Wide Process Monitoring (30 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Statistics
- Artificial intelligence
Steven X. Ding mainly investigates Fault detection and isolation, Control theory, Fault tolerance, Data mining and Discrete time and continuous time.
His studies in Fault detection and isolation integrate themes in fields like Control system, Margin and Algorithm, Constant false alarm rate, Residual.
His study in the field of Computation also crosses realms of Isolation.
His Control theory study combines topics in areas such as Open-circuit voltage and Converters.
He interconnects Multiplicative function, Control theory, State observer, Estimator and Backstepping in the investigation of issues within Fault tolerance.
His Data mining study incorporates themes from Bayesian inference, Principal component analysis, Probabilistic framework and Benchmark.
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