Sun Jian-guo
About
In The Last Decade
Sun Jian-guo
47 papers receiving 323 citations
Peers
Comparison fields: 5 of 58
- Control and Systems Engineering 149
- Artificial Intelligence 107
- Computer Vision and Pattern Recognition 85
- Computational Mechanics 54
- Aerospace Engineering 53
Countries citing papers authored by Sun Jian-guo
This map shows the geographic impact of Sun Jian-guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sun Jian-guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sun Jian-guo more than expected).
Fields of papers citing papers by Sun Jian-guo
This network shows the impact of papers produced by Sun Jian-guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sun Jian-guo. The network helps show where Sun Jian-guo may publish in the future.
Co-authorship network of co-authors of Sun Jian-guo
This figure shows the co-authorship network connecting the top 25 collaborators of Sun Jian-guo. A scholar is included among the top collaborators of Sun Jian-guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sun Jian-guo. Sun Jian-guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Design of an Active Disturbance Rejection Decoupling Multivariable Control Scheme for Aero-Engine | 1 |
| 2 | Performance seeking control of turbo shaft engine with variable inlet guide vanes | 1 |
| 3 | Subsystem disturbance rejection control of turbo-shaft engine/helicopter based on cascade ADRC | 1 |
| 4 | Aero-engine high stability control scheme design based on angle of attack predictive model | 2 |
| 5 | Application of active disturbance rejection control method in aeroengines afterburning transition state control | 1 |
| 6 | Design and application of a disturbance rejection rotor speed control method for turbo-shaft engines | 1 |
| 7 | Application of PSO-based rough set theory and neural network to aeroengine fault diagnosis | 2 |
| 8 | Adaptive model of rotor/turbo-shaft engine | 3 |
| 9 | Improved pruning algorithms for sparse least squares support vector regression machine | 0 |
| 10 | Multi-objective optimization of aeroengine PID control based on multi-objective genetic algorithms | 1 |
| 11 | Fault diagnosis for gas turbine engines based on Kalman filter and neural networks | 1 |
| 12 | Aeroengine direct thrust control based on neural network inverse control | 6 |
| 13 | Investigation of state feedback control based on internal model principle for an turbo-shaft Engine | 1 |
| 14 | Application of adaptive genetic neural network algorithm in design of thrust estimator | 3 |
| 15 | Study on wireless data transmission of data acquisition for the rotary joint | 1 |
| 16 | Aeroengine Gas Path Fault Diagnosis Using Rough Sets and Neural Networks | 4 |
| 17 | Experimental Verification of H_(∞)/LTR Method for Aeroengine Control Systems | 5 |
| 18 | Aero-Engine Performance Seeking Control Based on Sequential Quadratic Programming Algorithm | 3 |
| 19 | A Survey of Gas Turbine Control Technique | 2 |
| 20 | Direct Control of Aeroengine Thrust Based on Correlation Analysis and Neural Networks | 5 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.