Ridong Zhang

1.4k total citations
51 papers, 1.1k citations indexed

About

Ridong Zhang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Automotive Engineering. According to data from OpenAlex, Ridong Zhang has authored 51 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Control and Systems Engineering, 8 papers in Mechanical Engineering and 6 papers in Automotive Engineering. Recurrent topics in Ridong Zhang's work include Fault Detection and Control Systems (24 papers), Advanced Control Systems Optimization (17 papers) and Iterative Learning Control Systems (13 papers). Ridong Zhang is often cited by papers focused on Fault Detection and Control Systems (24 papers), Advanced Control Systems Optimization (17 papers) and Iterative Learning Control Systems (13 papers). Ridong Zhang collaborates with scholars based in China, Hong Kong and United States. Ridong Zhang's co-authors include Furong Gao, Jili Tao, Renquan Lu, Huiyu Zhou, Sheng Wu, Yong Xu, Junfeng Zhang, Anke Xue, Nan Wang and Xudong Zhao and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics and Fuel.

In The Last Decade

Ridong Zhang

49 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ridong Zhang China 17 751 230 213 142 121 51 1.1k
Horst Schulte Germany 17 661 0.9× 395 1.7× 82 0.4× 183 1.3× 61 0.5× 108 966
Martin Herceg Slovakia 10 883 1.2× 197 0.9× 131 0.6× 91 0.6× 56 0.5× 18 1.1k
Yufang Chang China 17 501 0.7× 189 0.8× 94 0.4× 174 1.2× 212 1.8× 61 929
Qudrat Khan Pakistan 18 735 1.0× 356 1.5× 61 0.3× 149 1.0× 105 0.9× 78 1.1k
Torsten Knohl Germany 9 939 1.3× 471 2.0× 107 0.5× 230 1.6× 82 0.7× 12 1.3k
Huifang Kong China 13 568 0.8× 212 0.9× 391 1.8× 258 1.8× 30 0.2× 47 852
Xiaoyuan Zhu China 18 629 0.8× 227 1.0× 560 2.6× 296 2.1× 86 0.7× 58 1.1k
Marcin Cychowski Ireland 12 794 1.1× 252 1.1× 75 0.4× 241 1.7× 81 0.7× 38 1.1k
Wensheng Luo China 17 1.0k 1.4× 708 3.1× 163 0.8× 71 0.5× 269 2.2× 41 1.3k
Elisabetta Punta Italy 16 1.1k 1.5× 133 0.6× 119 0.6× 191 1.3× 70 0.6× 73 1.3k

Countries citing papers authored by Ridong Zhang

Since Specialization
Citations

This map shows the geographic impact of Ridong Zhang'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 Ridong Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ridong Zhang more than expected).

Fields of papers citing papers by Ridong Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ridong Zhang. 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 Ridong Zhang. The network helps show where Ridong Zhang may publish in the future.

Co-authorship network of co-authors of Ridong Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Ridong Zhang. A scholar is included among the top collaborators of Ridong Zhang 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 Ridong Zhang. Ridong Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Youqiang, Ridong Zhang, & Furong Gao. (2025). Multi-scale residual attention networks with spatio-temporal attention co-optimization for industrial fault diagnosis. Computers & Chemical Engineering. 205. 109482–109482. 5 indexed citations
2.
Chen, Youqiang, Yue Zhao, Ridong Zhang, & Furong Gao. (2025). A branch selective kernel network based on slow features with interpretability for fault detection and diagnosis in chemical processes. Process Safety and Environmental Protection. 204. 108118–108118. 1 indexed citations
3.
Chen, Youqiang & Ridong Zhang. (2025). Deep Multiscale Convolutional Model With Multihead Self-Attention for Industrial Process Fault Diagnosis. IEEE Transactions on Systems Man and Cybernetics Systems. 55(4). 2503–2512. 10 indexed citations
4.
Zhang, Ridong, et al.. (2025). New design of two-dimensional model predictive iterative learning control with novel error compensation for batch processes. Journal of Process Control. 157. 103592–103592. 1 indexed citations
5.
Chen, Youqiang, Ridong Zhang, & Furong Gao. (2024). Fault diagnosis of industrial process using attention mechanism with 3DCNN-LSTM. Chemical Engineering Science. 293. 120059–120059. 14 indexed citations
6.
Wang, Lei, et al.. (2024). Non-excitation closed-loop identification based on hysteresis bias relay feedback. Computers & Chemical Engineering. 188. 108776–108776. 2 indexed citations
7.
Chen, Youqiang, et al.. (2024). Deep network model fusion of wide kernel feature learning for industrial process modeling and fault diagnosis. Process Safety and Environmental Protection. 194. 1283–1302. 5 indexed citations
8.
Wang, Limin, et al.. (2024). Two-dimensional reinforcement learning model-free fault-tolerant control for batch processes against multi- faults. Computers & Chemical Engineering. 192. 108883–108883. 6 indexed citations
9.
Zhang, Ridong, et al.. (2024). Industrial process fault diagnosis using dilated convolutional stacking bidirectional gated recurrent unit with high and low-order feature fusion. Chemical Engineering Science. 305. 121164–121164. 9 indexed citations
10.
Zhang, Ridong, et al.. (2024). Design of model fusion learning method based on deep bidirectional GRU neural network in fault diagnosis of industrial processes. Chemical Engineering Science. 302. 120884–120884. 13 indexed citations
11.
Wang, Limin, Jingxian Yu, Ping Li, Haisheng Li, & Ridong Zhang. (2020). A 2D-FM model-based robust iterative learning model predictive control for batch processes. ISA Transactions. 110. 271–282. 26 indexed citations
12.
13.
Zhang, Ridong & Furong Gao. (2018). Two-Dimensional Iterative Learning Model Predictive Control for Batch Processes: A New State Space Model Compensation Approach. IEEE Transactions on Systems Man and Cybernetics Systems. 51(2). 833–841. 31 indexed citations
14.
Zhang, Ridong, Anke Xue, & Furong Gao. (2018). Model Predictive Control: Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2 indexed citations
15.
Zhang, Ridong, Anke Xue, & Furong Gao. (2018). Model Predictive Control. 19 indexed citations
16.
Zhang, Junfeng, Xudong Zhao, Ridong Zhang, & Yun Chen. (2017). Improved Controller Design for Uncertain Positive Systems and its Extension to Uncertain Positive Switched Systems. Asian Journal of Control. 20(1). 159–173. 16 indexed citations
17.
Tao, Jili, et al.. (2017). Improved GA based FC-UC hybrid power management considering prolong lifetime. 4150–4155. 1 indexed citations
18.
Wang, Xinguang, Jili Tao, & Ridong Zhang. (2016). Fuzzy energy management control for battery/ultra-capacitor hybrid electric vehicles. 6207–6211. 7 indexed citations
19.
Zhang, Junfeng, Xudong Zhao, Ridong Zhang, & Shaosheng Zhou. (2016). Dual approach to stability and stabilisation of uncertain switched positive systems. International Journal of Systems Science. 48(4). 873–884. 11 indexed citations
20.
Zhang, Junfeng, Xudong Zhao, & Ridong Zhang. (2016). An improved approach to controller design of positive systems using controller gain decomposition. Journal of the Franklin Institute. 354(3). 1356–1373. 34 indexed citations

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.

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