Miguel A. Llama
- Control and Systems Engineering top 2%
- Artificial Intelligence top 10%
- Mechanical Engineering
- Aerospace Engineering
- Computer Networks and Communications top 10%
- Co-authors
- Víctor SantibáñezRafael KellyRogelio SotoAlejandro DzulHéctor RíosLeonid FridmanEdgar N. SánchezJ. Linares‐Flores
- Topics
- Adaptive Control of Nonlinear Systems (31 papers)Control and Dynamics of Mobile Robots (12 papers)Fuzzy Logic and Control Systems (9 papers)
- Cited by
- Control and Systems EngineeringArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Automatic ControlIEEE Transactions on Industrial ElectronicsIEEE Access
- Partner nations
- Mexico
In The Last Decade
Miguel A. Llama
36 papers receiving 557 citations
Peers
Comparison fields: 5 of 58
- Control and Systems Engineering 502
- Artificial Intelligence 119
- Mechanical Engineering 85
- Aerospace Engineering 69
- Computer Networks and Communications 65
Countries citing papers authored by Miguel A. Llama
This map shows the geographic impact of Miguel A. Llama'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 Miguel A. Llama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel A. Llama more than expected).
Fields of papers citing papers by Miguel A. Llama
This network shows the impact of papers produced by Miguel A. Llama. 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 Miguel A. Llama. The network helps show where Miguel A. Llama may publish in the future.
Co-authorship network of co-authors of Miguel A. Llama
This figure shows the co-authorship network connecting the top 25 collaborators of Miguel A. Llama. A scholar is included among the top collaborators of Miguel A. Llama 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 Miguel A. Llama. Miguel A. Llama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 38 | |
| 5 | 16 | |
| 6 | 22 | |
| 7 | 3 | |
| 8 | 31 | |
| 9 | 6 | |
| 10 | 4 | |
| 11 | 26 | |
| 12 | Variable gains PD tracking control of robot manipulators: Stability analysis and simulations | 3 |
| 13 | 137 | |
| 14 | 5 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 22 | |
| 18 | 7 | |
| 19 | 3 | |
| 20 | 65 |
About Miguel A. Llama
Miguel A. Llama is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Networks and Communications, having authored 39 papers that have together received 589 indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (31 papers), Control and Dynamics of Mobile Robots (12 papers) and Fuzzy Logic and Control Systems (9 papers). The work is most often cited by research in Control and Systems Engineering (502 citations), Artificial Intelligence (119 citations) and Computer Vision and Pattern Recognition (60 citations). Miguel A. Llama has collaborated with scholars based in Mexico. Frequent co-authors include Víctor Santibáñez, Rafael Kelly, Rogelio Soto, Alejandro Dzul, Héctor Ríos, Leonid Fridman, Edgar N. Sánchez, J. Linares‐Flores, María Assunção Flores and Eduardo Bayro–Corrochano. Their work appears in journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics and IEEE Access.
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.