Iván Salgado

752 total citations
55 papers, 550 citations indexed

About

Iván Salgado is a scholar working on Control and Systems Engineering, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Iván Salgado has authored 55 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Control and Systems Engineering, 16 papers in Biomedical Engineering and 10 papers in Artificial Intelligence. Recurrent topics in Iván Salgado's work include Adaptive Control of Nonlinear Systems (26 papers), Advanced Control Systems Optimization (11 papers) and Prosthetics and Rehabilitation Robotics (10 papers). Iván Salgado is often cited by papers focused on Adaptive Control of Nonlinear Systems (26 papers), Advanced Control Systems Optimization (11 papers) and Prosthetics and Rehabilitation Robotics (10 papers). Iván Salgado collaborates with scholars based in Mexico, United Kingdom and India. Iván Salgado's co-authors include Isaac Chaírez, Oscar Camacho-Nieto, Hafiz Ahmed, Leonid Fridman, David Cruz‐Ortiz, B. Bandyopadhyay, Sid-Ali Amamra, Shyam Kamal, Manuel Mera and Cornelio Yáñez-Márquéz and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Access.

In The Last Decade

Iván Salgado

53 papers receiving 538 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Iván Salgado Mexico 15 371 121 110 58 54 55 550
Ulrich Konigorski Germany 10 190 0.5× 81 0.7× 88 0.8× 55 0.9× 36 0.7× 110 403
Cao Van Kien Vietnam 13 210 0.6× 113 0.9× 88 0.8× 64 1.1× 12 0.2× 40 418
Richa Sharma India 13 442 1.2× 93 0.8× 101 0.9× 62 1.1× 28 0.5× 20 673
Charles Fallaha Canada 6 431 1.2× 71 0.6× 134 1.2× 150 2.6× 20 0.4× 14 535
Mustafa Şinasi Ayas Türkiye 15 418 1.1× 122 1.0× 242 2.2× 70 1.2× 16 0.3× 51 638
Mahmood Mazare Iran 16 356 1.0× 112 0.9× 94 0.9× 79 1.4× 78 1.4× 32 517
Serhat Obuz United States 11 373 1.0× 76 0.6× 138 1.3× 41 0.7× 107 2.0× 23 527
Shuo Ding China 11 100 0.3× 227 1.9× 48 0.4× 76 1.3× 60 1.1× 36 461
Bing Chu United Kingdom 21 902 2.4× 294 2.4× 319 2.9× 415 7.2× 44 0.8× 120 1.3k
Mukul Kumar Gupta India 10 70 0.2× 49 0.4× 79 0.7× 28 0.5× 36 0.7× 29 272

Countries citing papers authored by Iván Salgado

Since Specialization
Citations

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

Fields of papers citing papers by Iván Salgado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iván Salgado

This figure shows the co-authorship network connecting the top 25 collaborators of Iván Salgado. A scholar is included among the top collaborators of Iván Salgado 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 Iván Salgado. Iván Salgado 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.
Villarreal-Cervantes, Miguel Gabriel, et al.. (2024). Desarrollo y análisis de la integración de la dinámica del motor en el modelo de un actuador elástico en serie con detección de fuerza de reacción.. PÄDI Boletín Científico de Ciencias Básicas e Ingenierías del ICBI. 12. 128–137. 1 indexed citations
2.
Gasparini, Francesca, et al.. (2024). Multiclass classifiers for hand-gesture recognition of electromyographic signals from WyoFlex Band. BOA (University of Milano-Bicocca). 134–139. 1 indexed citations
3.
Salgado, Iván, et al.. (2023). Forearm sEMG data from young healthy humans during the execution of hand movements. Scientific Data. 10(1). 310–310. 4 indexed citations
4.
5.
Salgado, Iván, et al.. (2022). Stable learning laws design for long short-term memory identifier for uncertain discrete systems via control Lyapunov functions. Neurocomputing. 491. 144–159. 2 indexed citations
6.
Cruz‐Ortiz, David, et al.. (2022). Home-care nursing controlled mobile robot with vital signal monitoring. Medical & Biological Engineering & Computing. 61(2). 399–420. 11 indexed citations
7.
Cruz‐Ortiz, David, et al.. (2022). First-order sliding mode control for second order systems with asymmetric constraints. 227–232. 1 indexed citations
8.
Ahmed, Hafiz, Iván Salgado, Isaac Chaírez, & Mohamed Benbouzid. (2020). Robust Gradient Estimator for Unknown Frequency Estimation in Noisy Environment: Application to Grid-Synchronization. IEEE Access. 8. 70693–70702. 14 indexed citations
9.
Rodríguez, Julia L., et al.. (2020). Enhanced Naproxen Elimination in Water by Catalytic Ozonation Based on NiO Films. Catalysts. 10(8). 884–884. 8 indexed citations
10.
Salgado, Iván, et al.. (2020). Adaptive sliding-mode controller of a lower limb mobile exoskeleton for active rehabilitation. ISA Transactions. 109. 218–228. 37 indexed citations
11.
Salgado, Iván, et al.. (2020). Hybrid State Constraint Adaptive Disturbance Rejection Controller for a Mobile Worm Bio-Inspired Robot. Mathematical and Computational Applications. 25(1). 13–13. 12 indexed citations
12.
Cruz‐Ortiz, David, et al.. (2020). Terminal Sliding-Mode Control of Virtual Humanoid Robot with Joint Restrictions Walking on stepping objects. Cybernetics & Systems. 51(4). 402–425. 5 indexed citations
13.
Salgado, Iván, et al.. (2020). Differential neural network identifier with composite learning laws for uncertain nonlinear systems. IFAC-PapersOnLine. 53(2). 7897–7902. 2 indexed citations
14.
Cruz‐Ortiz, David, et al.. (2019). Hybrid position/force output feedback second-order sliding mode control for a prototype of an active orthosis used in back-assisted mobilization. Medical & Biological Engineering & Computing. 57(9). 1843–1860. 8 indexed citations
15.
Ahmed, Hafiz, Iván Salgado, & Héctor Ríos. (2018). Robust synchronization of master-slave chaotic systems using approximate model: An experimental study. ISA Transactions. 73. 141–146. 17 indexed citations
16.
Salgado, Iván, Manuel Mera, & Isaac Chaírez. (2017). Quasi-minimal active disturbance rejection control of MIMO perturbed linear systems based on differential neural networks and the attractive ellipsoid method. ISA Transactions. 71(Pt 2). 304–316. 2 indexed citations
17.
Salgado, Iván, Shyam Kamal, B. Bandyopadhyay, Isaac Chaírez, & Leonid Fridman. (2016). Control of discrete time systems based on recurrent Super-Twisting-like algorithm. ISA Transactions. 64. 47–55. 40 indexed citations
18.
Salgado, Iván, David Cruz‐Ortiz, Oscar Camacho-Nieto, & Isaac Chaírez. (2016). Output feedback control of a skid-steered mobile robot based on the super-twisting algorithm. Control Engineering Practice. 58. 193–203. 27 indexed citations
19.
Salgado, Iván, Isaac Chaírez, Oscar Camacho-Nieto, & Cornelio Yáñez-Márquéz. (2014). Super-twisting sliding mode differentiation for improving PD controllers performance of second order systems. ISA Transactions. 53(4). 1096–1106. 27 indexed citations
20.
Salgado, Iván & Isaac Chaírez. (2009). Discrete time recurrent neural network observer. 2764–2770. 8 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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