Paolo Rapisarda

3.2k total citations · 1 hit paper
121 papers, 2.0k citations indexed

About

Paolo Rapisarda is a scholar working on Control and Systems Engineering, Statistical and Nonlinear Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Paolo Rapisarda has authored 121 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Control and Systems Engineering, 27 papers in Statistical and Nonlinear Physics and 26 papers in Electrical and Electronic Engineering. Recurrent topics in Paolo Rapisarda's work include Control Systems and Identification (38 papers), Advanced Control Systems Optimization (29 papers) and Fault Detection and Control Systems (28 papers). Paolo Rapisarda is often cited by papers focused on Control Systems and Identification (38 papers), Advanced Control Systems Optimization (29 papers) and Fault Detection and Control Systems (28 papers). Paolo Rapisarda collaborates with scholars based in United Kingdom, Netherlands and Japan. Paolo Rapisarda's co-authors include Ivan Markovsky, Jan C. Willems, Harry L. Trentelman, Jonathan C. Mayo‐Maldonado, P. L. Lewin, Arjan van der Schaft, Thabiso Maupong, Paula Rocha, M. Kanat Camlibel and Diego Napp and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and IEEE Transactions on Industrial Electronics.

In The Last Decade

Paolo Rapisarda

110 papers receiving 1.9k citations

Hit Papers

A note on persistency of excitation 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paolo Rapisarda United Kingdom 19 1.6k 325 248 178 169 121 2.0k
Andreas Rauh Germany 15 955 0.6× 243 0.7× 145 0.6× 332 1.9× 103 0.6× 207 1.3k
H. G. Bock Germany 16 1.2k 0.7× 122 0.4× 147 0.6× 114 0.6× 44 0.3× 50 1.7k
Eduardo Cerpa Chile 17 1.2k 0.7× 109 0.3× 215 0.9× 405 2.3× 24 0.1× 42 1.6k
Yiheng Wei China 33 1.9k 1.2× 260 0.8× 309 1.2× 88 0.5× 79 0.5× 156 2.7k
Tomomichi Hagiwara Japan 23 2.1k 1.3× 88 0.3× 292 1.2× 395 2.2× 14 0.1× 235 2.4k
Michael P. Polis United States 18 896 0.6× 431 1.3× 87 0.4× 462 2.6× 14 0.1× 66 1.5k
Matthew C. Turner United Kingdom 23 2.3k 1.5× 369 1.1× 74 0.3× 115 0.6× 11 0.1× 150 2.6k
Guido Maione Italy 20 707 0.4× 162 0.5× 72 0.3× 120 0.7× 29 0.2× 105 1.2k
Lorenzo Ntogramatzidis Australia 17 756 0.5× 139 0.4× 115 0.5× 142 0.8× 17 0.1× 104 1.0k
William P. Heath United Kingdom 22 1.3k 0.8× 108 0.3× 123 0.5× 108 0.6× 9 0.1× 145 1.6k

Countries citing papers authored by Paolo Rapisarda

Since Specialization
Citations

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

Fields of papers citing papers by Paolo Rapisarda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paolo Rapisarda

This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Rapisarda. A scholar is included among the top collaborators of Paolo Rapisarda 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 Paolo Rapisarda. Paolo Rapisarda 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.
Camlibel, M. Kanat, Henk J. van Waarde, & Paolo Rapisarda. (2025). The shortest experiment for linear system identification. Systems & Control Letters. 197. 106045–106045.
2.
Faulwasser, Timm, et al.. (2024). A continuous-time fundamental lemma and its application in data-driven optimal control. Systems & Control Letters. 194. 105950–105950. 2 indexed citations
3.
Ohta, Yoshito & Paolo Rapisarda. (2024). A sampling linear functional framework for data-driven analysis and control of continuous-time systems. 357–362. 3 indexed citations
4.
Chu, Bing, et al.. (2024). Data-Driven Model Predictive Control for Continuous-Time Systems. ePrints Soton (University of Southampton). 369–374.
5.
Rapisarda, Paolo, Henk J. van Waarde, & M. Kanat Camlibel. (2023). Data-driven simulation of continuous-time linear time-invariant systems: the autonomous case. IFAC-PapersOnLine. 56(2). 2244–2249. 1 indexed citations
6.
Rapisarda, Paolo, Henk J. van Waarde, & M. Kanat Camlibel. (2023). Orthogonal Polynomial Bases for Data-Driven Analysis and Control of Continuous-Time Systems. IEEE Transactions on Automatic Control. 69(7). 4307–4319. 12 indexed citations
7.
Rapisarda, Paolo, Henk J. van Waarde, & M. Kanat Camlibel. (2023). A “Fundamental Lemma” for Continuous-Time Systems, with Applications to Data-Driven Simulation. SSRN Electronic Journal. 1 indexed citations
8.
Rapisarda, Paolo, et al.. (2023). Informativity for Identification for $2D$ State-Representable Autonomous Systems, with Applications to Data-Driven Simulation. ePrints Soton (University of Southampton). 584–589. 2 indexed citations
9.
Waarde, Henk J. van, M. Kanat Camlibel, Paolo Rapisarda, & Harry L. Trentelman. (2022). Data-Driven Dissipativity Analysis: Application of the Matrix S-Lemma. IEEE Control Systems. 42(3). 140–149. 30 indexed citations
10.
Rapisarda, Paolo & Yoshito Ohta. (2018). System transformation induced by generalized orthonormal basis functions preserves dissipativity. ePrints Soton (University of Southampton). 1 indexed citations
11.
Maupong, Thabiso, Jonathan C. Mayo‐Maldonado, & Paolo Rapisarda. (2017). On Lyapunov functions and data-driven dissipativity. IFAC-PapersOnLine. 50(1). 7783–7788. 29 indexed citations
12.
Mayo‐Maldonado, Jonathan C. & Paolo Rapisarda. (2015). A systematic approach to constant power load stabilization by passive damping. 1346–1351. 5 indexed citations
13.
Rahman, M. S. Abd, Paolo Rapisarda, & P. L. Lewin. (2014). The use of three dimensional filters for on-line partial discharge localisation in large transformers. 10–14. 5 indexed citations
14.
Maleki, Sepehr, Paolo Rapisarda, Lorenzo Ntogramatzidis, & Eric Rogers. (2013). A Geometric Approach to 3D Fault Identification. ePrints Soton (University of Southampton). 1–6. 5 indexed citations
15.
Napp, Diego, Paolo Rapisarda, & Paula Rocha. (2011). Time-relevant 2D behaviors. cas 32. 1–5. 2 indexed citations
16.
Kojima, Chiaki, Paolo Rapisarda, & Kiyofumi Takaba. (2010). Lyapunov stability analysis of higher-order 2-D systems. Multidimensional Systems and Signal Processing. 22(4). 287–302. 23 indexed citations
17.
Fuhrmann, Paul A., Paolo Rapisarda, & Yutaka Yamamoto. (2007). On the state of behaviors. Linear Algebra and its Applications. 424(2-3). 570–614. 17 indexed citations
18.
Rapisarda, Paolo & Harry L. Trentelman. (2004). Linear Hamiltonian Behaviors and Bilinear Differential Forms. SIAM Journal on Control and Optimization. 43(3). 769–791. 11 indexed citations
19.
Rapisarda, Paolo & Jan C. Willems. (2002). The subspace Nevalinna interpolation problem and the most powerful unfalsified model. 3. 2029–2033. 1 indexed citations
20.
Peeters, Ralf & Paolo Rapisarda. (2000). A new algorithm to solve the polynomial Lyapunov equation. 3 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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