14 citations as recorded by crossref.

1. Non-invasive chaos control based on 2-contraction stabilizability D. Angeli et al. https://doi.org/10.1016/j.automatica.2025.112778
2. Is the brain uncontrollable, like the weather? N. Rust https://doi.org/10.53053/RFPZ2797
3. Reducing manipulations in a control simulation experiment based on instability vectors with the Lorenz-63 model M. Ouyang et al. https://doi.org/10.5194/npg-30-183-2023
4. Ensemble-based model predictive control using data assimilation techniques K. Kurosawa et al. https://doi.org/10.5194/npg-32-293-2025
5. Ensemble Kalman Filter Meets Model Predictive Control in Chaotic Systems Y. Sawada https://doi.org/10.2151/sola.2024-053
6. Chaos suppression through Chaos enhancement L. Li et al. https://doi.org/10.1007/s11071-024-10426-z
7. Control simulation experiments of extreme events with the Lorenz-96 model Q. Sun et al. https://doi.org/10.5194/npg-30-117-2023
8. Bottom–up approach for mitigating extreme events with limited intervention options: a case study with Lorenz 96 model T. Mitsui et al. https://doi.org/10.5194/npg-32-457-2025
9. Pseudo-Lorenz attractors in echo state networks T. Kabayama et al. https://doi.org/10.1007/s13160-025-00740-3
10. A duality principle for chaotic systems: from data assimilation to efficient control T. Miyoshi https://doi.org/10.1007/s11071-025-12021-2
11. Convex Optimization of Initial Perturbations toward Quantitative Weather Control T. Ohtsuka et al. https://doi.org/10.2151/sola.2025-020
12. Leading the Lorenz 63 system toward the prescribed regime by model predictive control coupled with data assimilation F. Kawasaki & S. Kotsuki https://doi.org/10.5194/npg-31-319-2024
13. Towards Analyzable Design Paradigms for Chaos-Based Cryptographic Primitives A. Abba et al. https://doi.org/10.3390/jcp5030064
14. Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control R. Nagai et al. https://doi.org/10.5194/npg-32-281-2025