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Algorithm of the PbGA search for the optimal PbF.
| العنوان: | Algorithm of the PbGA search for the optimal PbF. |
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| المؤلفون: | Larasmoyo Nugroho, Rika Andiarti, Rini Akmeliawati, Sastra Kusuma Wijaya |
| سنة النشر: | 2024 |
| مصطلحات موضوعية: | Biochemistry, Biotechnology, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, versatiledeep reinforcement learning, hydestoc hybrid deterministic, established deterministic controller, consistently falls short, reusable launch vehicle, improving genetic algorithm, landing distance accuracy, miss distance, landing speed, landing guidance, |
| الوصف: | The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. However, when compared to an established deterministic controller, it consistently falls short in terms of landing distance accuracy. To address this issue, the HYDESTOC Hybrid Deterministic-Stochastic (a combination of DDPG/deep deterministic policy gradient and PID/proportional-integral-derivative) algorithm was introduced to improve terminal distance accuracy while keeping propellant consumption low. Results from extensive cross-validated Monte Carlo simulations show that a miss distance of less than 0.02 meters, landing speed of less than 0.4 m/s, settling time of 20 seconds or fewer, and a constant crash-free performance is achievable using this method. |
| نوع الوثيقة: | still image |
| اللغة: | unknown |
| Relation: | https://figshare.com/articles/figure/Algorithm_of_the_PbGA_search_for_the_optimal_PbF_/25318292 |
| DOI: | 10.1371/journal.pone.0292539.g010 |
| الاتاحة: | https://doi.org/10.1371/journal.pone.0292539.g010 https://figshare.com/articles/figure/Algorithm_of_the_PbGA_search_for_the_optimal_PbF_/25318292 |
| Rights: | CC BY 4.0 |
| رقم الانضمام: | edsbas.98F5F3BA |
| قاعدة البيانات: | BASE |
| DOI: | 10.1371/journal.pone.0292539.g010 |
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