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Chai, Runqi; Tsourdos, Antonios; Savvaris, Al; Xia, Yuanqing; Chai, Senchun
IEEE transactions on industrial electronics (1982), 08/2020, Letnik: 67, Številka: 8Journal Article
A two-step strategy is developed for real-time trajectory planning of a hypersonic vehicle (HV) in the reentry phase. The first step generates the optimal trajectory for the HV using a recently proposed fuzzy multiobjective transcription method. In the second step, the optimally generated trajectories are utilized to train a deep neural network (DNN), which is then acted as the optimal command generator in real time. A detailed simulation study is carried out to verify the effectiveness and real-time applicability of the proposed integrated design. The DNN-driven controller is further compared against other optimization-based techniques existing in relative works. Moreover, extension works on the real-time trajectory planning of a six-degree-of-freedom HV model are performed. The results confirm the feasibility and reliability of applying the proposed method for the planning of the HV entry flight path in real time.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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