7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; Followed by 2nd TEOS 2007
DOI: 10.2514/6.2007-7880
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Optimization of Airship Routes for Weather

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Cited by 7 publications
(3 citation statements)
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“…Solar powered airships [38][39][40][41], renewable energies powered airships [42][43][44], hydrogen powered airships [45], high altitude wind power generation with airships [46], solar turbine power stations with floating solar chimneys [47], energy storage alternatives for airships with regenerative fuel cell (RFC) [48,49], and the effect of high altitude on its energy system performance [50] have all received attention. Other studies have looked at the optimum airship routes to lower fuel usage, assuming already chosen destinations [37,51].…”
Section: Introductionmentioning
confidence: 99%
“…Solar powered airships [38][39][40][41], renewable energies powered airships [42][43][44], hydrogen powered airships [45], high altitude wind power generation with airships [46], solar turbine power stations with floating solar chimneys [47], energy storage alternatives for airships with regenerative fuel cell (RFC) [48,49], and the effect of high altitude on its energy system performance [50] have all received attention. Other studies have looked at the optimum airship routes to lower fuel usage, assuming already chosen destinations [37,51].…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, connections that create an angle greater than the critical turning or pitching angles of the UAV described in Section 3 were also omitted. The field strengths for obstacles are computed using (15) to (17). The field strengths for time and energy consumption are computed on demand as they depend on the nodal approach direction, wind conditions and other flight characteristics.…”
Section: Trajectory Planning and Test Setupmentioning
confidence: 99%
“…In this work, the wind was added as a disturbance, and the dynamic constraints were not taken into account. Al-Sabban et al presented a Markov decision process-based fixed-wing UAV path planner that exploits wind energy to minimize energy consumption in an uncertain and time-varying wind field [17]. The simulation results showed almost 30% energy savings compared to a straight line path, but this was only conducted for one WVF sample.…”
Section: Introductionmentioning
confidence: 99%