scholarly journals An Optimal Explicit Guidance Algorithm for Terminal Descent Phase of Lunar Soft Landing

Author(s):  
Avijit Banerjee ◽  
Radhakant Padhi
2018 ◽  
Vol 51 (12) ◽  
pp. 6-11 ◽  
Author(s):  
Julio C. Sanchez ◽  
Francisco Gavilan ◽  
Rafael Vazquez

2014 ◽  
Vol 47 (1) ◽  
pp. 14-19 ◽  
Author(s):  
M.P. Rijesh ◽  
G. Sijo ◽  
N.K. Philip ◽  
P. Natarajan

2019 ◽  
Author(s):  
Quan-Hoang Vuong
Keyword(s):  

In search of a soft landing (Vietnam Investment Review; May 7, 2000)


2005 ◽  
Author(s):  
Velimir Anton Bole ◽  
Dusan Mramor
Keyword(s):  

2021 ◽  
Vol 11 (1) ◽  
pp. 410
Author(s):  
Yu-Hsien Lin ◽  
Yu-Ting Lin ◽  
Yen-Jun Chiu

On the basis of a full-appendage DARPA SUBOFF model (DTRC model 5470), a scale (λ = 0.535) semi-autonomous submarine free-running model (SFRM) was designed for testing its manoeuvrability and stability in the constrained water. Prior to the experimental tests of the SFRM, a six-degree-of-freedom (6-DOF) manoeuvre model with an autopilot system was developed by using logic operations in MATLAB. The SFRM’s attitude and its trim polygon were presented by coping with the changes in mass and trimming moment. By adopting a series of manoeuvring tests in empty tanks, the performances of the SFRM were introduced in cases of three sailing speeds. In addition, the PD controller was established by considering the simulation results of these manoeuvring tests. The optimal control gains with respect to each manoeuvring test can be calculated by using the PID tuner in MATLAB. Two sets of control gains derived from the optimal characteristics parameters were compared in order to decide on the most appropriate PD controller with the line-of-sight (LOS) guidance algorithm for the SFRM in the autopilot simulation. Eventually, the simulated trajectories and course angles of the SFRM would be illustrated in the post-processor based on the Cinema 4D modelling.


Author(s):  
Huatao Chen ◽  
Kun Zhao ◽  
Juan L.G. Guirao ◽  
Dengqing Cao

AbstractFor the entry guidance problem of hypersonic gliding vehicles (HGVs), an analytical predictor–corrector guidance method based on feedback control of bank angle is proposed. First, the relative functions between the velocity, bank angle and range-to-go are deduced, and then, the analytical relation is introduced into the predictor–corrector algorithm, which is used to replace the traditional method to predict the range-to-go via numerical integration. To eliminate the phugoid trajectory oscillation, a method for adding the aerodynamic load feedback into the control loop of the bank angle is proposed. According to the quasi-equilibrium gliding condition, the function of the quasi-equilibrium glide load along with the velocity variation is derived. For each guidance period, the deviation between the real-time load and the quasi-equilibrium gliding load is revised to obtain a smooth reentry trajectory. The simulation results indicate that the guidance algorithm can adapt to the mission requirements of different downranges, and it also has the ability to guide the vehicle to carry out a large range of lateral maneuvers. The feedback control law of the bank angle effectively eliminates the phugoid trajectory oscillation and guides the vehicle to complete a smooth reentry flight. The Monte Carlo test indicated that the guidance precision and robustness are good.


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