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Human Memory/Learning Inspired Approach for Attitude Control of Crew Exploration Vehicles (CEVs)
By: Song, Y.D.; Zhang, M.J.; Ran Zhang; WenChuan Cai; Bin Li; Liguo Weng;
2007 / IEEE / 1-4244-0988-8
Description
This item was taken from the IEEE Conference ' Human Memory/Learning Inspired Approach for Attitude Control of Crew Exploration Vehicles (CEVs) ' This paper addresses the problem of attitude control of Crew Exploration Vehicle (CEV). Unlike traditional spacecraft with surface deflections for attitude control, CEV uses RCS jet engines for attitude adjustment, which calls for control algorithms for firing the small propulsion engines mounted in the vehicle. In this work, by combining both actuation and attitude dynamics, we develop a strategy to control the vehicle attitude via adjusting reaction control system (RCS) throttle angles. Since the resultant (combined) dynamics of the vehicle are highly nonlinear and coupled with significant uncertainties, we explore a control approach based on human memory and learning mechanism, which does not reply on precise system information dynamics. Furthermore, the overall control scheme has simple structure and demands much less computation as compared with most existing methods, making it attractive for real-time implementation. The effectiveness of this approach is also verified via simulation.
Related Topics
Vehicle Attitude Control
Crew Exploration Vehicle
Spacecraft
Reaction Control System Jet Engine
Propulsion Engine
Attitude Dynamics
Actuation Dynamics
Uncertain System
Human Memory
Humans
Attitude Control
Nonlinear Dynamical Systems
Vehicle Dynamics
Control Systems
Space Vehicles
Jet Engines
Propulsion
Couplings
Uncertainty
Learning Mechanism
Uncertain Systems
Space Vehicles
Nonlinear Control Systems
Attitude Control
Vehicle Dynamics
Engineering
Surface Deflection