Abstract:

This paper introduces a new technique to control spacecraft maneuvers. The new technique is based upon using neuro-fuzzy approach to predict the required control torque, using a modelless-strategy, for attitude and rate tracking subjected to torque constraints. The Neuro-Fuzzy Controller (NFC) is built up using the Adaptive Neuro-Fuzzy Inference System (ANFIS) which transforms a fuzzy controller into an adaptive network to take the advantage of all the neural network control techniques proposed in the literature. First, the inverse dynamics of the spacecraft is developed by training the ANFIS with specified states such as Euler angles and the angular velocities. These data can be collected via direct measurements, estimators, or simulation using attitude propagators. Second, three types of controllers are developed, started with a Single Level NFC (SLNFC) to a Multi Level NFC (MLNFC) and ended by a Hybrid Controller. The configuration of the first and second controllers depends on the structure of the data used in the training phase. While, the hybrid controller utilizesthe NFC in general to solve the problem of large angles attitude tracking in the absence of the system model and brings the system to a steady state with relatively small errors then, it switches to either a classical or a modern controller to refine the steady state errors. Finally, each one of them is tested against two different controllers belonging to classical and modern control approaches for the purpose of performance evaluation. The first one is a classical PD controller using quaternion feedback, and the other is a Non-Linear Predictive controller (NLP) which is developed to predict the required control action to track a certain trajectory under rate and torque constraints. The developed controllers have shown a competitive performance to that of classical one and the simulation results give neuro-fuzzy control approach an edge over the modern control approaches specially when considering the hard constraint of a modelless spacecraft.                                                                                                                                                   

Keywords: Neuro-Fuzzy Modeling, Neuro-Fuzzy Control,Nonlinear Control, Tracking Control, Spacecraft.

(Full Paper, 440 KB)

Biographies:

Mohammad Abdelrahman, born in 1970, graduated in Cairo University, Faculty of Engineering, Aerospace Department in 1992. He received from the same department M.Sc. degree in 1998 and Ph.D. degree in 2002. During 1995-2000 he worked as a teaching assistant and associate lecturer of automatic control at October 6thUniversity, Faculty of Engineering, Mechatronics Department.  Since 2000, he has been working as a researcher at the National Authority for Remote Sensing and Space Science (NARSS), Space Sciences Division. Dr. Abdelrahman participated in the Egyptian Space Program and BayernSat project at TUM, Germany as an ADCS specialist. Also, he was a PI and Co-PI for many research projects sponsored by NARSS.His current research interests include, spacecraft attitude and orbit determination and control, estimation theory, Optimization, non-linear control, neuro-fuzzy modeling and control, GPS/INS integration based systems.

BibTex:

(Full Paper, 440 KB)