Geno-fuzzy control in autonomous servicing of a space station

Abstract The provision of spacecraft servicing to a space station comprises the tasks of assembly, resupply, repair and maintenance of manufactured space parts in-orbit. Servicing tasks use rendezvous and docking operations to accomplish their objectives. Autonomous servicing relies on intelligent fly control systems to perform fast, soft, and precise docking operations. This paper proposes the use of a fuzzy logic control system, mounted on an active chaser vehicle which wants to dock with a big passive space station in orbit around the Earth. The geno-fuzzy controller is a knowledge-based controller that performs the closed-loop operations autonomously. It produces smooth control actions in the proximity of the target and during the docking, to avoid disturbance torques in the final assembly orbit. The use of a genetic algorithm tool to optimise the controller so as to reduce docking time and fuel consumption is analyzed. It performs the optimization by finding the best fuzzy sets of the controller membership functions, and the most suitable rule data base.

[1]  Charles L. Karr,et al.  Genetic-algorithm-based fuzzy control of spacecraft autonomous rendezvous , 1997 .

[2]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[3]  Francisco Herrera,et al.  Tuning fuzzy logic controllers by genetic algorithms , 1995, Int. J. Approx. Reason..

[4]  I. Turksen.  Measurement of membership functions and their acquisition , 1991 .

[5]  E. H. Mamdani,et al.  Twenty years of fuzzy control: experiences gained and lessons learnt , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[6]  Masaki Togai,et al.  A fuzzy logic programming environment for real-time control , 1988, Int. J. Approx. Reason..

[7]  S. K. Tso,et al.  Effective Development of Fuzzy-Logic Rules for Real-time Control of Autonomous Vehicles , 1994 .

[8]  Robert N. Lea,et al.  Space shuttle attitude control by reinforcement learning and fuzzy logic , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[9]  W. Wöhlke.  Rendezvous and Berthing Between Columbus Free Flying Laboratory and Space Station Freedom , 1992 .

[10]  P. Martin Larsen,et al.  Industrial applications of fuzzy logic control , 1980 .

[11]  M. Kaplan.  Modern Spacecraft Dynamics and Control , 1976 .

[12]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  T. Pavlidis,et al.  Fuzzy sets and their applications to cognitive and decision processes , 1977 .

[14]  Oscar R. Gonzalez,et al.  Design and implementation of fuzzy logic controllers , 1993 .

[15]  Robert B. Brown.  Fuzzy logic application for modeling man-in-the-loop space shuttle proximity operations , 1994 .

[16]  W. H. Clohessy,et al.  Terminal Guidance System for Satellite Rendezvous , 2012 .

[17]  Chi-Chang J. Ho,et al.  Automatic spacecraft docking using computer vision-based guidance and control techniques , 1993 .

[18]  Wjm Walter Kickert,et al.  ANALYSIS OF A FUZZY LOGIC CONTROLLER , 1978 .

[19]  K F Gill,et al.  A Justification for the Wider Use of Fuzzy Logic Control Algorithms , 1985 .

[20]  Ii Robert J. Marks.  Fuzzy Logic Technology and Applications I , 1994 .

[21]  Ebrahim H. Mamdani,et al.  A linguistic self-organizing process controller , 1979, Autom..

[22]  K F Gill,et al.  Attitude control of a spacecraft using an extended self-organizing fuzzy logic controller , 1987 .

[23]  Anthony V. Sebald,et al.  An Optimization Approach for Fuzzy Controller Design , 1990, 1990 American Control Conference.

[24]  Luigi Fortuna,et al.  Genetic algorithms and applications in system engineering: a survey , 1993 .

[25]  K. Doya,et al.  Intelligent control of a flying vehicle using fuzzy associative memory system , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[26]  Donald M. Waltz.  On-Orbit Servicing of Space Systems , 1993 .