Fuzzy genetic controllers for the autonomous rendezvous and docking problem


Autonomous rendezvous and docking has been dlefined as one of the primary goals in today’s space technology. Autonomous operation of an unmanned space vehicle in a real world environment poses a series of problems. The kno,wledge about the environment is in general incomplete, uncertain and approximate. Perceptually acquired information is not precise, sensor’s noise introduces uncertainty and imprecision, sensor’s limited range and visibility introduces incompleteness. in this study, fuzzy logic and genetic algorithm (GA) have been applied to this problem in order to perform better in the case of all these problems. Fuzzy and GA combination imitates the role of human in the decision process. Background Information On Autonomous Rendezvous And Docking Technology The methodology presented in this research can be applied to any transportation problem. Some of the problems include decision making and evaluation of transportation system, transportation network design and traffic scheduling. Decision making and evaluation of a transportation system comprise of achieving multiple objectives using one of the alternate methods. All of these methods cannot satisfy all the objectives. Human decision making is required to weigh all the methods and choose the right alternative. Fuzzy logic with its role of human expert and GA being a strong search and optimization algorithm can mimic the human expert’s role. The problem can be formulated and GAfuzzy method can be applied to find the method that satisfies all the objectives optimally. In the transportation network design, GA-fuzzy method can be applied to find the shortest path or routes to be traversed between the different nodes (for example, bus terminus). GA has been used to solve the traveling salesman problem (TSP), gas pipeline and other combinatorial problems. GA and fuzzy have also been used to find the optimal solution for a lot of scheduling problems. “Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commerical advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is b) permission of the Association for Computing Machinery. To cop) otherwise, or to republish, requires a fee and/or specific permission.”

DOI: 10.1145/315891.316088

Extracted Key Phrases

2 Figures and Tables

Cite this paper

@inproceedings{Gopalan1995FuzzyGC, title={Fuzzy genetic controllers for the autonomous rendezvous and docking problem}, author={Vijayarangan Gopalan and Abdollah Homaifar and M. Reza Salami and R. W. Dabney and Bijan Sayyarrodsari}, booktitle={SAC}, year={1995} }