Formulation of FISPLAN: A Fuzzy Logic based Reactive Planner for AUVs towards Situation Aware Control
Author(s) -
Subhra Kanti Das,
Dibyendu Pal
Publication year - 2013
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2013.09.06
Subject(s) - planner , computer science , fuzzy logic , controller (irrigation) , control theory (sociology) , interval (graph theory) , field (mathematics) , subsea , energy (signal processing) , control (management) , artificial intelligence , mathematics , marine engineering , engineering , statistics , combinatorics , pure mathematics , agronomy , biology
the paper presents a detailed discussion on the structural organisation of a Fuzzy Inference System Planner (FISPLAN) for Autonomous Underwater Vehicles (AUVs), including elaboration of membership functions for the inputs as well as outputs. The inference mechanism is detailed with discussions on the rule base, which in essence incorporates the planning logic. In order to assess the effectiveness of the planner as a means of reactive escape under critical situations, a case study is studied with reference to a state of the art AUV. An approximate subsea current model is developed from field observations, and residual energy is estimated by referring to a typical Lithium-polymer cell discharge characteristic together with data recorded in actual field trials. Situations are simulated by considering different combinations of sea-currents as well as status of resident energy. Results reveal that the simulated system, by virtue of the planner, is capable of perceiving situations, thereby realizing their imminence and making a decisive action thereupon. In concise, the fuzzy planner may be considered to provide human-like perception of situations on the basis of crisp observations. Furthermore dynamics of the system are modelled with actual parameters, and subsequently controller responses for pitching and velocity correction are illustrated. Choice of planning interval is also expressed as a function of the controllers’ response
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