Automated Synthesis of a Fuzzy Controller for a Cargo Ship Steering by Means of Qualitative Simulation

Francisco Mugica Alvarez
Instituto Latinoamericano de la Comunicación Educativa
Calle del Puente, 45
Col. Ejidos de Huipulco, Delegación Tlalpan
14380, México, D.F.
México
Email: FMugica@ILCE.Edu.MX
François E. Cellier
Institute of Computational Science
ETH Zürich
CH-8092 Zürich
Switzerland
Email: FCellier@Inf.ETHZ.CH

Keywords

Fuzzy Control
Qualitative Simulation
Learning
Inductive Reasoning
Inverse Model
Ship Dynamics

Abstract

In this paper, Fuzzy Inductive Reasoning, FIR, will be applied to the systematic design of an autopilot of a cargo ship to demonstrate that this methodology works well when applied to highly non-linear plants. The application at hand shows as well the use of several fuzzy inductive reasoners coupled in parallel to resolve a single MIMO controller into several MISO controllers. The functionality of the approach is demonstrated by simulating the quantitative plant together with its qualitative controllers in a mixed quantitative/qualitative simulation enviroment. An important issue in the context of the systematic design presented here is the use of a new technique for obtaining the inverse model dynamics of the plant. In order to evaluate the performance of the Fuzzy Inductive Reasoning Based Controller, FIRBC, open-loop and closed-loop design stages are tested by means of simulation, and the results are compared with a Fuzzy Model Reference Learning Controller, FMRLC, recently proposed for use in the same application.

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