Abstract
This paper proposes the universal information technology for designing the rule bases (RB) with the formation of optimal consequents for fuzzy systems (FS) of different types on the basis of ant colony optimization (ACO) techniques. The developed ACO-based information technology allows effectively synthesizing rule bases of various dimensions both for the MISO and MIMO fuzzy systems taking into account the particular features of the RB consequents formation in the conditions of insufficient initial information. In order to study and validate the efficiency of the presented information technology the design of the RB for the adaptive fuzzy control system of the ship steering device is carried out in this work. The computer simulations results show that adaptive control system with developed RB provides achievement of high enough quality indicators of rudder angle control. Thus, application of the proposed ACO-based information technology allows designing effective RB with optimal consequents by means of minor computational costs that, in turn, confirms its high efficiency.
Highlights
CURRENTLY, fuzzy logic, fuzzy sets theory and soft computing techniques are widely being used when designing and researching computer systems of various classes [1,2,3]
To significantly reduce the number of edges q in the graph, which will substantially decrease the computational costs of information technology and, increase its performance, this paper proposes the new concept for constructing a rule base graph, which can be called "RuleNode"
The development and research of the universal information technology for designing rule bases (RB) with the formation of optimal consequents for different types of fuzzy systems (FS) based on ant colony optimization techniques is presented in this work
Summary
CURRENTLY, fuzzy logic, fuzzy sets theory and soft computing techniques are widely being used when designing and researching computer systems of various classes [1,2,3]. After theoretical substantiation in a number of fundamental works by L. Kosko et al [4,5,6] the mathematical apparatus of fuzzy logic is successfully used for solving different tasks in conditions of incomplete information and uncertainty. The most expedient is the use of fuzzy logic methods and means in the development of intelligent control and decision making systems for automation of complex nonstationary and nonlinear technical plants, in particular, such as ships and marine floating structures, unmanned underwater and aerial vehicles, mobile robots and drones, industrial robotic production lines, chemical reactors, power plants, etc. The most expedient is the use of fuzzy logic methods and means in the development of intelligent control and decision making systems for automation of complex nonstationary and nonlinear technical plants, in particular, such as ships and marine floating structures, unmanned underwater and aerial vehicles, mobile robots and drones, industrial robotic production lines, chemical reactors, power plants, etc. [7,8,9]
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