Nonlinear controller of an air-cushion system for a swamp terrain vehicle: fuzzy logic approach

Abstract

This paper presents the fuzzy logic controller (FLC) of an air-cushion system for a swamp peat terrain vehicle and describes the process by which it functions. Cushion pressure is controlled by an electronic proportional control valve and FLC using the output signal of the distance (height) measuring sensor that was attached to the vehicle. The main purpose of this study was to develop a control scheme for an air-cushion system and to investigate the relationship between vehicle vertical position and the air-cushion system, and to illustrate the important role of the fuzzy logic control system. Experimental values were recorded in the laboratory for control system testing, and in the swamp peat terrain field for vehicle performance investigation. In this paper, a fuzzy logic expert system (FLES) model, based on the Mamdani approach, was developed to predict the changes in flowrate. The mean relative error of actual and predicted values from the FLES model of flowrate was found to be slightly above the acceptable limit. The goodness of fit of the prediction values from the FLES model was found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system.

Fuzzy logic-based model for prediction of building wall humidity level

“…FLES generally comprises four principal components 14,15. They are (1) Fuzzification, which takes the crisp numeric inputs and coverts them into the fuzzy form, (2) Rule base, which holds a set of if-then rules, (3) Inference, which creates the control actions and (4) Defuzzification, which calculates the actual (crisp) output.…”

“…FLES generally comprises four principal components. 14,15 They are (1) Fuzzification, which takes the crisp numeric inputs and coverts them into the fuzzy form, (2) Rule base, which holds a set of if-then rules, (3) Inference, which creates the control actions and (4) Defuzzification, which calculates the actual (crisp) output. In general, rule base is a set of logical statements for the linguistic variables used in FLES with the membership functions created from statistical data, expert's appraisals etc.…”