Showing 3 results for Fuzzy Inference
M. Hakimollahi, S. G. Jalali Naini, M. Bagherpour, S. Jafari, A. Shahmoradi,
Volume 2, Issue 4 (10-2012)
Abstract
In recent years, the balanced score card (BSC) has been the focus of considerable methodology for strategic
cost management in management accounting area since it was originally proposed by Kaplan ,R.S. and
Norton, D.P. in 1992. BSC is an approach to performance measurement based on both financial and nonfinancial
information from four perspectives which are called financial, customer, internal business process,
and learning and growth, in order to balance the traditional financial performance system by several
grouping of performance measures: short-term and long-term, internal and external, and current and future.
Over time, it has been developed to a strategic management system from a comprehensive performance
measure, and used in many organizations such as business, hospital, and autonomy in many countries. In
this paper, we propose a general model based on BSC by introducing fuzzy inference mechanism. From
this, specialists’ knowledge and experience can be effectively reflected during the construction of the
practical model. Then we illustrate a practical example for an Automotive Manufacturing Co.
Farhad Pashaei, Seyed Mahdi Abtahi,
Volume 11, Issue 4 (12-2021)
Abstract
In this paper, firstly chaotic behavior of the lateral dynamics of vehicle is investigated by the use of numerical tools including Lyapunov exponent and bifurcation diagrams. To this end rout to chaos along with period doubling and quasi-periodic responses are demonstrated in terms of bifurcation diagrams. After chaos analysis, a novel controller commensurate with the chaotic characteristics of the system, in conformity with Poincaré map is represented to suppress the chaotic behavior of lateral movement. The Poincaré map of the system is derived by means of a neuro fuzzy network. A robust Fuzzy system on the basis of nonlinear Ott-Grebogi-Yorke (OGY) method forms the control system. Closed-loop results of the system shows effectiveness of the chaos controller in extreme conditions.
Yavar Nourollahi Golouje, Seyyed Mahdi Abtahi, Majid Majidi,
Volume 12, Issue 2 (6-2022)
Abstract
In this paper, analysis and control of the chaotic vibrations in bounce dynamic of vehicle have been studied according to the comparison of controller based on the nonlinear control and chaos controller on the basis of the chaotic system properties. After modeling the vehicle dynamic, the chaotic behavior of the uncontrolled system was determined using combination of the numerical analysis including bifurcation diagrams and max Lyapunov exponent. The system parameters values were then identified in the quasi-periodic and chaotic behavior system. In order to eliminate the chaotic vibrations, the control signal was first developed using a nonlinear fast-terminal sliding mode control algorithm that its control gains are estimated online by fuzzy logic which was designed for vehicle vertical dynamics. Then the delayed feedback control was designed based on the development of Pyragas algorithm to control the system based on the properties of the chaotic system and generation of a small control signal. Comparison of the feedback system depicts priority of the Fuzzy-Pyragas controller in less energy consumption and better behavior.
