Optimal fuzzy control using hedge algebras of a damped elastic jointed inverted pendulum

In this paper, three controllers including OFCHA (optimal fuzzy control using hedge algebras - HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Our attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time periodic follower force. Different values of the pendulum length are considered. Simulation results are exposed to illustrate the effect of OFCHA in comparison with FCHA and CFC. | Vietnam Journal of Mechanics, VAST, Vol. 32, No. 4 (2010), pp. 247 – 262 OPTIMAL FUZZY CONTROL USING HEDGE ALGEBRAS OF A DAMPED ELASTIC JOINTED INVERTED PENDULUM Bui Hai Le1 , Tran Duc Trung1 and Vu Nhu Lan2 1 Hanoi University of Science and Technology 2 Institute of Information Technology Abstract. In this paper, three controllers including OFCHA (optimal fuzzy control using hedge algebras - HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Our attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time periodic follower force. Different values of the pendulum length are considered. Simulation results are exposed to illustrate the effect of OFCHA in comparison with FCHA and CFC. 1. INTRODUCTION Fuzzy set theory introduced by Zadeh in 1965 has provided a mathematical tool useful for modelling uncertain (imprecise) and vague data and been presented in many real situations. As typical unstable nonlinear models, inverted pendulum systems are often used as a benchmark for verifying the effect of a new control method because of the simplicity of the structure. Recently, many researches on stabilization of pendulum systems have been done. Yi and Yubazaki [1] presented a fuzzy controller for stabilization control of inverted pendulum systems basing on the Single Input Rule Modules (SIRMs) dynamically connected fuzzy inference model. The fuzzy controller has four input items, each with a SIRM and a dynamic importance degree. Yi et al. [2] presented a fuzzy controller with six input items and one output item for stabilizing a parallel-type double inverted pendulum system basing on the SIRMs dynamically connected fuzzy inference model. Becerikli and Celikb [3] presented a fuzzy controller for an inverted pendulum system in two stages: investigation of fuzzy control system modeling methods and solution of the "Inverted Pendulum Problem" by using Java programming with .

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