2002 Volume 45 Issue 2 Pages 449-455
A learning method for acquiring the appropriate fuzzy rules using error back propagation to improve the control performance of the pneumatic servo system is presented in this paper. In the proposed method, two criteria are defined and are adjusted so as to minimize them using error back propagation. These criteria are defined on the fuzzy rules, that is, shapes of membership functions of antecedent clause and real values of consequent clause in the fuzzy controller. Two differentiating coefficients of the plant, used in error back propagation with respect to those criteria, are estimated by the newly established neural network. Moreover, sigmoid function is introduced for the connection of the neural network to compensate for the effect of non-linearity of the system. The method was applied to an existent vertical type pneumatic servo system and proved its effectiveness for practical use.
JSME international journal. Ser. 1, Solid mechanics, strength of materials
JSME international journal. Ser. A, Mechanics and material engineering
JSME international journal. Ser. 3, Vibration, control engineering, engineering for industry
JSME international journal. Ser. C, Dynamics, control, robotics, design and manufacturing
JSME International Journal Series A Solid Mechanics and Material Engineering
JSME International Journal Series B Fluids and Thermal Engineering