Fuzzy Logic Control of Material Forming Process

Adaptive controllers with self-adjustment capabilities possess many advantages over conventional methods. An adaptive fuzzy controller may be implemented either in a direct form or in an indirect form, and it is generally referred to as a self-organizing controller. One advantage of fuzzy controllers is their simple computation requirements in comparison with more algorithmic-based controllers. A metal forming process is a good candidate for the implementation of fuzzy logic rules because of its nonlinear and stochastic properties. In this paper, a prototype electromechanical forming machine was developed and tested. The system includes an optical sensor, an AC induction motor, a servo controller, a forming mechanism, and a microprocessor. The measured state variable is processed by the CPU with a fuzzy logic algorithm. The controller utilizes primary and secondary errors between the actual response and desired output to conduct rule reasoning. Results from testing are presented.