Designing fuzzy logic controllers for DC servomotors supported by fuzzy logic control development environment

The design of advanced controllers for many industrial processes is heavily dependent on the availability of a model for the process. Construction of appropriate models is often not possible due to the complexity and nonlinearity of the process. Fuzzy logic can be used for different tasks within intelligent control systems because they represent general, nonlinear relationships that can be initialized using expert knowledge. In adaptive control the key problem is system identification and fuzzy logic is used as process identification and acts as an on-line adaptive part of the control system. The presented work in this paper devoted to the development and the implementation of a smooth and robust fuzzy logic based PID controller targeting a real process represented by a DC servomotor. The aim is to overcome the need for an on-line tuning problem associated with the parameters of classical PID approach and enhances the performance. The adopted self-tuning strategy improves the performance automatically until it converges to a predetermined optimal global criterion. The experimental results and the performance of a developed fuzzy logic controller is compared with other methods such as, model reference adaptive controller and other fuzzy logic based controllers using the same process in terms of steady state error, settling time, and response time. The developed controller shows better performance.