Effic ient Control of DC Servomotor Systems Using Backpropagation Neural Networks
Jack N. Averitt, Yahia F. Makableh · 2011
DC motor systems have played an important role in the improvement and development of the industrial revolution, making them the heart of different applications beside AC motor systems. Therefore, the development of a more efficient control strategy that can be used for the control of a DC servomotor system, and a well defined mathematical model that can be used for off line simulation are essential for this type of systems Servomotor systems are known to have nonlinear parameters and dynamic factors, such as backlash, dead zone and Coulomb friction that make the systems hard to control using conventional control methods such as PID controllers. Also, the dynamics of the servomotor and outside factors add more complexity to the analysis of the system, for example when the load attached to the control system changes. Due to these parameters and factors new intelligent control techniques such as Neural Networks, genetic algorithms and Fuzzy logic methods are under research consideration in order to solve the complex problems related to the control of these nonlinear systems.