Comparison of sliding-mode and fuzzy neural network control for motor-toggle servomechanism

A comparative study of sliding-mode control and fuzzy neural network (FNN) control on the motor-toggle servomechanism is presented in this paper. The toggle mechanism is driven by a permanent-magnet synchronous servo motor. T he rod and crank of the toggle mechanism are assumed to be rigid. First, Ha milton's principle and Lagrange multiplier method are applied to formulate the equation of motion. Then, based on the principles of the sliding-mode c ontrol, a robust controller is developed to control the position of a slide r of the motor-toggle servomechanism, Furthermore, an FNN controller with a daptive learning rates is implemented to control the motor-toggle servomech anism for the comparison of control characteristics. Simulation and experim ental results show that both the sliding-mode and FNN controllers provide h igh-performance dynamic characteristics and are robust with regard to param etric variations and external disturbances. Moreover, the FNN controller ca n result in small control effort without chattering.