Vibration suppression of a flexible manipulator using self-tuning optimal control and LIPCA

Abstract

Nowadays active vibration suppression of flexible manipulators is important in many engineering applications, such as robot manipulators and high-speed flexible mechanisms. The demand for short settling time and low energy consumption of the vibration suppression has necessitated the consideration to optimal control. For a wide range of operating conditions, the fixed optimal parameters determined for a control algorithm might not produce the highest performance. Hence, a self-tuning optimal control method for a flexible manipulator should be used to enhance the performance. This method can tune itself to the optimal parameters on the basis of the initial maximum responses of the controlled system. In this study, the multi-objective genetic algorithm is used to search for optimal parameters with regard to positive position feedback, thereby minimizing the settling time and energy consumption multi-objective functions. The experimental results reveal that the energy consumption can be reduced significantly while the settling time is still slightly increased.