Real-Time Tip Position Control of a Flexible Link Robot

Abstract

Lightweight flexible robots are widely used in space applications due to their fast response and operation at high speed compared to conventional industrial rigid link
robots. But the modeling and control of a flexible robot is more complex and difficult due to distributed structural flexibility. Further, a number of control complexities are
encountered in case of flexible link robots such as non-minimum phase and under actuated behavior, non linear time varying and distributed parameter systems. Many control strategies have been proposed in the past, but most of the works have not considered the actuator dynamics and experimental validation of the modeling.

In this thesis, we consider the actuator dynamics is considered in modeling and also we have undertaken the experimental validation of the modeling. Tip positioning is
the prime control objective of interest in many robotics applications. A tip feedback joint PD control has been proposed for tip positioning of the single link flexible robot. Gains of the controller have been obtained by using genetic algorithm and bacteria foraging optimization methods. By exploiting the above two evolutionary computing techniques for obtaining optimal gains good tip position control has been achieved together with good tracking control. The performances of the above two evolutionary computing tuned controller have been verified by both simulation and experiments.