Synchronization Controller for a 3-RRR Parallel Manipulator

A 3-RRR parallel manipulator has been well-known as a closed-loop kinematic chain mechanism in which the end-effector generally a moving platform is connected to the base by several independent actuators. Performance of the robot is decided by performances of the component actuators which are independently driven by tracking controllers without acknowledging information from each other. The platform performance is degraded if any actuator could not be driven well. Therefore, this paper aims to develop an advanced synchronization (SYNC) controller for position tracking of a 3-RRR parallel robot using three DC motor-driven actuators. The proposed control scheme consists of three sliding mode controllers (SMC) to drive the actuators and a supervisory controller named PID-neural network controller (PIDNNC) to compensate the synchronization errors due to system nonlinearities, uncertainties and external disturbances. A Lyapunov stability condition is added to the PIDNNC training mechanism to ensure the robust tracking performance of the manipulator. Numerical simulations have been performed under different working conditions to demonstrate the effectiveness of the suggested control approach.