Cognitive Robotics (Jan 2023)
Adjustable Convergence Rate Prescribed Performance with Fractional-Order PID Controller for Servo Pneumatic Actuated Robot Positioning
Abstract
ABSTRACT: This study presents the method for optimal error tracking in position control for a servo pneumatic actuated robot grasper system using a new adjustable convergence rate prescribed performance control (ACR-PPC). It focuses on improving the feedback controller and the fractional-order proportional-integral-derivative (FOPID) controller used for the position control of each robot's finger. Multiple features were considered such as tracking error, rising time, faster transient response with finite-time convergence, oscillation reduction, and pressure stabilization in the pneumatic system. Experiments were conducted using a single finger of a tri-finger pneumatic gripper (TPG) robot, actuated by a single proportional valve with a double-acting cylinder (PPVDC). Two types of input trajectories were tested: step and sine wave inputs, which are common and critical for pneumatic systems. The results show that the proposed method eliminates oscillation and achieves high tracking performance within the prescribed bounds and minimal overshoot as well. The oscillation was suppressed with minimal overshoot and fast response was achieved by tuning the formulated adjustable prescribe performance function, thus improving the rising time response without significant loss of performance.