Simulation Analysis for Trajectory Tracking Control of 5-DOFs Robotic Arm using ANFIS Approach

In this paper, the Scorbot-ER 5 Plus robotic arm is considered to track two different trajectories i.e., straight line and semi-circular one. For the same, the forward kinematic analysis is performed using DH convention. However, due to the unavailability of the closed form, solving the inverse kinematic problem is a quite challenging task. Therefore, in this work, adaptive neuro fuzzy inference system (ANFIS) technique is utilized to find out the inverse kinematic solutions. The recursive Newton-Euler method is employed to carry out the dynamic analysis for the Scorbot-ER 5 Plus. The Proportional-Integral-Derivative (PID) control strategy is implemented in Simulink/MATLAB to ensure the precise tracking of desired trajectories. In the proposed control strategy, the ANFIS based inverse kinematic solutions are exploited as input joint variables for each trajectory. It has been observed from the simulation analysis that ANFIS based PID control shows promising results for required trajectories.

[1]  Antonio Visioli,et al.  On the trajectory tracking control of industrial SCARA robot manipulators , 2002, IEEE Trans. Ind. Electron..

[2]  H. M. A. A. Al-Assadi,et al.  An adaptive-learning algorithm to solve the inverse kinematics problem of a 6 D.O.F serial robot manipulator , 2006, Adv. Eng. Softw..

[3]  Robert J. Schilling,et al.  Fundamentals of robotics - analysis and control , 1990 .

[4]  Jose Alvarez-Ramirez,et al.  On the PID tracking control of robot manipulators , 2001 .

[5]  Joseph F. Engelberger Robotics in practice :: management and applications of industrial robots , 1980 .

[7]  J. Denavit,et al.  A kinematic notation for lower pair mechanisms based on matrices , 1955 .

[8]  Subhash C. Kak,et al.  Inverse Kinematics in Robotics using Neural Networks , 1999, Inf. Sci..

[9]  T. A. Lasky,et al.  Robust independent joint controller design for industrial robot manipulators , 1991 .

[10]  Richard P. Paul,et al.  Robot manipulators : mathematics, programming, and control : the computer control of robot manipulators , 1981 .

[11]  Jyotindra Narayan,et al.  Adaptive neuro-fuzzy inference system–based path planning of 5-degrees-of-freedom spatial manipulator for medical applications , 2018, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[12]  Rasit Köker,et al.  A neural-network committee machine approach to the inverse kinematics problem solution of robotic manipulators , 2013, Engineering with Computers.

[13]  Beno Benhabib,et al.  A complete generalized solution to the inverse kinematics of robots , 1985, IEEE J. Robotics Autom..

[14]  S. Kucuk,et al.  The inverse kinematics solutions of industrial robot manipulators , 2004, Proceedings of the IEEE International Conference on Mechatronics, 2004. ICM '04..

[15]  Y. Su,et al.  Nonlinear PID control of a six-DOF parallel manipulator , 2004 .

[16]  Francis L. Merat,et al.  Introduction to robotics: Mechanics and control , 1987, IEEE J. Robotics Autom..

[17]  Jyotindra Narayan,et al.  ANFIS based kinematic analysis of a 4-DOFs SCARA robot , 2017, 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC).

[18]  Sunwon Park,et al.  PID controller tuning for desired closed‐loop responses for SI/SO systems , 1998 .

[19]  M. Sugeno,et al.  Structure identification of fuzzy model , 1988 .

[20]  Zafer Bingul,et al.  Robot Kinematics: Forward and Inverse Kinematics , 2006 .

[21]  Rafael Kelly,et al.  A tuning procedure for stable PID control of robot manipulators , 1995, Robotica.

[22]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.