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Nonlinear optimal control for a 4-DOF SCARA robotic manipulator

Published online by Cambridge University Press:  25 April 2023

G. Rigatos*
Affiliation:
Unit of Industrial Automation, Industrial Systems Institute, Rion Patras, Greece
M. Abbaszadeh
Affiliation:
Department of ECS Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
K. Busawon
Affiliation:
Department of Mechanical Engineering, University of Northumbria, Newcastle, UK
J. Pomares
Affiliation:
Department of Systems Engineering, University of Alicante, Alicante, Spain
*
*Corresponding author. E-mail: grigat@ieee.org

Abstract

Selective compliance articulated robot arms (SCARA) robotic manipulators find wide use in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-degrees of freedom (DOF) SCARA robotic manipulator. The dynamic model of the SCARA robot undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system, a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control method is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, it is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs and (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators. The nonlinear optimal controller for the 4-DOF SCARA robot is finally compared against a flatness-based controller implemented in successive loops.

Type
Research Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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