Modelling an Industrial Robot and Its Impact on Productivity

Carlos Llopis-Albert, Francisco Rubio and Francisco Valero
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Carlos Llopis-Albert: Centro de Investigación en Ingeniería Mecánica (CIIM), Universitat Politècnica de València—Camino de Vera s/n, 46022 Valencia, Spain
Francisco Rubio: Centro de Investigación en Ingeniería Mecánica (CIIM), Universitat Politècnica de València—Camino de Vera s/n, 46022 Valencia, Spain
Francisco Valero: Centro de Investigación en Ingeniería Mecánica (CIIM), Universitat Politècnica de València—Camino de Vera s/n, 46022 Valencia, Spain

Mathematics, 2021, vol. 9, issue 7, 1-13

Abstract: This research aims to design an efficient algorithm leading to an improvement of productivity by posing a multi-objective optimization, in which both the time consumed to carry out scheduled tasks and the associated costs of the autonomous industrial system are minimized. The algorithm proposed models the kinematics and dynamics of the industrial robot, provides collision-free trajectories, allows to constrain the energy consumed and meets the physical characteristics of the robot (i.e., restriction on torque, jerks and power in all driving motors). Additionally, the trajectory tracking accuracy is improved using an adaptive fuzzy sliding mode control (AFSMC), which allows compensating for parametric uncertainties, bounded external disturbances and constraint uncertainties. Therefore, the system stability and robustness are enhanced; thus, overcoming some of the limitations of the traditional proportional-integral-derivative (PID) controllers. The trade-offs among the economic issues related to the assembly line and the optimal time trajectory of the desired motion are analyzed using Pareto fronts. The technique is tested in different examples for a six-degrees-of-freedom (DOF) robot system. Results have proved how the use of this methodology enhances the performance and reliability of assembly lines.

Keywords: adaptive fuzzy sliding mode control; controller; multi-objective optimization; robotics; trajectory planning; Pareto frontier; trade-offs; productivity assessment (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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