Decentralized PID control is a widespread solution for trajectory tracking control of robotic manipulators in industrial contexts, because it provides a good trade-off between ease of implementation and performance. However, in many cases the final tuning of the independent controllers relies on exhaustive trial-and-error procedures, which are time-consuming, and may lead to globally sub-optimal configurations. In this paper, we describe an automatic and simultaneous tuning procedure for the linear controllers of a 5dof robotic manipulator based on Genetic Algorithms. The preliminary results described in this paper, obtained on a detailed model of an industrial manipulator developed within the SimMechanics Matlab environment, show the effectiveness of the evolutionary design procedure. The decentralized controllers can hold satisfactory performances over a wide range of operating conditions, including unknown load disturbances.

Genetic design of decentralized controllers for 5dof robotic manipulator

CUPERTINO, Francesco;NASO, David;TURCHIANO, Biagio
2003

Abstract

Decentralized PID control is a widespread solution for trajectory tracking control of robotic manipulators in industrial contexts, because it provides a good trade-off between ease of implementation and performance. However, in many cases the final tuning of the independent controllers relies on exhaustive trial-and-error procedures, which are time-consuming, and may lead to globally sub-optimal configurations. In this paper, we describe an automatic and simultaneous tuning procedure for the linear controllers of a 5dof robotic manipulator based on Genetic Algorithms. The preliminary results described in this paper, obtained on a detailed model of an industrial manipulator developed within the SimMechanics Matlab environment, show the effectiveness of the evolutionary design procedure. The decentralized controllers can hold satisfactory performances over a wide range of operating conditions, including unknown load disturbances.
International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
0-7803-7866-0
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/13802
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