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Article contents

Compliance and frequency optimization for energy efficiency in cyclic tasks

Published online by Cambridge University Press:  10 February 2017

Mohammad Shushtari
Affiliation:
Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. E-mails: nasiri.rezvan@gmail.com, sm.shushtari@gmail.com, mnili@ut.ac.ir
Rezvan Nasiri*
Affiliation:
Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. E-mails: nasiri.rezvan@gmail.com, sm.shushtari@gmail.com, mnili@ut.ac.ir
Mohammad Javad Yazdanpanah
Affiliation:
Advanced Control Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. E-mail: yazdan@ut.ac.ir
Majid Nili Ahmadabadi
Affiliation:
Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran. E-mails: nasiri.rezvan@gmail.com, sm.shushtari@gmail.com, mnili@ut.ac.ir
*
*Corresponding author. E-mail: nasiri.rezvan@gmail.com

Summary

We present an analytical method for the concurrent calculation of optimal parallel compliant elements and frequency of reference trajectories for serial manipulators performing cyclic tasks. In this approach, we simultaneously shape and exploit the robot's natural dynamics by finding a set of compliant elements and task frequency that result in minimization of an energy-based cost function. The cost function is the integral of a weighted squared norm of the generalized forces. We prove that the generalized force needed for tracking the reference trajectory is a linear function of compliance coefficients and a quadratic function of task frequency. Therefore, the cost function is quadratic with respect to stiffness coefficients and quartic with respect to the task frequency. These properties lead to a well-posed optimization problem with a closed-form solution. Using three case studies, we elucidate the properties of our method.

Type
Articles
Information
Robotica , Volume 35 , Issue 12 , December 2017 , pp. 2363 - 2380
Copyright
Copyright © Cambridge University Press 2017 

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