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Iterative Linear Quadratic Regulator Design for Nonlinear Biological Movement Systems

Authors: Weiwei Li, Emanuel Todorov

Published: 2004 (Conference Paper)

Source: International Conference on Informatics in Control, Automation and Robotics (ICINCO)

Algorithm: iLQR

DOI: 10.5220/0001143902220229

Summary

Introduces iLQR, applying iterative linearization around the current nominal trajectory to reduce nonlinear trajectory optimization to a sequence of LQR problems, enabling efficient second-order trajectory optimization for nonlinear systems.

Abstract

This paper presents an Iterative Linear Quadratic Regulator (ILQR) method for locally-optimal feedback control of nonlinear dynamical systems. The method is applied to a musculo-skeletal arm model with 10 state dimensions and 6 controls, and is used to compute energy-optimal reaching movements. Numerical comparisons with three existing methods demonstrate that the new method converges substantially faster and finds slightly better solutions.

Primary

Paper roboti.us

Standard

DOI 10.5220/0001143902220229

Alternate

scitepress.org PDF scitepress.org

Tags

  • Trajectory optimization

  • Iterative linear quadratic regulator

  • Differential dynamic programming

  • iLQR

  • DDP

  • Nonlinear control