A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems
Authors:
- E. TodorovETE. Todorov
- Weiwei LiWLWeiwei Li
Top Cited Papers
- 10 August 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 300-306
Abstract
We present an iterative Linear-Quadratic- Gaussian method for locally-optimal feedback control of nonlinear stochastic systems subject to control constraints. Previously, similar methods have been restricted to determin- istic unconstrained problems with quadratic costs. The new method constructs an afÞne feedback control law, obtained by minimizing a novel quadratic approximation to the optimal cost-to-go function. Global convergence is guaranteed through a Levenberg-Marquardt method; convergence in the vicinity of a local minimum is quadratic. Performance is illustrated on a limited-torque inverted pendulum problem, as well as a complex biomechanical control problem involving a stochastic model of the human arm, with 10 state dimensions and 6 muscle actuators. A Matlab implementation of the new algorithm is availabe at www.cogsci.ucsd.edu/~todorov.Keywords
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