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Optimal-Horizon Model-Predictive Control with Differential Dynamic Programming

2021-11-17 15:58:37
Kyle Stachowicz, Evangelos A. Theodorou
arXiv_RO
   
Abstract

We present an algorithm, based on the Differential Dynamic Programming framework, to handle trajectory optimization problems in which the horizon is determined online rather than fixed a priori. This algorithm exhibits exact one-step convergence for linear, quadratic, time-invariant problems and is fast enough for real-time nonlinear model-predictive control. We show derivations for the nonlinear algorithm in the discrete-time case, and apply this algorithm to a variety of nonlinear problems. Finally, we show the efficacy of the optimal-horizon model-predictive control scheme compared to a standard MPC controller, on an obstacle-avoidance problem with planar robots.

Abstract (translated)

URL

https://arxiv.org/abs/2111.09207

PDF

https://arxiv.org/pdf/2111.09207.pdf

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