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arXiv · 2009.05838

Guided Policy Search Based Control of a High Dimensional Advanced Manufacturing Process

Amit Surana·Kishore Reddy·Matthew Siopis
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Abstract

In this paper we apply guided policy search (GPS) based reinforcement learning framework for a high dimensional optimal control problem arising in an additive manufacturing process. The problem comprises of controlling the process parameters so that layer-wise deposition of material leads to desired geometric characteristics of the resulting part surface while minimizing the material deposited. A realistic simulation model of the deposition process along with carefully selected set of guiding distributions generated based on iterative Linear Quadratic Regulator is used to train a neural network policy using GPS. A closed loop control based on the trained policy and in-situ measurement of the deposition profile is tested experimentally, and shows promising performance.

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Amit Surana, Kishore Reddy, Matthew Siopis. 2020-09-12. Guided Policy Search Based Control of a High Dimensional Advanced Manufacturing Process. https://arxiv.org/abs/2009.05838

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