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Abstract

Hydraulic high strain rate materials testing machines are required to track a user-defined velocity profile during tensile or compression tests in the face of sudden large impact forces. Due to delays and limited bandwidth of the actuation system, causal feedback/feedforward controllers fail to compensate for these disturbances. This paper presents more suitable non-causal learning control strategies, which anticipate the impact and take corrective action in advance. Two control strategies are discussed. The first comprises an iterative algorithm, which calculates a command signal correction by passing the velocity error observed in the previous test through an inverse model linearized around the target velocity. In the second approach, a detailed nonlinear inverse model is used to obtain a command signal from demand motion and force data. It is concluded that the first method is superior if two or more iterations can be performed.

Keywords

iterative control learning control motion control electrohydraulic servosystems materials testing

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Learning control strategies for high-rate materials testing machines

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