Learning control strategies for high-rate materials testing machines

Reference:

Schlotter, M. and Plummer, A. R., 2011. Learning control strategies for high-rate materials testing machines. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 225 (8), pp. 1125-1135.

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Official URL:

http://dx.doi.org/10.1177/0959651811404871

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.

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