Learning control strategies for high-rate materials testing machines

Michael Schlotter, Andrew R Plummer

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)
217 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)1125-1135
Number of pages11
JournalProceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
Issue number8
Early online date21 Aug 2011
Publication statusPublished - Dec 2011


Dive into the research topics of 'Learning control strategies for high-rate materials testing machines'. Together they form a unique fingerprint.

Cite this