posted on 2013-12-17, 14:44authored byKeith J. Smith
Multi-actuator structural testing has traditionally been regarded, from a control
point of view, as a multi-loop single-input, single-output problem. This approach does
not take into account the interaction between. different actuators, due to the dynamics
of the structure under test, which can be considerable. The result of this is often poor
laboratory reproduction of the actual service data.
This project shows that the mass of the structure under test has a considerable
impact upon the stability of the traditional multi-loop, single-input, single-output
control system. Where stability is prejudiced, the loop gains have to be reduced to
maintain stability and this can degrade the performance of the test. In these
circumstances multivariable control offers the potential for a significant improvement
in performance.
Two experimental rigs are used in this project, both exhibit major interaction
and pose a significant control problem. The first rig consists of a laboratory scale
cantilever beam excited by two electro-dynamic vibrators with displacements
measured by Linear Variable Differential Transformers (L VDTs). The second,
industrial-scale, rig consists of a large steel frame excited by two hydraulic actuators
with applied force measured by load cells. Multivariable controllers are designed and
implemented on these rigs based on the frequency-domain Characteristic Locus
method. The multivariable controllers are shown to demonstrate superior performance
to traditional multi-loop controllers.
Mathematical models of the rigs are not required for controller design, instead
experimental frequency responses are all that are needed. This is a major attraction of
the Characteristic Locus method since the task.of modelling the dynamics of a multichannel
structural test system is not trivial. However, obtaining the frequency response
of the second rig is made difficult by the imposition of closed-loop control during the
identification experiment. A technique is presented to overcome this problem using an
existing correlation method.
History
School
Aeronautical, Automotive, Chemical and Materials Engineering