ETTC'2003 - SEE

ETTC'2003 - SEE ETTC'2003 - SEE

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Indeed, when the objective of the test is to determine the structure characteristics, it is difficult to have a model with genuine parameters. Besides, even if you know the parameters that characterize the tested structure, you have to take into account the fact that these parameters may vary during the test. So any control system can not be chosen to guaranty the performance. Robust control is a control system design that permits to take into account the parameters variations of the model. The part 1 of this paper introduces a robust control system design that is applied to a hydraulic test bench that will be part of the test devices of LAMEFIP- ENSAM. The test bench includes a hydraulic actuator whose cylinder is linked to the mechanical structure to be tested. The tested structure is compressed by the actuator at constant velocity in order to determine its characteristics. The control system must take into account the fact that the parameters of the tested structure are not well-known and change during the test The parts 2 & 3 of the paper introduce some other test devices that are available at ENSICA and ENSAM. 1 - Benefits of robust control for test devices 1.1 - What is robust control ? The design of a control law requires a model of the process to control. The model can only be imperfect. However it is used in order to design control and to guaranty stability, stability margins, precision, performance,… Thus it is legitimate to question oneself on the behaviour of the control system with respect to the model uncertainties. A property of control is said to be robust if it is maintained in spite of the model uncertainties. It is possible to check a posteriori the behaviour of the control system with respect to uncertainties but it would be a saving in time and in money to design a control system that permits to take into account the uncertainties of the model a priori. This is the objective of the robust control. Different methodologies of robust control have been developed. The methodology proposed in this article is the CRONE control system design. ETTC2003 European Test and Telemetry Conference

1.2 - The CRONE control system design CRONE (the French acronym of "Commande Robuste d'Ordre Non Entier") control system design [1] is a frequency-domain based methodology, using complex fractional differentiation [2]. It permits the robust control of perturbed linear plants using the common unity feedback configuration. It consists on determining the nominal and optimal open-loop transfer function that guaranties the required specifications. This methodology uses fractional derivative orders (real or complex) as high level parameters that make you easy the design and optimization of the control-system. Here is an example of fractional transfer function: β ( s) = cosh b ℜ n = a + i b ∈ C and s = σ + jω ∈ C . with i j 2 Three Crone control generations have been developed, successively extending the application fields. The third generation CRONE methodology can be described in five points: ETTC2003 European Test and Telemetry Conference −1 1 - You determine the nominal plant transfer function and the uncertainty domains. For a given frequency, an uncertainty domain is the smallest hull including the possible frequency responses of the plant. The use of the edge of the domains permits to take into account the uncertainty with the smallest number of data. 2 - You specify some parameters of the open-loop transfer function defined for the nominal state of the plant, for example the specifications at low and high frequencies. 3 - You specify the required specifications that you would like to obtain. 4 - Using the nominal plant locus and the uncertainty domains in the Nichols chart, you optimize the parameters of the fractional open-loop transfer function. 5 - The last point is the synthesis of the controller. While taking into account the plant right half-plane zeros and poles, the controller is deduced by frequency-domain system identification of the ratio of the fractional open-loop transfer function to the nominal plant function transfer. The resulting controller K(s) is a rational transfer function. / i ω cg s n

1.2 - The CRONE control system design<br />

CRONE (the French acronym of "Commande Robuste d'Ordre Non Entier")<br />

control system design [1] is a frequency-domain based methodology, using<br />

complex fractional differentiation [2]. It permits the robust control of perturbed linear<br />

plants using the common unity feedback configuration. It consists on determining<br />

the nominal and optimal open-loop transfer function that guaranties the required<br />

specifications. This methodology uses fractional derivative orders (real or complex)<br />

as high level parameters that make you easy the design and optimization of the<br />

control-system. Here is an example of fractional transfer function:<br />

β<br />

( s)<br />

= cosh b ℜ<br />

n = a + i b ∈ C and s = σ + jω<br />

∈ C .<br />

with i<br />

j<br />

2<br />

Three Crone control generations have been developed, successively<br />

extending the application fields. The third generation CRONE methodology can be<br />

described in five points:<br />

ETTC2003 European Test and Telemetry Conference<br />

−1<br />

1 - You determine the nominal plant transfer function and the uncertainty<br />

domains. For a given frequency, an uncertainty domain is the smallest hull<br />

including the possible frequency responses of the plant. The use of the edge of the<br />

domains permits to take into account the uncertainty with the smallest number of<br />

data.<br />

2 - You specify some parameters of the open-loop transfer function defined<br />

for the nominal state of the plant, for example the specifications at low and high<br />

frequencies.<br />

3 - You specify the required specifications that you would like to obtain.<br />

4 - Using the nominal plant locus and the uncertainty domains in the<br />

Nichols chart, you optimize the parameters of the fractional open-loop transfer<br />

function.<br />

5 - The last point is the synthesis of the controller. While taking into<br />

account the plant right half-plane zeros and poles, the controller is deduced by<br />

frequency-domain system identification of the ratio of the fractional open-loop<br />

transfer function to the nominal plant function transfer. The resulting controller K(s)<br />

is a rational transfer function.<br />

/ i<br />

ω<br />

cg<br />

s<br />

n

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