PROBABILISTIC CONTROL FOR THE ACTIVE MASS DRIVER BENCHMARK STRUCTURAL MODEL

PROBABILISTIC CONTROL FOR THE
ACTIVE MASS DRIVER BENCHMARK
STRUCTURAL MODEL
B. Scott May and James L. Becky
Civil Engineering, California Institute of Technology, Pasadena, CA 91125,
U.S.A.
SUMMARY
A probability-based robust control design methodology is presented that is
applied to the \benchmark system," which is a high- delity model of an
active-mass-driver laboratory structure. For the controller design, the objective
is to maximize the probability that the uncertain structure/controller
system achieves satisfactory performance when subject to uncertain excitation.
The controller's robust performance is computed for a set of possible
models by weighting the conditional performance probability for a particular
model with the probability of that model, then integrating over the set of
possible models. This is accomplished in an ecient manner using an asymptotic
approximation. The probable performance is then maximized over the
class of constant-gain acceleration-feedback controllers to nd the optimal
controller. This control design method is applied to a reduced-order model
of the benchmark system to obtain four controllers, two that are designed on