Geology Reference
In-Depth Information
BACKGROUND AND
LITERATURE REVIEW
mostly use an 'on-off' or 'bang-bang' strategy
for MR applications. The 'on-off' nature of these
algorithms neither provide a smooth change in
MR damper voltage input nor do they consider
all possible voltage values within its full range
(Jung et al., 2005).
A wide range of theoretical and experimental
studies has been performed to assess the efficacy
of MR dampers as semi-active devices (Jung et
al., 2005; Shook et al., 2007). In one of the first
examinations, Karnopp et al. (1974) proposed
a 'skyhook' damper control algorithm for a ve-
hicle suspension system and demonstrated that
this system offers improved performance over a
passive system when applied to a single-degree-
of-freedom (SDOF) system. Feng and Shinozuka
(1990) proposed a bang-bang control approach.
Lyapunov function based approaches are studied
and reported by Leitmann (1994), Sahasrabudhe
and Nagarajaiah (2005). Dyke et al. (1996) pro-
posed a clipped optimal control algorithm based
on acceleration feedback for the MR damper. In
this approach, a linear optimal controller, com-
bined with a force feedback loop, was designed
to adjust the command voltage of the MR damper.
The command signal was set at either zero or the
maximum value depending on how the damper
force compared with the target optimal control
force. The target optimal control can be obtained
from the H2/LQG (linear quadratic Gaussian)
(Dyke et al., 1996) and Lyapunov based methods
(Sahasrabudhe and Nagarajaiah, 2005).
The use of MR dampers as supplementary
damping device to base isolated structures is
promoted and validated by researchers across
the world through benchmark studies on build-
ings (Narasimhan et al., 2006, Nagarajaiah and
Narasimha, 2006, Narasimhan et al. 2008) and
bridge (Agrawal et al. 2009). Interested readers
are directed to special issues by Nagarajaiah et
al. (2008) and Agrawal and Nagarajaiah (2009)
and articles in these special issues for the details
of problem definition and control techniques used
on the benchmark structures.
A control system can be classified as passive, ac-
tive, hybrid, or semi-active based on the level of
energy required and the type of control devices
employed. Among these systems, the semi-active
approach has recently received considerable
attention because of its significant adaptability
without large power requirements like active
systems and is as reliable as passive systems.
Rapid-response, fail-safe, low power requirement,
simple interfaces between electronic controls
and mechanical systems are some characteristics
of magnetorheological (MR) devices that have
attracted significant research interest for using
them as semi-active control devices in applica-
tions of vibration mitigation (Soong and Spencer,
2002; Dyke et al., 1996). In particular, it has
been found that MR dampers can be designed to
be very effective vibration control actuators. In
civil engineering, MR damper applications have
mainly centered around the structural vibration
control under wind and earthquake excitations
(Dyke et al., 1996; Ali and Ramaswamy, 2008a).
The automotive industry has been interested in
developing applications of these materials, for
example, for engine mounts, shock absorbers,
clutches, and seat dampers (Karnopp et al., 1974).
Magnetorheological dampers are nonlinear
devices due to their inherent hysteretic damping
characteristics. The nonlinear hysteretic charac-
teristic can be varied (monitored) by changing
the input voltage to the damper. The nonlinear
hysteretic behaviour and voltage monitoring make
the design of suitable control algorithms that can
provide a smooth change in voltage, an interesting
and challenging task.
Control algorithms available in the literature
map control force required to an equivalent volt-
age and then supply that voltage into the damper.
This inverse mapping of force to voltage makes
the choice and development of control algorithms
more complicated. Semi-active control algorithms
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