@article{GawWan09,
author = {Gawthrop, Peter J.
and Wang, Liuping},
title = {Constrained intermittent model predictive control},
journal = {International Journal of Control},
year = 2009,
publisher = {Taylor and Francis},
volume = 82,
issue = 6,
pages = {1138--1147},
abstract = {The generalised hold formulation of intermittent control is re-examined and shown to have some useful theoretical and practical properties. It is shown that this provides a foundation for constrained model predictive control in an intermittent context. The method is illustrated using an example and verified with experimental results.},
issn = {0020-7179},
note = {Published online 27 January 2009},
doi = {10.1080/00207170802474702}
}
@article{LorLakGaw09,
author = {Loram, Ian D. and Lakie, Martin and Gawthrop, Peter J.},
title = {{Visual control of stable and unstable loads: what is the feedback delay and extent of linear time-invariant control?}},
journal = {J Physiol},
volume = 587,
number = 6,
pages = {1343-1365},
doi = {10.1113/jphysiol.2008.166173},
year = 2009,
abstract = {Human balance is commonly described using linear-time-invariant (LTI) models. The feedback time delay determines the position of balance in the motor-control hierarchy. The extent of LTI control illuminates the automaticity of the control process. Using non-parametric analysis, we measured the feedback delay, extent of LTI control and visuo-motor transfer function in six randomly disturbed, visuo-manual compensatory tracking tasks analogous to standing with small mechanical perturbations and purely visual information. The delay depended primarily on load order (2nd: 220 {+/-} 30 ms, 1st: 124 {+/-} 20 ms), and secondarily on visual magnification (extent 2nd: 34 ms, 1st: 8 ms) and was unaffected by load stability. LTI control explained 1st order and stable loads relatively well. For unstable (85 passive stabilisation) 2nd order loads, LTI control accounted for 40 of manual output at 0.1 Hz decreasing below 10 as frequency increased through the important 1-3 Hz region where manual power and visuo-motor gain are high. Visual control of unstable 2nd order loads incurs substantial feedback delays and the control process will not be LTI. These features do not result from exclusive use of visual inputs because we found much shorter delays and a greater degree of LTI control when subjects visually controlled a 1st order load. Rather, these results suggest that delay and variability are inevitable when more flexible, intentional mechanisms are required to control 2nd order unstable loads. The high variability of quiet standing, and movement generally, may be indicative of flexible, variable delay, intentional mechanisms rather than the automatic LTI responses usually reported in response to large perturbations.
}
}
@article{WanYouGawTay09,
author = {Wang, Liuping
and Young, Peter C.
and Gawthrop, Peter J.
and Taylor, C. James},
title = {Non-minimal state-space model-based continuous-time model predictive control with constraints},
journal = {International Journal of Control},
year = 2009,
volume = 82,
issue = 6,
pages = {1122--1137},
publisher = {Taylor and Francis},
abstract = {This article proposes a model predictive control scheme based on a non-minimal state-space (NMSS) structure. Such a combination yields a continuous-time state-space model predictive control system that permits hard constraints to be imposed on both plant input and output variables, whilst using NMSS output-feedback without the need for an observer. A comparison between the NMSS and observer-based approaches using Monte Carlo uncertainty analysis shows that the former design is considerably less sensitive to plant-model mismatch than the latter. Through simulation studies, the article also investigates the role of the implementation filter in noise attenuation, disturbance rejection and robustness of the closed-loop predictive control system. The results show that the filter poles become a subset of the closed-loop poles and this provides a straightforward method of tuning the closed-loop performance to achieve a reasonable balance between speed of response, disturbance rejection, measurement noise attenuation and robustness.},
issn = {0020-7179},
doi = {10.1080/00207170802474694},
note = {Published online 16 March 2009}
}
@article{Gaw09,
author = {Peter J Gawthrop},
title = {Frequency Domain Analysis of Intermittent Control},
journal = {Proceedings of the Institution of Mechanical Engineers
Pt. I: Journal of Systems and Control Engineering},
year = 2009,
volume = 223,
number = 5,
pages = {591-603},
doi = {10.1243/09596518JSCE759},
abstract = {
Intermittent control is a feedback control design method that
combines both continuous-time and discrete-time domains; a recent
result shows that this form of intermittent control can be
rewritten as a sampled-data feedback system with a particular
vector generalised hold. This paper builds on this result to give,
for the first time, a frequency domain analysis of the closed-loop
system containing an intermittent controller.
This analysis is illustrated using two examples. The first example
is related to the human balance control system and us thus
physiologically relevant. The second example gives a theoretical
explanation of the phenomenon of self-induced oscillations in
intermittent control systems.
}
}
@article{GawWan09a,
author = {Peter J Gawthrop and Liuping Wang},
title = {Event-driven Intermittent Control},
journal = {International Journal of Control},
year = 2009,
note = {Published online 09 July 2009},
volume = 82,
number = 12,
pages = {2235 - 2248},
month = {December},
doi = {10.1080/00207170902978115},
abstract = {
An intermittent controller with fixed sampling interval is recast as
an event-driven controller. The key aspect of intermittent control
that makes this possible is the use of basis functions, or,
equivalently, a generalised hold, to generate the intersample
open-loop control signal. The controller incorporates both
feedforward events in response to known signals and feedback events
in response to detected disturbances. The latter feature makes use
of an extended basis-function generator to generate open-loop
predictions of states to be compared with measured or observed
states. Intermittent control is based on an underlying
continuous-time controller; it is emphasised that the design of this
continuous-time controller is important, particularly in the
presence of input disturbances. Illustrative simulation examples
are given.
}
}
@article{GawLorLak09,
author = {Peter Gawthrop and Ian Loram and Martin Lakie},
title = {Predictive Feedback in Human Simulated Pendulum Balancing},
journal = {Biological Cybernetics},
year = 2009,
volume = 101,
number = 2,
pages = {131-146},
doi = {10.1007/s00422-009-0325-6},
note = {Published online July 09, 2009},
abstract = {
In studies of human balance, it is common to fit stimulus-response
data by tuning the time-delay and gain parameters of a simple
delayed feedback model. Many interpret this fitted model, a simple
delayed feedback model, as evidence that predictive processes are
not required to explain existing data on standing balance.
However, two questions lead us to doubt this approach. First, does
fitting a delayed feedback model lead to reliable estimates of the
time-delay? Second, can a non-predictive controller provide an
explanation compatible with the independently estimated time delay?
For methodological and experimental clarity, we study human
balancing of a simulated inverted pendulum via joystick and
screen. A two-step approach to data analysis is used: firstly a
non-parametric model - the closed-loop impulse response - is
estimated from the experimental data; secondly, a parametric model
is fitted to the non-parametric impulse-response by adjusting
time-delay and controller parameters. To support the second step, a
new explicit formula relating controller parameters to closed-loop
impulse response is derived. Two classes of controller are
investigated within a common state-space context: non-predictive and
predictive.
It is found that the time-delay estimate arising from the second
step is strongly dependent on which controller class is assumed; in
particular, the non-predictive control assumption leads to
time-delay estimates that are smaller than those arising from the
predictive assumption.
Moreover, the time-delays estimated using the non-predictive control
assumption are not consistent with a lower-bound on the time-delay
of the non-parametric model whereas the corresponding predictive
result is consistent. Thus while the goodness of fit only marginally
favoured predictive over non-predictive control, if we add the
additional constraint that the model must reproduce the
non-parametric time delay, then the non-predictive control model
fails. We conclude (i) the time-delay should be estimated
independently of fitting a low order parametric model, (ii) that
balance of the simulated inverted pendulum could not be explained by
the non-predictive control model and (iii) that predictive control
provided a better explanation than non-predictive control.
}
}
@article{GawBhiMoh09,
title = {Physical-model-based control of a piezoelectric tube for nano-scale positioning applications},
journal = {Mechatronics},
volume = 20,
number = 1,
pages = {74 - 84},
month = {February},
year = 2010,
issn = {0957-4158},
doi = {10.1016/j.mechatronics.2009.09.006},
author = {P.J. Gawthrop and B. Bhikkaji and S.O.R. Moheimani},
keywords = {Flexible structures},
keywords = {Piezoelectric transducers},
keywords = {Charge control},
keywords = {Vibration control},
keywords = {Bond graphs},
keywords = {Physical-model-based control},
abstract = {
Piezoelectric tubes exhibit a highly resonant mode of vibration which, if uncontrolled, limits the maximum scan rate in nano-scale positioning applications. Highly resonant systems with collocated sensor/actuator are often controlled using resonant shunt dampers. Unfortunately, in the configuration used here, this approach is not possible due the non-minimum phase property arising from the presence of a right-half plane zero.
This problem is solved by: (i) interpreting the resonant shunt damper in the context of physical-model-based control (PMBC) and (ii) extending the PMBC approach to handle non-minimum phase systems.
The resultant controller combines the physical insight of the resonant shunt damper with the ability to control the non-minimum phase piezoelectric tube.
A digital implementation of the controller was experimentally evaluated and found to successfully eliminate the resonant mode of vibration during an accurate and fast scan using a piezoelectric tube actuator.},
note = {Available online 13 October 2009}
}
@article{Gaw09a,
author = {P.J. Gawthrop},
title = {Act-and-Wait and Intermittent Control: Some Comments},
journal = {IEEE Transactions on Control Systems Technology},
year = 2009,
note = {Published on-line: 10/11/2009},
doi = {10.1109/TCST.2009.2034403},
issn = {1063-6536},
abstract = {The act-and-wait control introduced by Insperger is shown to be related
to a form of intermittent control. Theoretical and practical similarities
and differences between the two methods are explored.}
}
@article{Gaw09b,
author = {Peter Gawthrop},
title = {Spherical Panoramas},
journal = {Journal of the Royal Photographic Society},
year = 2009,
volume = 149,
number = 2,
pages = {118-121},
month = {March},
url = {http://www.lightspacewater.net/Tutorials/OSP/PerspectivePanorama/Gaw09b.pdf}
}
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