@article{Gaw98a,
author = {Peter J. Gawthrop},
cscauthor = {pjg},
title = {Physical Interpretation of Inverse Dynamics using
Bond Graphs},
journal = {The Bond Graph Digest},
year = 1998,
volume = 2,
number = 1,
month = {January},
pages = {23pp}
}
@article{JohHunGaw98,
author = {T. A. Johansen and K. J. Hunt
and P. J. Gawthrop and H. Fritz},
cscauthor = {kjh,pjg},
title = {Off-equilibrium linearisation and design of gain scheduled
control with application to vehicle speed control},
journal = {Control Engineering Practice},
year = {1998},
volume = {6},
number = {2},
pages = {167--180},
abstract = {In conventional gain-scheduled control design,
linearisation of a time-invariant nonlinear system and local control
design for the resulting set of linear time-invariant systems is
performed at a set of equilibrium points. Due to its validity only
near equilibrium, such a design may result in poor transient
performance. To resolve this problem, one can base the control design
on a dynamic linearisation about some nominal trajectory. However, a
drawback with this approach is that control design for the resulting
linear time-varying system is in general a difficult problem. In this
paper it is suggested that linearisation and local controller design
should be carried out not only at equilibrium states, but also in
transient operating regimes. It is shown that this results in a set of
time-invariant linearisations which, when they are interpolated, form
a close approximation to the time-varying system resulting from
dynamic linearisation. Consequently, the transient performance can be
improved by increasing the number of linear time-invariant
controllers. The feasibility of this approach, and possible
improvements in transient performance, are illustrated with results
from an experimental vehicle speed-control application. },
pdf = {../../Publications/csc1998/JohHunGaw98.pdf}
}
@article{GawDemSil98,
author = {Gawthrop, P.J. and Demircioglu, H. and Siller-Alcala, I.I.},
journal = {Control Theory and Applications, IEE Proceedings -},
title = {Multivariable continuous-time generalised predictive control: a state-space approach to linear and nonlinear systems},
year = 1998,
month = {may},
volume = 145,
number = 3,
pages = {241 -250},
abstract = {The multivariable continuous-time generalised predictive controller (CGPC) is recast in a state-space form and shown to include generalised minimum variance (GMV) and a new algorithm, predictive GMV (PGMV) as special cases. Comparisons are drawn with the exact linearisation methods of nonlinear control, and it is noted that, unlike the transfer function approach, the state-space approach extends readily to the nonlinear case. The resulting state space design algorithms are conceptually and algorithmically simpler than the corresponding transfer function based versions and have been realised as a freely available Matlab tool-box},
keywords = {CGPC;Matlab tool-box;PGMV;exact linearisation methods;generalised minimum variance;linear systems;multivariable continuous-time generalised predictive control ;nonlinear control;nonlinear systems;predictive GMV;state space design algorithms;state-space approach;transfer function based versions;multivariable control systems;nonlinear control systems;predictive control;state-space methods;},
doi = {10.1049/ip-cta:19982045},
issn = {1350-2379}
}
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