| [1] |
W.-H. Chen, D. J. Ballance, P. J. Gawthrop, and John O'Reilly.
A nonlinear disturbance observer for robotic manipulators.
IEEE Transactions on Industrial Electronics, 47(4):932--938,
August 2000.
[ bib |
.pdf ]
A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well
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| [2] |
W.-H. Chen, D. J. Ballance, and P. J. Gawthrop.
Optimal control of SISO nonlinear systems: A predictive control
approach.
In Proceedings of the UKACC conference “Control 2000”,
Cambridge, U.K., 2000.
[ bib |
.pdf ]
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| [3] |
Peter J. Gawthrop.
Estimating physical parameters of nonlinear systems using bond graph
models.
In Proceedings of the 12th IFAC Symposium on System
Identification (SYSID 2000), Santa Barbara, California, USA, June 2000.
[ bib |
.pdf ]
An approach to the estimation of the physical parameters of nonlinear systems modelled by bond graphs is presented and illustrative examples given.
|
| [4] |
Peter J. Gawthrop.
Symbolic generation of real-time simulation code for large stiff
nonlinear systems.
In Proceedings of the UKACC conference “Control 2000”,
Cambridge, U.K., 2000.
[ bib |
.pdf ]
Real-time simulation requires fast stable integration algorithms with a fixed sample interval which can be chosen without loss of stability. A symbolic approach to generating system-dependent integration algorithms is proposed and evaluated
|
| [5] |
Peter J Gawthrop.
Sensitivity bond graphs.
Journal of the Franklin Institute, 337(7):907--922, November
2000.
[ bib |
DOI |
.pdf ]
A sensitivity bond graph, of the same structure as the system bond graph, is shown to provide a simple and effective method of generating sensitivity functions of use in optimisation. The approach is illustrated in the context of partially-known system parameter and state estimation.
|
| [6] |
Peter J Gawthrop.
Physical interpretation of inverse dynamics using bicausal bond
graphs.
Journal of the Franklin Institute, 337(6):743--769, 2000.
[ bib |
DOI |
.pdf ]
A physical interpretation of the inverse dynamics of linear and nonlinear systems is given in terms of the bond graph of the inverse system. It is argued that this interpretation yields physical insight to guide the control engineer. Examples are drawn from both robotic and process systems.
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| [7] |
Peter J Gawthrop.
Linear predictive pole-placement control: Practical issues.
In Proceedings of the 39th IEEE Conference on Decision and
Control, pages 160--165, Sydney, Australia, December 2000. IEEE.
[ bib |
.pdf ]
Some of the theoretical properties of predictive-pole-placement control (a form of model-based predictive control) are given a practical interpretation and corresponding design rules suggested.
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| [8] | Peter J. Gawthrop and Eric Ronco. A sensitivity bond graph approach to estimation and control of mechatronic systems. In Proceedings of the 1st IFAC Conference on Mechatronic Systems, Darmstadt, September 2000. [ bib | .pdf ] |
| [9] |
Peter J. Gawthrop and Eric Ronco.
Estimation and control of mechatronic systems using sensitivity bond
graphs.
Control Engineering Practice, 8(11):1237--1248, November 2000.
[ bib |
DOI |
.pdf ]
A new bond graph framework for sensitivity theory is applied to model-based predictive control, state estimation, and parameter estimation in the context of physical systems. The approach is illustrated using a nonlinear mechatronic system.
|
| [10] |
Peter J. Gawthrop and Liuping Wang.
Transfer function and frequency response estimation using resonant
filters.
In Proceedings of the 12th IFAC Symposium on System
Identification (SYSID 2000), Santa Barbara, California, USA, June 2000.
[ bib |
.pdf ]
A resonant filter approach is proposed for direct identification of continuous-time transfer functions from input-output data when the input contains periodic components. The asymptotic properties of the method are analysed; in particular the noise reduction properties are emphasised. Some illustrative simulations are provided.
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| [11] | David Palmer, Donald J. Ballance, Peter J. Gawthrop, Kenneth Strain, and Norna A. Robertson. Modelling gravitational wave detector suspensions using bond graphs. In I Troch and F. Breitenecker, editors, Proceedings of the 3rd IMACS Symposium on Mathematical Modelling, pages 739--742, Vienna, Austria, February 2000. ARGESIM. [ bib ] |
| [12] |
David Palmer, Donald J. Ballance, and Peter J. Gawthrop.
Modelling gravitational wave detector suspensions using bond graphs
and symbolic computation.
In Proceedings of the UKACC conference “Control 2000”,
Cambridge, U.K., 2000.
[ bib |
.pdf ]
Real-time simulation requires fast stable integration algorithms with a fixed sample interval which can be chosen without loss of stability. A symbolic approach to generating system-dependent integration algorithms is proposed and evaluated.
|
| [13] |
Eric Ronco and Peter J. Gawthrop.
Symbolic quasi-Newton optimisation for system identification.
In Proceedings of the UKACC conference “Control 2000”,
Cambridge, U.K., 2000.
[ bib |
.pdf ]
A new approach to time-critical optimisation in the context of identification and control is presented. Symbolic algebra is used to provide the equations for computing the sensitivity functions of a system relevant to provide rapid computation of gradient information. It is verified that the resultant gradient-based optimisation is substantially faster than the corresponding non-gradient method.
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