Page 680 - The Mechatronics Handbook

controlled system. Examples have been given of modeling and simulation with 20-sim that allows for such
an approach.
Mechatronic designers should constantly be aware of the fact that solutions can be found in different
domains. Not every mechanical deficiency can easily be solved by control. A good mechanical design
may be easier and cheaper to achieve. On the other hand, a good controller may be able to achieve the
desired performance much easier and cheaper than a complex mechanical construction. In some cases
the combination can even achieve performances that would never have been possible without a mecha-
tronic design.
The same holds for the design of sensors. Each sensor could be fitted with a filter to remove noise
from the measurements. But if several sensors are being combined, sensor fusion in a Kalman filter
algorithm will benefit from the availability of the raw data.
Communication between all the designers involved and transparency of the design decisions in the
various domains are essential for the success of a true mechatronic design.

References
1. Matworks (2001). The Mathworks: Developers of Matlab and Simulink, www.mathworks.com
2. Coelingh, H.J., Design Support for Motion Control Systems, Ph.D. thesis, University of Twente, 2000,
also www.rt.el.utwente.nl/clh/
3. Coelingh, H.J., de Vries, T.J.A., van Amerongen, J., Design support for motion control systems—
application to the Philips fast component mounter, in Mechatronics Forum 7th Int. Conf., Mecha-
tronics 2000, Atlanta, Ga, USA.
4. Controllab Products, 20-sim, www.20sim.com
5. Broenink, J.F., Computer-Aided Physical-Systems Modeling and Simulation: a Bond-Graph Approach,
Ph.D. thesis, University of Twente, 1990.
6. Dynasim, Dymola, www.dynasim.se/
7. Weustink, P.B.T., de Vries, T.J.A., Breedveld, P.C., Object Oriented Modeling and Simulation of Mecha-
tronic Systems with 20-sim 3.0, in Mechatronics 98, J. Adolfson and J. Karlsén (Eds.), Elsevier Science,
1998.
8. De Vries, T.J.A., Conceptual Design of Controlled Electro-Mechanical Systems, Ph.D. thesis, University
of Twente, 1994.
9. Breedveld, P.C., Fundamentals of bond graphs, in IMACS Annals of Computing and Applied Math-
ematics, Vol. 3: Modelling and Simulation of Systems, Basel, 1989, pp. 7–14.
10.Cellier, F.E., Elmqvist, H., Otter, M., Modeling from physical principles, in The Control Handbook,
W.S. Levine (Ed.), CRC Press, pp. 99–108, 1996.
11.Gawthrop, P., Lorcan Smith, L., Metamodelling: Bond Graphs and Dynamic Systems, Prentice-Hall, NJ,
1996.
12.Van Amerongen, J., Modelling, simulation and controller design for mechatronic systems with 20-sim
3.0, in Proc. 1st IFAC Conf. on Mechatronic Systems, Darmstadt, Germany, September 2000, pp. 831–836.
13.Groenhuis, H., A Design Tool for Electromechanical Servo Systems, Ph.D. thesis, University of Twente,
1991.
14.Van Amerongen, J., Coelingh, H.J., de Vries, T.J.A., “Computer support for mechatronic control system
design,” Robotics and Autonomous Systems, vol. 30, no. 3, pp. 249–260, PII: SO921-8890 (99)00090-
1, 2000.
15.Van Amerongen, J., van der Klugt, P.G.M., van Nauta Lemke, H.R., Rudder roll stabilization for ships,
Automatica, vol. 26, no. 4, pp. 679–690.
16.Arimoto, S., A brief history of iterative learning control, in Iterative Learning Control: Analysis, Design,
Integration and Applications, Kluwer Academic Publishers, pp. 3–7, 1988.
17.De Vries, T.J.A., Velthuis, W.J.R., van Amerongen, J., Learning feed-forward control: a survey and
historical note, in 1st IFAC Conf. on Mechatronic Systems, Darmstadt, Germany, September 2000,
pp. 949–954.

©2002 CRC Press LLC