2015 |
Osama Hassanein / Sreenatha G. Anavatti / Hyungbo Shim / S. A. Salman Auto-generating Fuzzy System Modelling of Physical Systems Proceedings Article In: Proc. of 2015 IEEE Conference on Control Applications, pp. 1142-1147, IEEE, Sydney, NSW, Australia, 2015. Abstract | Links | BibTeX | Tags: Nonlinear system @inproceedings{HassaneinAnavattiShimSalman15, Nonlinear system identification has gained importance over the years as enhancement tool that can improve control design and performance significantly. This is particularly true for systems with non-linearity and unmodelled disturbances. This paper proposes an Auto-Generating Fuzzy System Modelling mechanism (AGFSM) with online tuning capability. The proposed mechanism offers a universal black-box modelling tool for any system, linear or nonlinear, regardless of any prior knowledge of the physical relationship inside the system or the system behaviour. The proposed mechanism comprises of two phases, a structure-generating phase and a parameter-learning phase. Structure generating phase is based on the entropy measure used to control the model accuracy. Parameter learning phase is based on supervised learning algorithms using the back propagation algorithm. The proposed AGFSM mechanism is used to develop the models of both linear and nonlinear systems using input-output data. |
2004 |
Young Ik Son / Hyungbo Shim / Jin Heon Seo A dynamic output feedback control law for elastic joint robots via feedback-passivity approach Journal Article In: Journal of the Franklin Institute, vol. 341, no. 6, pp. 477-490, 2004, ISSN: 0016-0032. Abstract | Links | BibTeX | Tags: Nonlinear system @article{SonShimSeo04, Motivated by recent dynamic output feedback passivation results, a new set-point control law is presented for an elastic joint robot when the velocity measurements are not available. The proposed methodology designs an additional dynamics with which the parallel-connected system is feedback passive. That is, the composite nonlinear robot system has relative degree one with a new output and its zero-dynamics subsystem becomes the virtual closed-loop system with a simple proportional-derivative (PD) control law. This approach provides an alternative way of replacing the role of the velocity measurements for the PD law. With the proposed control law, the transfer function of the additional system has the form of sG(s) with a strictly positive real (SPR) G(s). Robustness analysis is also given with regard to uncertainties on the robot parameters. The performance of the proposed control law is illustrated in the simulation studies of a manipulator with three revolute elastic joints. |
List of English Publication
2015 |
Auto-generating Fuzzy System Modelling of Physical Systems Proceedings Article In: Proc. of 2015 IEEE Conference on Control Applications, pp. 1142-1147, IEEE, Sydney, NSW, Australia, 2015. |
2004 |
A dynamic output feedback control law for elastic joint robots via feedback-passivity approach Journal Article In: Journal of the Franklin Institute, vol. 341, no. 6, pp. 477-490, 2004, ISSN: 0016-0032. |