New Piecewise Estimator Observer for Continuous Time Linear Systems with Sampled and Delayed Measurements
- 4 Downloads
This paper addresses the problem of sampled and delayed output measurements for continuous time linear systems. A novel observer design so-called piecewise estimator observer (PEO) is proposed to reconstruct the continuous system state without time delay. The PEO is composed of the current estimator and the piecewise continuous hybrid system. The main advantage of the proposed technique is further simple analysis and design, as well as less conservative to system parameters variation. Also it considered the sampling period in the observer design. Furthermore, at every sampling instant, the initial condition of the piecewise continuous hybrid system can be re-initialized which prevents the observation accumulation errors and achieves accurate results. In addition, comprehensive stability analysis of the observer is performed based on the linear matrix inequality. Moreover, the performance of the piecewise estimator observer is assessed with the delayed Luenberger observer and Kalman filter observer via a numerical example, and the simulation results are presented.
KeywordsSampled and delayed measurements Piecewise continuous hybrid systems Current estimator State estimation
Unable to display preview. Download preview PDF.
This work is partially supported by the National Natural Science Foundation of China (61773212, 61304077), by International Science and Technology Cooperation Program of China (2015DFA01710), by the Natural Science Foundation of Jiangsu Province (BK20170094), by the Chinese Ministry of Education Project of Humanities and Social Sciences (13YJCZH171), and by the 11th Jiangsu Province Six talent peaks of high level talents (2014_ZBZZ_005).
- 11.Ishii, I.; Nakabo, Y.; Ishikawa, M.: Target tracking algorithm for 1 ms visual feedback system using massively parallel processing. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 2309–2314 (1996)Google Scholar
- 12.Seuret, A.; Michaut, F.; Richard, J.-P.; Divoux, T.: Networked control using GPS synchronization. In: American Control Conference, p. 6 (2006)Google Scholar
- 14.Wang, H.P.; Vasseur, C.; Koncar, V.: Piecewise continuous systems used in trajectory tracking of a vision based x–y robot. In: Sobh, T., Elleithy, K., Mahmood, A., Karim, M.A. (eds.) Novel Algorithms and Techniques in Telecommunications, Automation and Industrial Electronics, pp. 255–260. Springer, London (2008)CrossRefGoogle Scholar
- 17.Hussein, M.T.; Söffker, D.: State variables estimation of flexible link robot using vision sensor data. In: 7th Vienna International Conference on Mathematical Modelling, pp. 193–198 (2012)Google Scholar
- 18.Hussein, M.T.: Vision-Based Control of Flexible Robot Systems. Ph.D. Thesis, Duisburg, Essen, Universität (2014)Google Scholar
- 20.Deng, L.; Janabi-Sharifi, F.; Wilson, W.J.: Stability and robustness of visual servoing methods. In: Proceedings of IEEE International Conference on Robotics and Automation ICRA’02, vol. 2, pp. 1604–1609 (2002)Google Scholar
- 21.Wu, H.; Chen, C.-C.; Feng, J.; Kühnlenz, K.; Hirche, S.: A switching control law for a networked visual servo control system. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), pp. 5556–5563 (2010)Google Scholar
- 25.Engell, S.; Frehse, G.; Schniederl, E.: Modelling, Analysis and Design of Hybrid Systems, vol. 279. Springer, Berlin (2003)Google Scholar
- 27.Koncar, V.; Vasseur, C.: Piecewise functioning systems: Bi-sampled controllers. Stud. Inform. Control 11(2), 185–198 (2002)Google Scholar
- 29.Unbehauen, H.: Control Systems. Robotics and Automation. EOLSS, Oxford (2009)Google Scholar