A Fuzzy Networked Control System Following Frequency Transmission Strategy

  • Héctor Benítez-Pérez IIMAS UNAM Cto. Escolar 3000, C. U., México D. F.
  • Jorge Ortega-Arjona Facultad de Ciencias UNAM Av. Universidad 3000, C. U., México D. F.
  • Oscar Esquivel-Flores IIMAS UNAM Cto. Escolar 3000, C. U., México D. F.
  • Jared A. Rojas-Vargas
  • Andrés Álvarez-Cid Facultad de Ingeniería UNAM Av. Universidad 3000, C.U., México D. F.

Abstract

At present, network control systems employ a common approximation to solve the connectivity issue due to time delays coupled with external factors . However, this approach tends to be complex in terms of time delays, and the inherent local phase is missing. Therefore, it is necessary to study the behavior of the delays as well as the integration of the differential equations of these bounded delays. The related time delays need to be known a priori, but from a dynamic real-time perspective in order to understand the dynamic phase behavior. The objective of this paper is to demonstrate the inclusion of the data frequency transmission and time delays that are bounded as parameters of the dynamic response from a real-time scheduling approximation, considering the local phase situation. The related control law is designed considering a fuzzy logic approximation for nonlinear time delays coupling. The main advantage is the integration of this behavior through extended state space representation. This keeps certain linear and bounded behavior leading to a stable situation during an events presentation, based on an accurate data transmission rate. An expected result is that the basics of the local phase missing as a result of the local bounded time delays from the lack of tide synchronization conforms to the modeling approximation.

References

[1] Benítez-Pérez, H.; Benítez-Pérez A.; Ortega-Arjona J. (2012); Networked Control Systems Design considering Scheduling Restrictions and Local Faults using Local State Estimation, Accepted in In- ternational Journal of Innovative Computing, Information and Control (IJICIC).

[2] Benítez-Pérez, H.; García-Nocetti F. (2005); Reconfigurable Distributed Control, Springer Verlag.

[3] Blanke, M. et al. (2003); Diagnosis and Fault Tolerant Control, Springer.
http://dx.doi.org/10.1007/978-3-662-05344-7

[4] Branicky, M. et al. (2003); Networked control system co-simulation for co-design, Proc. American Control Conf, 4:3341-3346.

[5] Cervin, A. et al. (2003); How Does Control Timing Affect Performance? Analysis and Simulation of Timing Using Jitterbug and TrueTime, IEEE Control Systems Magazine, 23(3):16-30.
http://dx.doi.org/10.1109/MCS.2003.1200240

[6] Benítez-Pérez, H. et al. (2012); Bounded Communication Between Nodes in a NCS as a Strategy of Scheduling Approximation, International Journal on Parallel Emergent and Distributed Systems, 27(6):481-502.
http://dx.doi.org/10.1080/17445760.2012.717941

[7] Fridman, E.; Shaked, U. (2003); Delay-dependent stability and H∞ control: constant and timevarying delays, International Journal Control, 76(1):48-60
http://dx.doi.org/10.1080/0020717021000049151

[8] Izadi, Z. R.; Blanke, M. (1999); A Ship Propulsion System as a Benchmark for Fault-Tolerant Control, Control Engineering Practice, 7:227-239.
http://dx.doi.org/10.1016/S0967-0661(98)00149-X

[9] Jiang, J.; Zhao, Q. (1999); Reconfigurable Control Based on Imprecise Fault Identification, Procedings of the American Control Conference, IEEE, San Diego, 114-118.

[10] Kim, D. et al (2002); Maximum allowable delay bounds of networked control systems.Control Engineering Practice, 11:1301-1313.
http://dx.doi.org/10.1016/S0967-0661(02)00238-1

[11] Lian, F. et al (2001); Time delay modelling and sample time selection for networked control systems, Proceedings of ASME-DSC, XX.

[12] Lian, F. et al (2002); Network design considerations for distributed networked for distributed control systems, IEEE Transactions on Control Systems Technology, 10(2):297-307.
http://dx.doi.org/10.1109/87.987076

[13] Liu, C.; Layland, J. (1973); Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment, Journal of the Association for Computing Machinery, 20(1):46-61.
http://dx.doi.org/10.1145/321738.321743

[14] Méndez-Monroy P.E.; Benítez-Pérez, H. (2009); Supervisory Fuzzy Control for Networked Control Systems, International Journal Innovative Computing, Information and Control Express Letters, ICIC-EL, 233-240.

[15] Menendez, A., Benítez-Pérez, H. (2010); Scheduling strategy for Real-Time Distributed Systems. Journal of Applied Research and Technology, 8(2):177-185.

[16] Nilsson, J. (1998); Real-Time Control with Delays, PhD. Thesis, Department of Automatic Control, Lund Institute of Technology, Sweden.

[17] Benítez-Pérez, H. et al. (2010); Reconfigurable Fuzzy Takagi Sugeno Model Predictive Control Networked Control (Magnetic Levitation Case Study). Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 224(8):1022-1032.

[18] Tanaka, K.; Wang, H.O. (2001); Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, New York, Wiley.

[19] Thompson, H. (2004); Wireless and Internet Communications Technologies for monitoring and Con- trol, Control Engineering Practice, 12:781-791.
http://dx.doi.org/10.1016/j.conengprac.2003.09.002

[20] Walsh, G.C. et al. (1999); Stability Analysis of Networked Control Systems, Proc. American Control Conference, San Diego, USA, 2876-2880.
http://dx.doi.org/10.1109/acc.1999.786599

[21] Wang, Y.; Sun, Z. (2007); Control of Networked Control Systems Via LMI Approach, International Journal of Innovative Computing, Information and Control, 3(2).

[22] Zhang, H. et al. (2007); Guaranteed cost networked control for T-S fuzzy system switch time delays, IEEE Transactions on Systems Man and Cybernetics part C: Applications and Reviews, 37(2):160- 172.
http://dx.doi.org/10.1109/TSMCC.2006.886983

[23] Zhu, X. et al.(2008); State Feedback Control Design of Networked Control Systems with Time Delay in the Plant, International Journal of Innovative Computing, Information and Control, 4(2):283-290.

[24] Quanser Inc. (2006); 2-DOF Helicopter Reference Manual Quanser Innovate Educate.

[25] Quanser Inc. (2006); Magnetic Levitation Experiment, Quanser Consulting.
Published
2015-11-16
How to Cite
BENÍTEZ-PÉREZ, Héctor et al. A Fuzzy Networked Control System Following Frequency Transmission Strategy. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 11, n. 1, p. 11-25, nov. 2015. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/2158>. Date accessed: 11 july 2020. doi: https://doi.org/10.15837/ijccc.2016.1.2158.

Keywords

Fuzzy networks control (FNC), frequency control, local phase challenge