Fuzzy Control to Improve Energy-Economizing in Cyber-Physical Systems

ABSTRACT Energy-supply issues constitute one of the most important issues that we face nowadays. Before a viable alternative energy source of supply is discovered and implemented, saving energy is essential. To improve the energy economizing of actuators, this work proposes a method based on fuzzy logic for scheduling and controlling electrical operators in a cyber-physical system. With the feedbacks of sensor data including output of process and the environmental variations, the intelligent controller can gather the current situation and predicted trend. After analyzing the data with the fuzzy rule, the actuators are controlled with the consideration of the desired set point and energy economizing. The results of a simulation reveal that the fuzzy control method for actuators in a cyber-physical system can be used to minimize the power consumption of the system while accomplishing the desired set point.

[1]  R. Sharapov,et al.  Convergence of genetic algorithms , 2006, Pattern Recognition and Image Analysis.

[2]  Sang Hyuk Son,et al.  The case for feedback control real-time scheduling , 1998, Proceedings of 11th Euromicro Conference on Real-Time Systems. Euromicro RTS'99.

[3]  N. Wiener,et al.  Behavior, Purpose and Teleology , 1943, Philosophy of Science.

[4]  Robert Sabatier,et al.  A New Stopping Criterion for Genetic Algorithms , 2016, IJCCI.

[5]  Wayne H. Wolf,et al.  Cyber-physical Systems , 2009, Computer.

[6]  N. Andrei Modern Control Theory-A historical perspective - , 2006 .

[7]  Tzuu-Hseng S. Li,et al.  Fuzzy target tracking control of autonomous mobile robots by using infrared sensors , 2004, IEEE Transactions on Fuzzy Systems.

[8]  By Radha Poovendran Cyber – Physical Systems : Close Encounters Between Two Parallel Worlds , 2010 .

[9]  Wenji Mao,et al.  Cyber-Physical-Social Systems for Command and Control , 2011, IEEE Intelligent Systems.

[10]  Guofang Gong,et al.  Self-tuning-parameter fuzzy PID temperature control in a large hydraulic system , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[11]  Haldun Aytug,et al.  Stopping Criteria for Finite Length Genetic Algorithms , 1996, INFORMS J. Comput..

[12]  R.C. Johnson,et al.  Introduction to adaptive arrays , 1982, Proceedings of the IEEE.

[13]  Boleslaw K. Szymanski,et al.  A middleware framework for market-based actuator coordination in sensor and actuator networks , 2008, ICPS '08.

[14]  Radha Poovendran,et al.  Cyber-Physical Systems: Close Encounters Between Two Parallel Worlds [Point of View] , 2010, Proc. IEEE.

[15]  Feng Xia,et al.  Feedback Scheduling of Priority-Driven Control Networks , 2008, Comput. Stand. Interfaces.

[16]  José M. F. Moura,et al.  Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.