Ultracapacitor modeling and control with discrete fractional order artificial neural network

In this article a new approach of using the discrete time fractional order artificial neural network controller for control of charging and discharging process for system with ultracapacitor is proposed. First, the discrete fractional order neural network for incommensurate non-linear system modeling is presented. After successful modeling of the system with ultracapacitor the neural network inverse controller, based on the presented configuration of fractional order neural network, is given. All the computer simulations are tested and compared with the results achieved on the physical device. Advantages of the proposed solution are described and discussed.

[1]  Dominik Sierociuk,et al.  Time domain validation of ultracapacitor fractional order model , 2010, 49th IEEE Conference on Decision and Control (CDC).

[2]  N. Retiere,et al.  Half-order modelling of supercapacitors , 2004, Conference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting..

[3]  A. Berthon,et al.  Artificial neural network control and energy management in 42 V DC link , 2005, 2005 European Conference on Power Electronics and Applications.

[4]  Dominik Sierociuk,et al.  Adaptive Feedback Control of Fractional Order Discrete State-Space Systems , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[5]  I. Podlubny.  Fractional differential equations , 1998 .

[6]  Dominik Sierociuk,et al.  Modeling of heat transfer process by using discrete fractional-order neural networks , 2011, 2011 16th International Conference on Methods & Models in Automation & Robotics.

[7]  Dominik Sierociuk,et al.  Comparison and validation of integer and fractional order ultracapacitor models , 2011 .

[8]  D. Sierociuk,et al.  Fractional Kalman filter algorithm for the states, parameters and order of fractional system estimation , 2006 .

[9]  J. J. Quintana,et al.  IDENTIFICATION OF THE FRACTIONAL IMPEDANCE OF ULTRACAPACITORS , 2006 .

[10]  Hamid Gualous,et al.  Supercapacitor thermal- and electrical-behaviour modelling using ANN , 2006 .

[11]  Chu-qi Su,et al.  Computer simulation study on ultracapacitor for electric vehicle , 2009, 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[12]  S. Westerlund,et al.  Capacitor theory , 1994 .

[13]  Y. Chen,et al.  Fractional Processes and Fractional-Order Signal Processing , 2012 .

[14]  Dominik Sierociuk,et al.  Some applications of fractional order calculus , 2010 .

[15]  K. B. Oldham,et al.  The Fractional Calculus: Theory and Applications of Differentiation and Integration to Arbitrary Order , 1974 .

[16]  Dominik Sierociuk,et al.  OBSERVER FOR DISCRETE FRACTIONAL ORDER STATE-SPACE SYSTEMS , 2006 .