Characteristic model based all-coefficient adaptive control of an AMB suspended energy storage flywheel test rig

Feedback control of active magnetic bearing (AMB) suspended energy storage flywheel systems is critical in the operation of the systems and has been well studied. Both the classical proportional-integral-derivative (PID) control design method and modern control theory, such as H∞ control and μ-synthesis, have been explored. PID control is easy to implement but is not effective in handling complex rotordynamics. Modern control design methods usually require a plant model and an accurate characterization of the uncertainties. In each case, few experimental validation results on the closed-loop performance are available because of the costs and the technical challenges associated with the construction of experimental test rigs. In this paper, we apply the characteristic model based all-coefficient adaptive control (ACAC) design method for the stabilization of an AMB suspended flywheel test rig we recently constructed. Both simulation and experimental results demonstrate strong closed-loop performance in spite of the simplicity of the control design and implementation.

[1]  Guo Li,et al.  Characteristic model based control of the X-34 reusable launch vehicle in its climbing phase , 2009, Science in China Series F: Information Sciences.

[2]  Brian T. Murphy,et al.  Analysis and Testing of a Magnetic Bearing Energy Storage Flywheel With Gain-Scheduled, MIMO Control , 2000 .

[3]  G. Schweitzer,et al.  Magnetic bearings : theory, design, and application to rotating machinery , 2009 .

[4]  Zongli Lin,et al.  Design, Construction, and Modeling of a Flexible Rotor Active Magnetic Bearing Test Rig , 2012, IEEE/ASME Transactions on Mechatronics.

[5]  Yefa Hu,et al.  A platform for analysis and control design: Emulation of energy storage flywheels on a rotor-AMB test rig , 2016 .

[6]  Duoqing Sun Stability analysis of golden-section adaptive control systems based on the characteristic model , 2016, Science China Information Sciences.

[7]  Hongxin Wu,et al.  A framework for stability analysis of high-order nonlinear systems based on the CMAC method , 2016, Science China Information Sciences.

[8]  Zongli Lin,et al.  Control of a flexible rotor active magnetic bearing test rig: a characteristic model based all-coefficient adaptive control approach , 2014 .

[9]  Concha M. Reid,et al.  History of Electrochemical and Energy Storage Technology Development at NASA Glenn Research Center , 2013 .

[10]  Hairong Dong,et al.  Characteristic model-based all-coefficient adaptive control for automatic train control systems , 2013, Science China Information Sciences.

[11]  Robert E. Hebner,et al.  Flywheel batteries come around again , 2002 .

[12]  Haibo Ji,et al.  Characteristic model based adaptive controller design and analysis for a class of SISO systems , 2015, Science China Information Sciences.

[14]  J. G. Bitterly,et al.  Flywheel technology: past, present, and 21st century projections , 1998 .

[15]  Jun Hu,et al.  Characteristic Model-Based All-Coefficient Adaptive Control Method and Its Applications , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[16]  Kamal Al-Haddad,et al.  A comprehensive review of Flywheel Energy Storage System technology , 2017 .

[17]  Bin Meng,et al.  Characteristic model-based control of robotic manipulators with dynamic uncertainties , 2015, Science China Information Sciences.

[18]  Bangcheng Han,et al.  Frequency-varying synchronous micro-vibration suppression for a MSFW with application of small-gain theorem , 2017 .

[19]  K. Mclallin,et al.  Magnetic Circuit Model of PM Motor-Generator to Predict Radial Forces , 2004 .

[20]  Zongli Lin,et al.  Modeling of a High Speed Rotor Test Rig With Active Magnetic Bearings , 2006 .

[21]  Jun Hu,et al.  Theory and Applications of Characteristic Modeling : An Introductory Overview , 2014 .

[22]  Osama Mohammed,et al.  Energy Storage Technologies for High-Power Applications , 2016, IEEE Transactions on Industry Applications.

[23]  Saifur Rahman,et al.  Flywheel Energy Storage Systems for Ride-through Applications in a Facility Microgrid , 2012, IEEE Transactions on Smart Grid.

[24]  Kenzo Nonami,et al.  Low Power Consumption Nonlinear Control with H∞ Compensator for a Zero-Bias Flywheel AMB System , 2004 .

[25]  J. G. Bitterly,et al.  Flywheel technology past, present, and 21st Century projections , 1997, IECEC-97 Proceedings of the Thirty-Second Intersociety Energy Conversion Engineering Conference (Cat. No.97CH6203).

[26]  Albert F. Kascak,et al.  Stabilizing Gyroscopic Modes in Magnetic-Bearing-Supported Flywheels by Using Cross-Axis Proportional Gains , 2013 .

[27]  Markus Ahrens,et al.  Performance of a magnetically suspended flywheel energy storage device , 1996, IEEE Trans. Control. Syst. Technol..

[28]  Timothy P. Dever,et al.  Modeling and Development of a Magnetic Bearing Controller for a High Speed Flywheel System , 2004 .

[29]  Haoran Zhao,et al.  Review of energy storage system for wind power integration support , 2015 .

[30]  Hedayat Saboori,et al.  Emergence of hybrid energy storage systems in renewable energy and transport applications – A review , 2016 .