Modeling and control of smart materials-based actuators and their applications

In recent years, as a result of rapid development in the fields of aerospace, optics, telecommunication, etc., demands for ultraprecision devices have been ever-increasing. A practical solution to achieve ultraprecision devices is to integrate piezo actuators and sensors  into the structure and to develope a methodology for control the accuracy of the device. Piezo materials belong to a class of so called smart materials that are capable of changing their physical properties, such as the shape, in response to an externally applied stimulus. In comparison with traditional electric motors, the smart material-based actuators have the advantages of lightness, low noise levels, low power requirements and high reliability. Therefore, they are widely used in applications of micro/nano-robots, micro-manipulation and micro/nano positioning stage. However, their characteristics (nonlinearities, badly damped vibrations, etc.) require the use of advanced control techniques. In addition to these characteristics, the particularity of working at the micro/nano-scale makes their  control even more challenging.

The current research work is control of multiple piezoelectric actuators (PEAs) in Fabry-Perot spectrometer (FPS).  The FPS can provide multispectral mappings for research on atmospheric science and planetary mineralogy, such as measuring the Earth’s O2-A band, aerosol, surface albedo, and pressure. The developed FPS uses three PEAs to provide spectral tuning of the desired optical signal transmittance by selecting the gap spacing of a tuneable optical filter. The PEAs are required to be controlled at nanometer steps with high accuracy.

One challenge we are currently working on at OVGU is the implementation of the inverse compensator for the Preisach model in F-P system. If the Preisach model is utilized to describe the hysteresis effect, it requires at least more than 10K elementary relay operators. The inverse compensator is built based on the model, which also needs more than 10K relay operators. Therefore, it causes the implementation problem when implementing the inverse compensator. To overcome this problem, we applied the model order reduction approach to reduce the number of  the relay operators in the Preisach model. In our current work, we have successfully used 200 relay operators to describe the hysteresis effect and at the same time to preserve the model accuracy. This work has been published in IEEE Transactions on Industrial Electronics (Impact factor: 7.168).  The next step will be applying the proposed approach to construct the inverse compensator for the three PEAs in the F-P system.