Instrumentation and Measurement (Mechatronics)

Much of the research is related to measurement, control and signal processing, mainly considering applications in mechatronic, industrial, and robotic systems. A particular focus has been on the development of new digital tachometers for use in closed-loop control servo-systems and open loop measurement systems. These systems intrinsically involve the signal processing of quantized signals and work on these sensor-based measurement systems has been generalized to the analysis of the errors associated with DSP filters, when processing quantized signals. The visualization of robotic mechatronic and energy systems through the use of virtual reality software is a related area of active research. 


Sample Publications include: 

  • R. C. Kavanagh, “FIR differentiators for quantized signals,” IEEE Trans. Sig. Processing, vol. 49, no. 11, pp. 2713-2720, Nov. 2001. 

  •  G. O’ Donovan, R. C. Kavanagh, J. M. D. Murphy, M. G. Egan,  “Modular approach to parameter estimation in geared and linear resonant systems,” Control Engineering Practice,  vol. 12, no. 1, pp. 75-86, 2004

  •  R. C. Kavanagh, A. Jones, “New low-cost technique for accurate surface velocity measurement of a rotating drum,”  IEEE Trans. Instrum. Meas., vol 53, no. 2, pp. 416-422, Apr. 2004.

  •  N. Boggarpu, R. C. Kavanagh, “New learning algorithm for high-quality velocity measurement and control when using low-cost optical encoders,” IEEE Trans. Instrum. and Measurement, vol. 59, no. 3, pp. 565-574, Mar.  2010.

  •  R. F. Foley, R. C. Kavanagh, M. G. Egan, “Sensorless current estimation and sharing in multi-phase buck converters,” IEEE Trans. Power Electronics, vol. 25,  2010. 


Current PhD students:  

Xiaoli Yang 

Topic:  “Design of digital differentiators” 


Naveen Boggarpu 

Topic: “Improved kinematic sensing for motion control applications” 


James McGrath 

Topic: “Fusing diverse sources of remotely sensed data for automated mapping” 


Current Research Masters Student: 


Megan Flanders

“Virtual Reality Simulations of Dynamic Robotic Systems with Feedback Control”

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