Control of hysteresis: theory and experimental results

By Xiaobo Tan, R. Venkataraman, Perinkulam S. Krishnaprasad. SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2001

137 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials

View Paper: https://www.semanticscholar.org/paper/56242b6cc0c0780e41ead8a76aa49a53b0bdad75

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Kam K. Leang
2. Qingze Zou
3. Santosh Devasia
4. John S. Baras
5. Xiaobo Tan
6. Andrew J. Fleming
7. Chun-Yi Su
8. S. O. Reza Moheimani

In Electrical and Electronic Engineering

1. Kam K. Leang
2. Santosh Devasia
3. John S. Baras
4. Qingze Zou
5. Xiaobo Tan

In Electronic, Optical and Magnetic Materials

1. Kam K. Leang
2. Santosh Devasia
3. John S. Baras
4. Qingze Zou
5. Xiaobo Tan

Citations in the corpus

• Feedforward control of piezoactuators in atomic force microscope systems (2009, methodology): “Several approaches are available for estimating the Preisach weighting surface μ(·, ·) from the data [35], [37].”
• Modeling and control of hysteresis in magnetostrictive actuators (2004, methodology): “…of the magnetostrictive rod were considered to be the origin of the rate-dependent hysteresis in Venkataraman (1999), where the eddy current losses were modeled by placing a resistor in parallel with a hysteretic inductor and the magnetoelastic dynamics was modeled by a second-order linear system.”
• Design of hysteresis-compensating iterative learning control for piezo-positioners: Application to atomic force microscopes (2006, methodology): “The modeling process To isolate the hysteresis behavior, we need to account for creep and vibration effects [13,28].”