[robotics-worldwide] [Journals][CfP] Special Issue on "Hysteresis Systems: Characterization, Modelling, and Control"

dothanhnho thanh4 at e.ntu.edu.sg
Sun Nov 27 14:26:11 PST 2016

Dear Colleagues, 

We apologize for multiple copies of this message and are pleased to announce
the Call for paper for Special Issue on "*Hysteresis Systems:
Characterization, Modelling, and Control*"

Please see all the details below

<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.hindawi.com_journals_mpe_si_713568_cfp_&d=DgIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=32qEzQHmO2hBh6Zw7E5VJebo83cI-bzL3VuQfd-klUQ&s=zQeRFttMPtQHKHgt4gSKGvAwvyM563w1TTKJVB3eFZg&e= >  

Special Issue on "*Hysteresis Systems: Characterization, Modelling, and
Call for Papers

Hysteresis system is commonly characterized by the memory effect, where the
effects of input to the system are experienced with a certain delay in time
and the response does not only depend on the input and output at the current
instant but also depend on the history of the input and output. This
phenomenon is originated from magnetic, ferromagnetic, and ferroelectric
materials and microsliding friction. It is like the elastic property of
materials in which a lag occurs between the application and the removal of a
force or field and its subsequent effect.

Hysteresis phenomenon might lead to performance degradation, for example, in
positioning applications, where the systems involve the nonlinearity. If
this phenomenon is neglected, it will give rise to inaccuracy in open loop
control and degrades the tracking performance of the system. In a worse
case, it could cause undesirable oscillations in the system which could even
lead to instability in the closed loop.

The hysteresis phenomenon might exhibit complex behaviours due to its memory
effect. This leads to a need of memory stacking in some hysteresis models.
Many different models have tried to capture this behaviour, ranging from
physics approach and phenomenological approach until black-box approach. An
example of the first approach can be seen in generic models that capture
some physical properties of the system, which includes stochastic properties
of surface asperities, which are used to model hysteresis in frictional
forces. On the other hand, disregarding the physical properties, some models
are used to represent the input-output relationship using NARX (nonlinear
autoregressive exogenous) or NARMAX (nonlinear autoregressive-moving-average
model with exogenous inputs). These examples represent the latter class of
the black-box approach. In between, there are also some models that try to
mathematically capture the hysteresis behaviour from its physical
properties. Some examples of this class are Preisach’s, Maxwell-slip, or
Bouc-Wen models.

In order to compensate for the error in a system due to a hysteresis
phenomenon, accurate models, identification strategy, and effective control
are prerequisite. As a consequence of the complex behaviour of hysteresis,
linear control strategies are generally unsuitable for providing an optimal
performance. If an accurate model of the system using any of the three
aforementioned approaches is available, a compensation of the error in the
system can be made easily by implementing model-based controllers. However,
in some cases, complete characterization of the hysteresis phenomenon on the
system is not available. Some nonlinear and adaptive control strategies have
been sought to be a potential answer to the problem. Sliding mode, adaptive
backstepping, disturbance observer and gain-scheduling are a few among many
nonlinear controllers to deal with the problem.

This special issue journal focusses on a mathematical analysis of some
systems that involve hysteresis such as in smart materials, magnetic fields,
or microsliding friction where hysteresis is dramatically represented as
compared to other (geometric nonlinear) systems. This includes original
theoretical work and application-based studies on hysteresis encompassing
all phenomena associated with mechanical, structural, civil, aeronautical,
ocean, electrical, and control systems.

All manuscripts are prereviewed by the editors, and if appropriate, sent for
blind peer review. Contributions must be original, not previously or
simultaneously published elsewhere, and are critically reviewed before they
are published.

*Potential topics include but are not limited to the following*:

Developments of hysteresis and backlash models for mechatronic, electronic,
and robotic systems
Identification techniques for the hysteresis and backlash models
Signal processing technique for hysteresis and backlash systems
Compensation control of systems with hysteresis and backlash
Ferroelectric materials
Frictional hysteresis
Hysteresis systems and stability theory
Hysteresis nonlinearity modelling and identification with backlash
Hysteresis and backlash in magnetic, ferromagnetic, and pneumatic actuators,
piezoelectric materials, shape memory alloy, thermal systems cable-driven
systems, and flexible and stretchable sensors/actuators
Hysteresis and backlash in electronic systems, mechatronics, and robotics
Authors can submit their manuscripts through the Manuscript Tracking System
at  https://urldefense.proofpoint.com/v2/url?u=http-3A__mts.hindawi.com_submit_journals_mpe_hs_&d=DgIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=32qEzQHmO2hBh6Zw7E5VJebo83cI-bzL3VuQfd-klUQ&s=EKDCZyoFHZAr9cWHdS3EeGIGFBNgdfpaUYRZArfMfLM&e= 
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**Important date**
Manuscript Due:	Friday, 3 March 2017
First Round of Reviews: Friday, 26 May 2017
Publication Date:	Friday, 21 July 2017

*Lead Guest Editor*
*Tegoeh Tjahjowidodo*, Nanyang Technological University, Nanyang, Singapore

*Guest Editors*
*Michael L. W. Shing*, Newcastle University, Newcastle, UK
*Thanh N. Do*, University of California, Santa Barbara, USA

I look forward to see your paper(s) being submitted.

Best regards,
Dr. Thanh Nho Do, California NanoSystems Institute, UC Santa Barbara, CA,

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