"Soft Sensing in Monitoring and Control"
A Special of the Journal of Sensors

With the development of measurement and data storage facilities,
variables of industrial processes are measured routinely by hardware
sensors and stored in real time. However, some properties are
difficult to measure and usually unavailable in real time, leading to
major difficulty in controlling product quality, although they are
important for monitoring and control. Soft sensors, as inferential
estimators, can draw conclusions on specific variables from process
observations on one or more other variables. To estimate these
unmeasured variables, first principles modeling is difficult due to
complex reactions and a large number of related variables.
Alternatively empirical models and data driven models can be employed
to estimate these unmeasured variables without looking into the
physical insight about the underlying process and thus obtained more
applications. Particularly, data-based multivariate statistical
methods and dynamic modeling techniques can be used to build soft
sensors. Soft sensing technology has been used to solve many problems,
such as performance monitoring, sensor validation, fault detection,
and process control.
The main focus of this special issue will be on the new and existing
soft sensor methodology and applications in monitoring and control,
whose goal is to observe a wide variety of usage of soft sensors in
various fields. The special issue will become an international forum
for researchers to summarize the most recent developments and ideas in
the field, with a special emphasis given to the technical and
application results obtained within the last decade. Potential topics
include, but are not limited to:

- Review of soft sensing technology
- Soft sensing models and their validation
- Data selection and choice of model structure
- Data reconciliation and gross error detection
- Heterogeneous multisensor fusion
- Multirate multisensor fusion
- Distributed soft sensing
- Fault tolerant soft sensing
- Adaptive soft sensing
- Robustness and uncertainty of soft sensing
- Data structure for soft sensing
- Mathematical tools for soft sensing
- Database and knowledge base used for soft sensing
- Industrial design methodology of soft sensing systems
- Optimal design of soft sensing systems
- Inferential control based on soft sensing
- Performance assessment methods for soft sensing systems
- Soft sensing in image systems
- Application of Kalman filters in soft sensing
- Successful applications

Before submission authors should carefully read over the journal's
Author Guidelines, which are located at Prospective authors
should submit an electronic copy of their complete manuscript through
the journal Manuscript Tracking System at according to the
following timetable:

Manuscript Due: Friday, 10 May 2013
First Round of Reviews: Friday, 2 August 2013
Publication Date: Friday, 27 September 2013

Lead Guest Editor:
- Fan Yang, Department of Automation, Tsinghua University, Beijing 100084, China

Guest Editors:
- Sirish L. Shah, Department of Chemical and Materials Engineering,
University of Alberta, Edmonton, AB, Canada T6G 2G6
- Deyun Xiao, Department of Automation, Tsinghua University, Beijing
100084, China
- Arun K. Tangirala, Department of Chemical Engineering, IIT Madras,
Chennai, Tamil Nadu 600036, India