Novel resilient state estimation method for process control in cyber-
physical systems
Scientists create a new process control model to protect systems from assailants and natural fluctuations

Date:
August 20, 2021
Source:
DGIST (Daegu Gyeongbuk Institute of Science and Technology)
Summary:
A new process control method uses a special mathematical structure
to accurately estimate the internal process variables of a system,
even when external sensors are damaged.



FULL STORY ==========================================================================
Be it nuclear power plants, patient monitoring equipment in hospitals,
or self- driving cars -- integrations of physical processes with
computers and process control, or cyber-physical systems (CPS), are
everywhere. However, the widespread application of CPS also makes them
prime targets for hackers. A simple change in the value of a sensor can
create havoc. Vulnerability to malicious attacks has created the need for systems that can withstand the corruption of sensors and still provide
safe and efficient process control.


==========================================================================
In a recent study published in IEEE Transactions on Automatic Control, Professor Yongsoon Eun from Daegu Gyeongbuk Institute of Science and Technology, and his colleague from Hyundai Motor Company, Yechan Jeong,
have developed a method for resilient state estimation (RSE) for systems
that are under attack. State estimation refers to the use of external variables, i.e., sensor readings, to determine the internal state of the
system using mathematical models called "observers." This is a critical
step in process control. When the internal state of a system can be
determined despite the corruption of sensors, it is called RSE.

"Would you ride an autonomous vehicle or live near a computer-controlled
power plant if safety and security were not considered in their
design? The importance of resiliency in control systems has been
recognized for over a decade." explains Prof. Eun.

All control systems are subject to variations or "disturbances" in
the process, which cause errors in state estimation. However, as the disturbance increases, so does the error, leading to a breakdown in
system resiliency. Making use of a kind of observer known as "Unknown
Input Observer (UIO)," the new RSE method overcomes this limitation and provides a way for state estimation that can withstand both malicious
attacks as well as external disturbances.

In this method, a UIO is designed for each sensor, the estimates from
each UIO are combined, and the error is processed to provide the true
value of the internal state of the system. The benefit of using a UIO
is that its estimation error always converges to zero, regardless of
external disturbances to the process. This is unlike other observers,
which can only provide a range for estimation error. Another novelty of
this method is that it deploys a 'partial state UIO,' a technique newly developed by Prof. Eun's team, by which as much partial information
on internal states as possible is extracted from each sensor when full
state information extraction is not feasible. This greatly expands the applicability of the new RSE method based on UIO.

"The proposed method gives a system a level of tolerance for faults and
attacks and, in cases where it is inevitable, allows graceful degradation
of system functionality. This makes it crucial to the design of CPS,"
concludes Prof.

Eun.

========================================================================== Story Source: Materials provided by DGIST_(Daegu_Gyeongbuk_Institute_of_Science_and Technology). Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Yechan Jeong, Yongsoon Eun. A Robust and Resilient State Estimation
for
Linear Systems. IEEE Transactions on Automatic Control, 2021;
1 DOI: 10.1109/TAC.2021.3088780 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/08/210820093412.htm

--- up 15 weeks, 22 hours, 45 minutes
* Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1:317/3)