application of control system

1. APPLICATIONS
OF
ARTIFICIAL INTELLIGENCE
IN
CONTROL SYSTEM
ANALYSIS AND DESIGN
PPT by - Samanyu B
Presented by
Jeevapandiyan S
Hamsa Priya K S

2. AGENDA
• Introduction​
• AI in Closed loop and open loop systems and its
applications
• AI in control system design and analysis
• Applications of AI in Control system
analysis and design​

3. INTRODUCTION
• With the rapid development of social economy and the
improvement of people's living standards, more and
more attention has been paid to the future development
of automizing control system with AI.
• Control systems have continuously evolved over
decades, and artificial intelligence technologies are
helping advance the next generation of some control
systems.
Applications of artificial Intelligence in Control system analysis and design 3

4. AI IN CLOSED AND OPEN LOOP
SYSTEMS
• Control Systems, particularly closed-loop control
systems (CLCS), are frequently used in production
machines, vehicles, and robots nowadays.
• Open loop systems, on the other hand mostly plays
a role in everyday process that we use
• Considering the control system design procedure and
the CLCS block diagram, AI can be applied in
different design steps and blocks. Thus, this Section
will first introduce AI for studying, modeling, and
scaling the real-world process which needs to be
controlled.

5. BLOCK DIAGRAM OF AN AI EMPOWERED CLCS MODEL
Applications of artificial Intelligence in Control system analysis and design 5
*ANN - Artificial
Neural Network

6. APPLICATIONS OF AI IN CLCS AND OLCS
Applications of artificial Intelligence in Control system analysis and design 6
OPEN LOOP SYSTEMS
CLOSED LOOP SYSTEMS
Tesla systems
have two AI
chips for better
safety and
performance on
the roads
The KUKA KR 360 FORTEC is
a heavy robotic arm with
outstanding reach and
precision, designed for
intelligent system concepts
SCARA
SCARA has an artificial
intelligence (AI), named
GORDON, which knows when and
where products are to be kept on
shelves

7. AI IN CONTROL SYSTEM DESIGN AND
ANALYSIS
• Before starting any control system design, the physical model of the process is
studied, modeled, scaled, and evaluated. These four steps are repeated until
the design model fits the real-world process, which needs to be controlled by
the control system
7
AI – empowered and based parameter fine tuning
:
• The advantage of AI-based, is that the probability distribution of process states
and the probability distribution of disturbance will be considered during training.
• A block diagram which uses AI for choosing optimal parameters is shown
below

8. BLOCK DIAGRAM SHOWING HOW AI CAN BE USED
FOR FINE TUNNING PARAMETERS
8
Applications of artificial Intelligence in Control system analysis and design

9. 9
Applications of artificial Intelligence in Control system analysis and design
• Here Artificial intelligence namely artificial neural networks are being used
• The data which was already pre-recorded from the process is fed to the AI ,
moreover the feedback output is also given as input to the AI
• The AI in turn , predicts what the outcome of the process would be and based on
that it choosed the most optimal model of parameters which will maximize efficiency

10. 10
• While designing control systems an important part of creating any
autonomous loop system is the controller. Eg:- PID controllers
• Again here AI can be used to replace the controller completely.
AI-BASED CONTROLLER:
• Going even a step further, the entire controller, i.e., in the block
diagram of Figure 5, a trained AI-based controller, most likely in the
form of an ANN-based controller, directly sets the control variables
based on the given reference value and the sensor input

11. 11
Applications of artificial Intelligence in Control system analysis and design
AI-BASED CONTROLLER
The challenging part of CLCS design with an
AI-based controller is now the training of AI.
Therefore, real-world data with the typical
process variance are needed and an unbiased
data set, covering all variance without bias

12. APPLICATIONS OF AI IN EVERYDAY CONTROL
SYSTEMS
12
Applications of artificial Intelligence in Control system analysis and design
Food manufacturing quality control:
• Maximizing product quality and minimizing off-spec product is a common goal for many
manufacturers. In this case, the expertise of human operators is needed to run equipment
at proper conditions.
• The AI-based solution and integrated on-line video analysis,
along with traditional process inputs, enable the creation of
a brain that controls multiple outputs simultaneously while
respecting the limits of the processing equipment.

13. 13
• Polymer production requires close control of
setpoints on the reactors
• Typical challenges involved in polymer
production includes transient control, especially
during change from one grade of polymer to
another
• The challenge here is also to control optimally
and deliver consistent outcomes as the
number of control variables is large, and many
times human experience is used.
CHEMICAL PROCESS CONTROL:
Applications of artificial Intelligence in Control system analysis and design
Tracking energy parameters in a dashboard can help
visualize optimization goals in a polymer production
plant
• And so, AI technology use can be extend to any complex
problem mentioned above that can be modeled using
simulations

14. THANK YOU
Any Queries?