Control systems engineering applies control theory to design systems that achieve desired behaviors. Soft computing techniques, such as fuzzy logic, neural networks, and genetic algorithms, resemble biological processes more closely than traditional techniques for solving computationally difficult tasks. This document presents a case study on using a fuzzy logic controller for speed control of a DC motor. Simulation results show the fuzzy logic controller provides better performance than PID controllers, with faster rise time, shorter settling time, and no overshoot. Soft computing approaches thus provide effective intelligent control systems with advantages like not requiring complex math and giving real-time expert control.

2. Introduction
• Control engineering or control systems engineering is
the engineering discipline that applies control theory to
design systems with desired behaviors. The practice
uses sensors to measure the output performance of the
device being controlled and those measurements can
be used to give feedback to the input actuators that
can make corrections toward desired performance.
• A control system is a device, or set of devices, that
manages, commands, directs or regulates the behavior
of other devices or systems.

3. Soft Computing
Approach to CSE
• Generally speaking, soft
computing techniques
resemble biological processes
more closely than traditional
techniques.
• In computer science, soft
computing is the use of
inexact solutions to
computationally hard tasks

4. Soft Computing
Fuzzy Logic
Neural
Network
Evolutionary
Algorithm (GA)

5. Neural Network
• Based on biological nervous system.
• It has an architecture that tries to mimic brain
mechanics to simulate intelligent behavior.

6. Fuzzy Logic
• Fuzzy logic attempts to systematically and
mathematically emulate human reasoning and decision
making.
• Fuzzy logic represents an excellent concept to close the
gap between human reasoning and computational
logic.
• Variables like intelligence, credibility, trustworthiness and
reputation employ subjectivity as well as uncertainty.

7. Genetic Algorithm
• Genetic algorithms (GAs) are stochastic
optimization methods based loosely on the
concepts of natural selection and evolution
process.
• Genetic algorithms
• (GAs) are the solution for optimization of hard
problems quickly, reliably and accurately.

8. A Case Study: Speed
Control of A DC Motor
• Speed control means intentional change of the drive
speed to a value required for performing the specific
work process.
• Speed control is either done manually by the operator
or by means of some automatic control device.

9. Fuzzy Logic Controller

10. Simulink Model

11. Rule Base

12. Response

13. Comparison
Response Without PID With PID Fuzzy
Rise Time (sec) 1.1362 0.7195 0.1
Settling Time (sec) 2.9 1.6587 0.6
Dead time (sec)
0 1 0
Peak Time (sec)
5.2388 0.2337 0
Overshoot (sec)
8.7813
0.15 0

14. ANFIS Model

15. Advantages of Soft
Computing Approach to
CSE
• Doesn’t need any difficult mathematical
calculation.
• It gives better performance than any other method.
• It is a real time expert system.
• Intelligent control systems can be made.

16. Other Application &
Future Scope
• Intelligent control of motor systems like DC servo
motor, Induction motor etc.
• Intelligent control in oil refineries.
• Use of intelligent control systems in power plants.
• Power systems applications.
• Development of smart grids using intelligent control
system.

17. Conclusion
• Due to lack in comprehensibility, conventional controllers are often
inferior to the intelligent controllers. Soft computing techniques provide
an ability to make decisions and learning from the reliable data or
expert’s experience. Moreover, soft computing techniques can cope
up with a variety of environmental and stability related uncertainties.
• There is a wide range scope of applications of high performance DC
motor drives in area such as rolling mills, chemical process, electric
trains, robotic manipulators and the home electric appliances. They
require speed controllers to perform tasks. Hence, a fuzzy based DC
motor speed control system method gives a smooth speed control
with less overshoot and no oscillations.
• When compared to conventional controllers, SC approach provides
better control.
•

18. References
• J.S.R. Jang, C.T. Sun, E. Mizutani, “Neuro- Fuzzy and
Soft Computing”
• Zadeh, Lotfi A., "Fuzzy Logic, Neural Networks, and
Soft Computing," Communication of the ACM,
March 1994, Vol. 37 No. 3, pages 77-84.
• X. S. Yang, Z. H. Cui, R. Xiao, A. Gandomi, M.
Karamanoglu, Swarm Intelligence and Bio-Inspired
Computation: Theory and Applications, Elsevier,
(2013).
• Wikipedia.com