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.

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

Soft Computing

Fuzzy LogicNeural

NetworkEvolutionary

Algorithm (GA)

Neural Network• Based on biological nervous system.

• It has an architecture that tries to mimic brain

mechanics to simulate intelligent behavior.

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.

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.

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.

Fuzzy Logic Controller

Simulink Model

Rule Base

Response

ComparisonResponse 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

ANFIS Model

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.

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.

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.•

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