Application of Soft Computing Techniques in Process Control System
Manjeet Kaur
Assistant Professor, ECE
Amity University Haryana
ABSTRACT:
Biological
Evolutionary
system (BES) is a special type of control
system that has shown strong robustness and
self-adaptability. In this synopsis report
biological evolutionary system is used to
develop
an
evolutionary
controller.
Evolutionary are stochastic optimization
techniques based on the principle of natural
evolution. The aim of this subject is to design a
speed controller for a DC motor by selection of
PID
parameters
using
“Evolutionary
Techniques.” These algorithms come under the
category
of
bio-inspired
optimization
techniques. The model of a DC motor is
considered as a second order system for speed
control. Here, there is a comparison between
conventional tuning methods and optimization
techniques of parameters for PID controller. In
some cases, it was found that the proposed PID
parameters adjusted by optimization technique
is better than the conventional techniques like a
Ziegler-Nichols’ method. These proposed
optimization methods could be applied for
higher order system also to provide better
system performance with minimum errors. It is
decided to create an objective function which
will evaluate the optimum PID gains based on
the controlled systems and overall error.
Drives that use electric motors as the prime
movers are known as electrical drives. There
are several advantages of electrical drives:
a. Flexible control characteristic –
This is particularly true when power electronic
converters are employed where the dynamic
and steady state characteristics of the motor can
be controlled by controlling the applied voltage
or current.
b. Available in wide range of
speed, torque and power
c. High efficiency, lower noise, low
maintenance
requirements
and
cleaner
operation
d. Electric energy is easy to be
transported.
PID is the most common and most
popular feedback controller used in Industrial
Processtoday. A PID controller calculates an
"error" value as the difference between
ameasured process variable and a desired ‘setpoint’. PID controller is also known as
1. Introduction
Drives are employed for systems
threetermcontrol:-
the
proportional(P),
integral(I) and derivative(D). By tuning these
that require motion control – e.g. transportation
threeparameters
system, fans, robots, pumps, machine tools, etc.
algorithm, the controller can provide control
Prime movers are required in drive systems to
action
provide the movement or motion and energy
requirements.After
that are used to provide the motion can come
controller, now we have to tune the controller;
from various sources: diesel engines, petrol
and there aredifferent approaches to tune the
engines, hydraulic motors, electric motors etc.
in
the
designedfor
PID
specific
implementing
controller
process
the
PID
PID parameters like P, I and D. The
Proportional
(P)
part
isresponsible
for
Evolutionary algorithms (EA) are
stochastic optimization techniques based on
following the desired set-point while the
naturalevolution and
Integral (I) and Derivative (D) partaccount for
strategy
the accumulation of past errors and the rate of
Evolutionaryalgorithms have been successfully
change of error in the process orplant,
applied to solve complex optimization problem
respectively.Open loop tuning methods are
inbusiness, engineering, and science. Some
where the feedback controller is disconnected
commonly used EAs are Genetic algorithms
and theexperimenter excites the plant and
(GA’s),
measures the response. The key point here is
Evolutionary
that since thecontroller is now disconnected the
DifferentialEvolution (DE). Each of these
plant is clearly now no longer strictly under
methods has its own characteristics, strengths
control. If theloop is critical, then this test could
and weaknesses.In general, an EA algorithm
be hazardous. Indeed if the process is open-
can generate a set of initial solutions randomly
loop unstable,then we will be in trouble before
based on thegiven seed and population size.
we begin. Notwithstanding for many process
Afterwards, it will go through evolution
controlapplications, open loop type experiments
operations such ascross-over and mutation
are
and
before evaluated by the objective function. The
deliverinformative results. If the system is
wining entity in thepopulation will be selected
steady at set point, and remains so, then we
as the parents (or seed) of the next generation.
have noinformation about how the process
The optimizationiteration continues until the
behaves.There are various tuning strategies
termination criteria are satisfied. Typically,
based on an open-loop step response. While
either the evolutionprocess reached users define
they allfollow the same basic idea, they differ
maximum
in slightly in how they extract the model
improvement in objectivefunction between the
parametersfrom the recorded response, and also
two generations converges.
usually
quick
to
perform,
differ slightly as to relate appropriate tuning
found
in
survival of the fittest
biological
Evolutionary
Programming
Strategy
number
organisms.
of
(EP),
(ES)
iteration
and
or
the
2. Review of existing literature
constantsto the model parameters. There are
In the paper [2011 1], three speed
four different methods, the classic Ziegler-
control methods for a drivesystem with
Nichols openloop test, the Cohen-Coon test,
resonant loads are carried out. The considered
Internal
controlmethods
Model
Approximate
Control
(IMC)
M-constrainedIntegral
and
are
the
following:
a
Gain
conventional proportional-integral (PI) control,
the
a PI-based state space control, and a model-
response is not sigmoidalor ‘S’ shaped and
basedpredictive control. To ensure a suitable
exhibits overshoot, or an integrator, then this
basis for their comparison,the three different
tuning method is notapplicable.
speed control methods are designed with
Optimization (AMIGO).
Naturally if
equalbandwidths and are verified with the same
drive’s safetyand physical limitations to be
test setup. Further-more, all speed control
directly incorporated into controlsynthesis. The
methods presented use only the drive-sidespeed
effect of the predictive horizon on the drive
measurement to control the drive speed. This
performance is examined. In the paper [12
paper [valentin 2012]continues the design
2013] an evolutionary fuzzy proportional-
considerations of anovel type of passive filter
integral-derivative
called hybrid LC filter (HLCF). The filteris
permanent magnetsynchronous motor (PMSM)
aimed
high-
is developed. We first consider a fuzzy
frequency differentialmode (DM) and common
PIDcontrol design problem based on the
mode (CM) currents in speed-controlledac
common control engineeringknowledge that
drives. A model of the HLCF is presented.
good transient performances can be obtainedby
Based on the model,a transfer function of the
increasing the P and I gains and decreasing the
HLCF is found. The HLCF behavior is
D gainwhen the transient error is big. Then we
analyzed in frequency domain. A method for
give an evolutionaryalgorithm (EA) to autotune
HLCF
estimation
the control parameters of the fuzzyPID
with asymptotes is proposed. A comparisonof
controller. We implement the proposed EA-
the measured, simulated, and calculated results
based fuzzyPID control controller in real time
infrequency domain is presented. [2013] A two
on
point boundary value problem occurduring the
floating-point DSP. We also give simulation
process of solving a single or set of
andexperimental
differentialequations whose solution has to
effectiveness of the proposedintelligent digital
satisfy
control
at
significant
reduction
frequencydomainbehavior
both
initial
and
in
finalboundary
a
Texas
(PID)
controller
for
a
InstrumentsTMS320F28335
results
system
to
under
show
the
abrupt
load
conditions. To solve numerically a nonlinear
torquevariation using a prototype PMSM. The
two
paper
pointboundary
value
problem
it
is
[2014]presents
digital
implementationof
that determines the strategy of the variations of
achieving improved performance ofBrushless
theinitial conditions to achieve the solution that
dc (BLDC) servomotor drive. The performance
aims to the finalconditions given. A hybrid
of fuzzyand PID controller-based BLDC
algorithm is proposed, which iscomposed of
servomotor drives is investigatedunder different
two algorithms: genetic and classic. Applying
operating conditions
thisalgorithm to solve the nonlinear two point
referencespeed,
boundary valueproblem two different indexes
disturbance, etc. BLDC servomotorsare used in
of parametric optimization isused. In the paper
aerospace,
[September
vehicles,
controller
for
a
model
theposition
predictive
control
of
an
industrial
fuzzy
and
necessary to use a computer and analgorithm
2013],
a
design
such
parameter
instrumentation
electric
control
vehicles,
controller
as
for
change
variations,
systems,
robotics,
applications.In
in
load
space
and
such
electrical drive with an elastic connectionis
applications, conventional controllers like P, PI,
presented. The control methodology enables the
and PIDare being used with the BLDC
servomotor drive control systemsto achieve
utilized to train the system. To evaluate
satisfactory
theefficacy of the proposed scheme, a 10 fold
transient
and
steady-state
responses. 2014 Optimalfeatures are selected
cross-validation is
using genetic algorithm (GA) with support
detection rate is found100% accurate with
vector
100% of sensitivity and specificity for the data
machine
as
a
classifier
for
implemented,
under
Clinical EEG data from epileptic and normal
GASVMscheme is a novel technique using a
subjects are used in theexperiment. The
hybrid
knowledge of neurologist (medical expert) is
decomposition, supportvector machine and GA.
Scope and limitations of
approach
with
The
the
creatingobjective function values for the GA.
3.
consideration.
and
proposed
wavelet
packet
Matching the power from an available
source to suit the motor requirements (voltage,
the study:
frequency, number of phases). This is an
For many years the motor controller was
example of "Power Conditioning" whose
a box which provided the motor speed control and
purpose is to provide pure DC or sine wave
enabled the motor to adapt to variations in the load.
power free from harmonics or interference.
Designs were often lossy or they provided only
Although it could be an integral part of a
crude increments in the parameters controlled.
generator control system, more generally,
Modern controllers may incorporate
both
power
electronics
and
microprocessors
enabling the control box to take on many more tasks
and to carry them out with greater precision. These
power conditioning could also be provided by a
separate free standing module operating on any
power source.
Limitations of the study
tasks include:
 Controlling the dynamics of the
machine and its response to applied loads.
 Simple low cost, low power
machines usually have simple open loop
control systems. The common DC brushed
(Speed, torque and efficiency of the
machine or the position of its moving elements)
motor for instance needs only a simple
voltage controller for speed control and
 Providing
electronic
commutation.
 Enabling
low cost, integrated circuit controllers are
available for this purpose.
self-starting
of
the
motor.
 Higher power machines however
tend to use more complex closed loop
 Protecting the motor and the
controller itself from damage or abuse.
controllers which are usually custom
designed for each particular machine and
often built into the machine itself.

Safety features also play a more
[5]
L. Kawecki, T. Niewierowicz, “Hybrid
important role in larger machines since in case
Genetic Algorithm to Solve the Two Point Boundary
of machine failure the potential for damage is
Value Problem in the Optimal Control of Induction
Motors,” IEEE Latin America Transactions, VOL.
greater.

12, NO. 2, MARCH 2014, pp. 176-182.
The system designer should also
[6]
R. Shanmugasundram, “Implementation
be aware of the consequences that high
and Performance Analysis of DigitalControllers for
frequency, high current pulsed loads of the
Brushless
inverters and choppers may have on battery
TRANSACTIONS ON MECHATRONICS, VOL.
lifetime in DC traction systems such as hybrid
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electric
vehicles.
Similarly
the
voltage
DC
Motor
drives,”
IEEE/ASME
AbhijitChoudhury,”DC-Link
[7]
regulation of the on board generator and the
Voltage Balancing for a Three-Level Electric
regenerative braking charge pulses can also
Vehicle Traction Inverter Using an Innovative
affect the battery adversely if not properly
Switching Sequence Control Scheme,” IEEE
controlled.
JOURNAL OF EMERGING AND SELECTED
4.
TOPICS IN POWER ELECTRONICS, VOL. 2,
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