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CONTENTS
1. Objective
2. Introduction
3. Automatic Voltage Regulation
4. PID Controller
5. FOPID Controller
6. Classical tuning methods of PID & FOPID Controller
7. Optimal Tuning of FOPID Tuning using PSO
8. Simulation Result
9. Conclusion
1. OBJECTIVE
• The aim of my work is to develop a controller based
on Particle Swarm Optimization Technique to
simulate an Automatic Voltage Regulator (AVR) for
a synchronous generator in order to achieve better
stability of the system and fulfil the requirements of
good excitation control.
2. INTRODUCTION
• In this work bio-inspired optimization technique in
controllers and their advantages over conventional
methods is discussed using MATLAB/Simulink.
• Also the advantage of FOPID controller over
Conventional PID controller is discussed using
MATLAB/Simulink.
• The main aim is to apply PSO technique to design
and tune parameters of FOPID controller to get an
output with better dynamic and static performance.
3. AUTOMATIC VOLTAGE
REGULATION
• The Automatic Voltage Regulator (AVR) is widely
used in industrial application to obtain the stability
and good regulation of different electrical apparatus.
• The automatic voltage regulator or AVR, as the name
implies, is a device intended to regulate voltage
automatically: that is to take a varying voltage level
and turn it into a constant voltage level.
Contd…
• A simple AVR consists of:-
1. Amplifier,
2. Exciter,
3. Generator and
4. Sensor.
Contd…
Fig : Block Diagram of AVR
Contd…
• Table 3.1 Parameter range for the components used in
AVR
4. PID CONTROLLER
• PID (proportional-integral-derivative) control
is one of the earlier control strategies.
Fig: Block Diagram of PID Controller
Contd…
• PID controller has all the necessary dynamics:
• Fast reaction on change of the controller input (D
mode),
• Increase in control signal to lead error towards zero (I
mode) and
• Suitable action inside control error area to eliminate
oscillations (P mode).
• The o/p of PID controller is given as:
Contd…
• Table : Effect of each controllers Kp, Ti and Td on a
closed-loop system
5. FOPID Controller
• Fractional-order calculus is an area of mathematics
that deals with derivatives and integrals from non-
integer orders.
• In fact, in principle, they provide more flexibility in
the controller design, with respect to the standard PID
controllers, because they have five parameters to
select (instead of three).
• The concept of FOPID controllers was proposed by
Podlubny in 1997 (Podlubny et al., 1997; Podlubny,
1999a).
Contd…
• It is Clear, by selecting λ = 1 and μ = 1, a classical PID
controller can be recovered. Using λ = 1, μ = 0, and λ = 0, μ =
1, respectively corresponds to the conventional PI & PD
controllers.
• All these classical types of PID controllers are special
cases of the FOPID controller.
•
Contd…
• The mathematical representation of such a controller
is as follows:
• ADVANTAGES OF F-O CONTROLLER
1. If the parameter of a controlled system changes, a fractional
order controller is less sensitive than a classical PID controller.
2. FOC has two extra variables to tune. This provides extra
degrees of freedom to the dynamic properties of fractional order
system.
6.CLASSICALTUNINGMETHODSOF
PID&FOPIDCONTROLLER
• PID Tuning
• The model of a plant is given
as
• The transfer is assumed as
• Where,
• K - Gain
• ϴ - delay time
• T – time constant
Contd…
• Now the response of plant is taken as
Contd…
• After computing the t1 and t2 times, the time delay
(ϴ) and process time constant (T) can be obtained
from the following equations:
Contd…
• Ziegler-Nichols Tuning Method
• Now the value of Kp, Ti, Td is obtained by the
following table :
Contd…
• Cohen-Coon Tuning Method
• Cohen and Coon based the controller settings on the
three parameters ϴ, T and K of the open loop step
response.
Contd…
FOPID Tuning
• Ziegler-Nichols Type Tuning Rules
• First set of tuning rules
• The first set of tuning rule is given as
• P=-0.0048+0.2664L+0.4982T+0.0232L2-0.0720T2-0.0348TL
Contd…
7. Optimal Tuning of FOPID Tuning
using PSO
• Introduction to Particle Swarm Optimization (PSO)
1. Origins
2. Concept
3. PSO Algorithm

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ppt.pptx

  • 1. CONTENTS 1. Objective 2. Introduction 3. Automatic Voltage Regulation 4. PID Controller 5. FOPID Controller 6. Classical tuning methods of PID & FOPID Controller 7. Optimal Tuning of FOPID Tuning using PSO 8. Simulation Result 9. Conclusion
  • 2. 1. OBJECTIVE • The aim of my work is to develop a controller based on Particle Swarm Optimization Technique to simulate an Automatic Voltage Regulator (AVR) for a synchronous generator in order to achieve better stability of the system and fulfil the requirements of good excitation control.
  • 3. 2. INTRODUCTION • In this work bio-inspired optimization technique in controllers and their advantages over conventional methods is discussed using MATLAB/Simulink. • Also the advantage of FOPID controller over Conventional PID controller is discussed using MATLAB/Simulink. • The main aim is to apply PSO technique to design and tune parameters of FOPID controller to get an output with better dynamic and static performance.
  • 4. 3. AUTOMATIC VOLTAGE REGULATION • The Automatic Voltage Regulator (AVR) is widely used in industrial application to obtain the stability and good regulation of different electrical apparatus. • The automatic voltage regulator or AVR, as the name implies, is a device intended to regulate voltage automatically: that is to take a varying voltage level and turn it into a constant voltage level.
  • 5. Contd… • A simple AVR consists of:- 1. Amplifier, 2. Exciter, 3. Generator and 4. Sensor.
  • 6. Contd… Fig : Block Diagram of AVR
  • 7. Contd… • Table 3.1 Parameter range for the components used in AVR
  • 8. 4. PID CONTROLLER • PID (proportional-integral-derivative) control is one of the earlier control strategies. Fig: Block Diagram of PID Controller
  • 9. Contd… • PID controller has all the necessary dynamics: • Fast reaction on change of the controller input (D mode), • Increase in control signal to lead error towards zero (I mode) and • Suitable action inside control error area to eliminate oscillations (P mode). • The o/p of PID controller is given as:
  • 10. Contd… • Table : Effect of each controllers Kp, Ti and Td on a closed-loop system
  • 11. 5. FOPID Controller • Fractional-order calculus is an area of mathematics that deals with derivatives and integrals from non- integer orders. • In fact, in principle, they provide more flexibility in the controller design, with respect to the standard PID controllers, because they have five parameters to select (instead of three). • The concept of FOPID controllers was proposed by Podlubny in 1997 (Podlubny et al., 1997; Podlubny, 1999a).
  • 12. Contd… • It is Clear, by selecting λ = 1 and μ = 1, a classical PID controller can be recovered. Using λ = 1, μ = 0, and λ = 0, μ = 1, respectively corresponds to the conventional PI & PD controllers. • All these classical types of PID controllers are special cases of the FOPID controller. •
  • 13. Contd… • The mathematical representation of such a controller is as follows: • ADVANTAGES OF F-O CONTROLLER 1. If the parameter of a controlled system changes, a fractional order controller is less sensitive than a classical PID controller. 2. FOC has two extra variables to tune. This provides extra degrees of freedom to the dynamic properties of fractional order system.
  • 14. 6.CLASSICALTUNINGMETHODSOF PID&FOPIDCONTROLLER • PID Tuning • The model of a plant is given as • The transfer is assumed as • Where, • K - Gain • ϴ - delay time • T – time constant
  • 15. Contd… • Now the response of plant is taken as
  • 16. Contd… • After computing the t1 and t2 times, the time delay (ϴ) and process time constant (T) can be obtained from the following equations:
  • 17. Contd… • Ziegler-Nichols Tuning Method • Now the value of Kp, Ti, Td is obtained by the following table :
  • 18. Contd… • Cohen-Coon Tuning Method • Cohen and Coon based the controller settings on the three parameters ϴ, T and K of the open loop step response.
  • 19. Contd… FOPID Tuning • Ziegler-Nichols Type Tuning Rules • First set of tuning rules • The first set of tuning rule is given as • P=-0.0048+0.2664L+0.4982T+0.0232L2-0.0720T2-0.0348TL
  • 21. 7. Optimal Tuning of FOPID Tuning using PSO • Introduction to Particle Swarm Optimization (PSO) 1. Origins 2. Concept 3. PSO Algorithm