Lecture 1
Introduction to Feedback and Control
Dr. Aamer Iqbal Bhatti
Introduction to feedback and control 9/16/2019
Grading Policy
Assignments = 05 %
Class Participation = 05 %
Labs = 10 %
Project = 10 %
Quizzes = 10 %
Midterm = 20 %
Final = 40 %
Introduction to feedback and control 9/16/2019
Couse Learning Outcomes (CLO’s)
CLO:1. Derive state space model of dynamic systems
CLO:2. Analysis of dynamic linear time invariant (LTI)
systems
CLO:3. Synthesis of linear controllers
Introduction to feedback and control 9/16/2019
Goals:
Define feedback systems and learn how to recognize main
features.
Describe what control systems do and the primary principles
of feedback.
Reading:
CONTROL SYSTEM DESIGN (An Introduction to State-
Space Methods ) by BERNARD FRIEDLAND
Introduction to feedback and control 9/16/2019
Lecture Outline
What is Control System?
Applications
Concept of feedback
Open loop and closed loop systems
Principles of feedback
Examples of feedback
Introduction to feedback and control 9/16/2019
Controls???
Objective is to modify the behavior of a given system so
that it works in accordance with our wishes
Science of designing such controllers
One of the complicated and theoretical branch of Electrical
Engineering
Introduction to feedback and control 9/16/2019
System:
Definition of Controls revolve around Systems.
What is a system?
Identify systems in this room:
Air-conditioners
Bracket fans
Amplifiers
Humans (Combination of sub-systems)
Power Supply of a PC
Introduction to feedback and control 9/16/2019
Motivation of feedback systems:
Many new applications of feedback control were developed
during World War II such as radar-based anti-aircraft gun
control, rocket flight control etc.
Nowadays, feedback control is an enabling technology in most
industries like:
Aerospace: autopilots ,open-loop unstable jet fighters ,rockets
Process control: electric arc furnaces,nuclear reactors ,chemical
reactors
Electronics: Op-amp circuits ,Phase-lock loops ,hard disk drives
Manufacturing Automation: Robotics
Introduction to feedback and control 9/16/2019
What is Feedback?
The term feedback is used to refer to a situation in which
two (or more) dynamical systems are connected together
such that each system influences the other and their
dynamics are thus strongly coupled.
Dynamical system: The system whose behavior changes
over time, often in response to external stimulation or
forcing.
Introduction to feedback and control 9/16/2019
Feedback is must
Can you manage this turn
with eyes closed?
Turning involves :
Direction adjustment
Speed adjustment
A human driver does it
easily.
What if a computer has to
do it?
Introduction to feedback and control 9/16/2019
Characteristics of Feedback Systems:
Advantages:
Faster response
Better stability
Less sensitive to noise
Less sensitive to system parameters
Disadvantages:
May have a tendency to oscillate
Cost becomes higher
Introduction to feedback and control 9/16/2019
Feedforward Control:
Open-loop system
Control element responds to change in command or
measured disturbance in a pre-defined way.
Can compensate for known plant dynamics, delays (before
you get errors)
No sensors needed.
System response must be predictable.
Introduction to feedback and control 9/16/2019
Features of feedback:
•Closed-loop system
•Automatically compensates for disturbances (controller acts
on error)
•Can improve undesirable properties of system/plant
•Can be very simple
Introduction to feedback and control 9/16/2019
Open and Closed Loop Systems:
A system is said to be a closed loop system if the
systems are interconnected in a cycle.
If we break the interconnection, we refer to the
configuration as an open loop system.
Introduction to feedback and control 9/16/2019
Components of Control System:
Sensors:
These are the devices that can measure the output variables to
be controlled.
Example: Thermocouples for temperature measurements,
differential pressure transmitters, radar range sensors,etc.
Actuators:
These are the devices that actually act upon the plant.
Typical actuators for process control include valves, electric
motors, heaters.
Controller:
Controllers use feedback measurements of the output variables
to compute and issue control signals to the actuators.
Introduction to feedback and control 9/16/2019
Control= Sensing + Computation + Actuation
Goals:
•Stability: system maintains desired operating point (hold steady speed)
• Performance: system responds rapidly to changes (accelerate to 6m/sec)
• Robustness: system tolerates perturbations in dynamics (mass, drag, etc)
Introduction to feedback and control 9/16/2019
Two main principles of feedback:
Robustness to uncertainty through feedback:
Allows high performance in the presence of uncertainty
Accurate sensing to compare actual to desired, correction
through computation and actuation
Design of dynamics through feedback:
Allows the dynamics (behavior) of the system to be modified
Interconnection gives closed loop that modifies natural
behavior
Leverage capability to enhance performance or affect stability
Introduction to feedback and control 9/16/2019
Introduction to feedback and control 9/16/2019
Example #1: Flyball Governor
Flyball Governor (1788) :
Shaft of a steam engine is
connected to a flyball
mechanism
Regulate speed of steam
engine
Reduce effects of
variations in load
(disturbance rejection)
Major advance of
industrial revolution
Introduction to feedback and control 9/16/2019
•Flyball governor used in Boulton-Watt Steam
engine
Introduction to feedback and control 9/16/2019
FlyBall Governor Video 1
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FlyBall Governor Video 2
Introduction to feedback and control 9/16/2019
Example 2:Homeostasis:
Regulation of glucose in the
bloodstream through the
production of insulin and
glucagon by the pancreas
Constant concentration of
glucose is maintained
When glucose levels rise the
hormone insulin is released and
causes the body to store excess
glucose in the liver
When glucose levels are low,
the pancreas secretes the
hormone glucagon, which has
the opposite effect
Introduction to feedback and control 9/16/2019
Example #2: Speed Control:
Stability/performance :
Steady state velocity approaches
desired velocity as k→∞
Smooth response; no overshoot or
oscillations
Disturbance rejection:
Effect of disturbances (eg, hills)
approaches zero as k→∞
Robustness :
Results don’t depend on the
specific values of b, m or k, for k
sufficiently large
Introduction to feedback and control 9/16/2019
Example 3:Robotics:
In robotics issues such as obstacle
avoidance, goal seeking, learning and
autonomy are prevalent
Today’s robots still exhibit simple
behaviors compared with humans,
and their ability to locomote,
interpret complex sensory inputs
Combination of AI community with
control presents a renewed path for
progress
Introduction to feedback and control 9/16/2019
Example 4:Insect Flight
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Some other examples:
Biological Systems:
Physiological regulation (homeostasis)
Bio-molecular regulatory networks
Environmental Systems:
Microbial ecosystems
Global carbon cycle
Financial Systems:
Markets and exchanges
Supply and service chains
Introduction to feedback and control 9/16/2019
Control Tools:
Modeling :
Input/output representations for MATLAB Toolboxes:
subsystems + interconnection rules
SIMULINK
System identification theory and
algorithms Control System
Theory and algorithms for reduced Neural Network
order modeling + model reduction
Data Acquisition Optimization
Analysis:
Fuzzy Logic
Stability of feedback systems,
including robustness “margins” Robust Control
Performance of input/output systems Instrument Control
(disturbance rejection, robustness)
Signal Processing
Synthesis:
LMI Control
Constructive tools for design of
feedback systems Statistics
Constructive tools for signal Model Predictive Control System
processing and estimation (Kalman Identification
filters)
Introduction to feedback and control µ-Analysis and Synthesis 9/16/2019
Introduction to feedback and control 9/16/2019
Control Courses at CUST
Control Systems
Linear System Theory
Design
EE5813
EE5843
Robust Control
Sliding Mode Control Nonlinear Control Systems
EE6893 Systems EE6843
EE5823
Introduction to feedback and control 9/16/2019
Control Courses at CUST
Advance level courses subject to student enrollment:
Digital Control Systems - EE5833
Adaptive Control Systems - EE6853
LMI in Control - EE6863
Automotive Control Systems - EE7813
Flight Control Systems - EE7823
Introduction to feedback and control 9/16/2019
CASPR – (Control and Signal Processing Research Group)
2003: Foundation of group. Weekly meetings were held and specialized
control courses like Robust Control, Nonlinear Control and LMI were
offered
2016: Nineteen PhDs have been produced by the group. Currently 11
PhD students are enrolled, out of which three students are near
completion
42+ Papers with Impact Factor of 70 have been published by CASPR
students in nine years
Introduction to feedback and control 9/16/2019
CASPR Activities
Research Areas
Automotive Engine - Parameter Estimation, Fault Diagnostic and Control
Hybrid Electric Vehicles – Modelling and Control
Aerospace Vehicles – Guidance and Control
Nuclear Research Reactor – Parameter Estimation and Control
PEM Fuel Cell – Parameter Estimation
Underground Coal Gasification
Aerodynamics and CFD
Nonlinear and Optimal Control Theory
Radar Signal Processing
Introduction to feedback and control 9/16/2019
Automatic Control Research Society –
www.acrs.com.pk
Introduction to feedback and control 9/16/2019
Control Symposium - 26th Sept 2019
Introduction to feedback and control 9/16/2019
Course Content Link
All course material will be uploaded online on the following
link https://tinyurl.com/LST-Fall2019
Introduction to feedback and control 9/16/2019
End of lecture……
Introduction to feedback and control 9/16/2019
