Transcript EE462 Fundamentals of Control Systems Engineering

EE357 Control System I - Lec B2
(2010W)
- Introduction
Outline
• What is a control system?
• Open-loop control vs. Closed-loop
(feedback) control
• Development of control theory
• A brief overview of EE357
What is a control system?
• A general definition: “A control system is a
device or set of devices to manage, command,
direct or regulate the behavior of other devices
or systems.”
• A control (feedback) loop, including sensors,
control algorithms and actuators, is arranged in
such a fashion as to try to regulate a variable at
a set point or reference value.
What is a control system?
A typical (feedback) control system contains
• Plant/process - object to be controlled
• Controllers - devices that compute and generate control
signals/actions
• Actuators - devices that perform control actions
• Sensors - devices that measure the output
Control objectives - tasks, targets of control
Open-loop Control
• The controller does not use measurement of
system output being controlled when
computing the control action, i.e. no feedback
control
action
command input
controller
output
process
sensor
Fig. 1. A block diagram representation of an open loop control
Closed-loop Control
• Also called feedback control, the controlled
system output is measured and being used
for computing the control action.
command
input
control
action
error
controller
output
actuator
process
sensor
Fig. 2. A block diagram representation of a closed-loop control
Example 1. Room Temperature
Control
• Open-loop scheme:
Switch
(on/off)
inlet vent
heat
furnace
temperature
room
– no measurement for feedback
– fixed control action
– can’t adjust to unexpected changes from the
system environment
Example 1. Room Temperature
Control
• Closed-loop scheme
desired temp.
thermostat
furnace
heat variation
inlet
heat
room temp.
room
– thermostat: sensing plus control device
– automatically adjust room temperature
– can easily change room temp. as desired
Example 1. Room Temperature
Control
Fig. 3. Response of closed-loop room temp. control
(ref. EE4629 notes, A. Lynch, 2006)
Example 2: Car Cruise Control
Road grade
desired speed
Control
unit
Engine
Car
body
speed
speedometer
Fig. 4. Bock diagram of closed-loop car speed control
• Control mechanism: compute the difference between
the set speed and the actual speed; then open throttle
according to the quantity of error
Example 3: Human Balance
System
perturbation
brain
ankle,
hip, foot
body
position
(com)
Sensors:
eye, inner ear balance sys. &
legs (pressure)
Fig. 5. Block diagram of human balance control
Example 3: Human Balance
System
• Analogy of human balance control:
– ankle, hip strategy: similar to inverted pendulum
– step strategy: similar to inverted pendulum on a
cart
Application and Theory
• Control systems and feedback control
concepts are everywhere: daily life,
manufacture plant, aerospace industry,
automotive industry, chemical, biomedical
processes … …
• The subject of control is multidisciplinary:
engineering, mathematics, computer science,
etc.
History: Primitive Phase
• Float valve feedback
regulator for water clock
– time is determined by the outlet
flow rate, which is determined by
liquid level
– liquid level is regulated by the
float valve
– sensing and actuation functions
are integrated in the float valve
mechanism
(Ref. Dorf, 10th.)
History: Primitive Phase
• Flyball Governor (Watt
1788)
– Mile stone for industry
revolution
– Flyball feedback mechanism
for the regulation of steam
engine speed
– Sensing and actuation are
integrated in one mechanism
(Ref. Dorf, 10th.)
History: Classical Phase
• Analysis based on mathematical modeling
– Analysis of Flyball governor based on nonlinear
differential equations (Maxwell 1868)
• Stability notions, stabilization
– nonlinear stability (Lyapunov, 1890)
– gyroscope/autopilot (Sperry, 1910)
• PID control (Minorsky, 1922)
History: Classical Phase
• Frequency domain methods for analysis and
design
– Nyquist plot, Bode diagram, feedback amplifier
(Black, Bode, Nyquist at Bell lab) (1930’s - 50’s)
• Key classical control methods
– Routh-Hurwitz stability criterion, root locus,
frequency response methods, Nyquist criterion
– Graphical and hand computation
– Suitable for SISO and low order systems
History: Modern Phase (1960 -)
•
•
•
•
Computer controlled system
State space modeling (based design)
Optimal control, Kalman filter
Communication systems, network based,
distributed control systems (DCS)…
Modern control uses state space modeling and can
deal with MIMO and high order systems
Related Issues in Control System
• Modeling: obtain mathematical models
• Analysis: stability, time-domain
specifications
• Design: specify the structure and
parameters of a controller to achieve the
desired performance specifications
• Implementation: analog filters, digital
controllers, micro-controllers, PLC,
DCS, etc.
EE 357
• Classical control methods and theories are
covered in EE357, the first control course
for EE students
– Modeling: o.d.e, transfer function
– Analysis: stability criteria, time-domain and
frequency-domain system specification
– Design: classical design tools based on several
important system charts and plots
Modern control is covered in EE460 and EE461.