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Module IV(I)
Control Systems
Design
DYNAMICS and CONTROL
Presented by
Pedro AlbertosProfessor of Systems Engineering and Control - UPV
Complex Control system
Module IV(III)
Control Systems
Design
Examples of systems and signals
Models of systems and signals
Controlled systems: properties
Control systems design
Control systems structure
Parameters tuning
“Complex” Control systems design
Control benefits
Topics to study2
Modules:
DYNAMICS & CONTROL
Examples of systems and signals
Models of systems and signals
Controlled systems: properties
Control systems design
Control systems structure
Parameters tuning
“Complex” Control systems design
Control benefits
Topics to study
Control Systems Structure
– Open-loop control
– Closed-loop control
– Supervisory control
– Cascade control
– Feed-forward control
– Two degrees of freedom control
– Hierarchical control
DYNAMICS & CONTROL
SYSTEM
Disturbances
Information
Co
ntr
olle
d
vari
able
s
Information
CONTROLGoals
SENSOR
3
. .dy G u G p Based on the Process
and disturbance Model:Ideal Control: 1 .r du G y G p
Tracking control: Perfect knowledge and feasibility of G-1
DYNAMICS & CONTROL
4
Basic control structures (I)– Open-loop Control
PROCESSCONTROL
Disturbance
Controlled Var.
Control
Action
Goals
sensor
ry yu
p
Regulation : Perfect knowledge and feasibility of G-1, Gd , and access to p
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Objetives
sensor
DYNAMICS & CONTROL
5
Basic control structures (II)– Closed-loop Control
Characteristics:
• Need a good feedback: access to variables and sensors
nGKH
GKHd
GKH
GGr
GKH
GKFy ed
111
• Use of high gain K1
0. ey F r d nH
Risk of instability
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action+
n
Measured
Var.
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action+
n
Measured
Var.SENSOR
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action
Virtual
Sensor
+
n
Measured
Var.
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action
Virtual
Sensor
+
n
Measured
Var.
and
the models
Internal variables
Filtered outputs
Estimated disturbances
Any other internal magnitude
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action
Virtual
Sensor
+
n
Measured
Var.
and
the models
Internal variables
Filtered outputs
Estimated disturbances
Any other internal magnitude
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action
Virtual
Sensor
+
n
Measured
Var.
and
the models
Reduce the effect of measurement noise
Get a richer information from the plant
Estimate some disturbance
Virtual sensor ≡ Estimator ≡ Observer ≡ Filter
Internal variables
Filtered outputs
Estimated disturbances
Any other internal magnitude
DYNAMICS & CONTROL
6
Improved control structures (I)– Virtual sensors
PROCESS
Disturbance
Contr.
Var.
Control
Action
Virtual
Sensor
+
n
Measured
Var.
and
the models
Reduce the effect of measurement noise
Get a richer information from the plant
Estimate some disturbance
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
dt
deKdteKeKu d
t
ip 0
PID Improvements:
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
dt
deKdteKeKu d
t
ip 0
PID Improvements:
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
dt
deKdteKeKu d
t
ip 0
- Filtered derivative
- Output (no input) derivative
PID Improvements:
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
dt
deKdteKeKu d
t
ip 0
- Filtered derivative
- Output (no input) derivative
- Limited integration (anti wind-up)
- Reset control
PID Improvements:
DYNAMICS & CONTROL
7
Improved control structures (II)– Closed-loop Control
PROCESSCONTROL
Disturbance
Controlled V.
Control
Action
Reference
sensor
PID
dt
deKdteKeKu d
t
ip 0
- Filtered derivative
- Output (no input) derivative
- Limited integration (anti wind-up)
- Reset control
Master
Complex Control Structures (I)
– Cascade Control
Master
Complex Control Structures (I)
– Cascade Control
Master
Complex Control Structures (I)
– Cascade Control
PID
Master
Complex Control Structures (I)
– Cascade Control
PID
• Make faster the internal Subprocess
• Reduce the effect of the inner disturbance
Master
Complex Control Structures (I)
– Cascade Control
PIDPID
Master
Complex Control Structures (I)
– Cascade Control
PIDPID
• Achieve desired closed-loop behavior
• Reduce the effect disturbances
• Allow for tracking
Master
Complex Control Structures (I)
– Cascade Control
PIDPID
This may be extended to a full set
of variables
Complex Control Structures (II)
– Model Predictive Control
Error: • Current Value
• Past Values
• Future Values
eKu p
k
j
jik
t
i eKudteKu00
;
t
eKu
dt
deKu k
dkd
;
PID
Complex Control Structures (II)
– Model Predictive Control
Complex Control Structures (II)
– Model Predictive Control
Complex Control Structures (III)
– Adaptive Control
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
Objetives
sensor
Complex Control Structures (III)
– Adaptive Control
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
Objetives
sensor
Model
Identification
Complex Control Structures (III)
– Adaptive Control
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
Objetives
sensor
Model
IdentificationC. Parameter
Computation
Complex Control Structures (III)
– Adaptive Control
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
Objetives
sensor
Model
IdentificationC. Parameter
Computation
Complex Control Structures (IV)
– Adaptive Control (Model Reference)
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
sensor
ref
y
Complex Control Structures (IV)
– Adaptive Control (Model Reference)
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
sensor
Model
Reference
ref
y
Complex Control Structures (IV)
– Adaptive Control (Model Reference)
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
sensor
Model
Reference
ref
my
y
Complex Control Structures (IV)
– Adaptive Control (Model Reference)
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
sensor
Model
Reference
ref
my
y
e
Complex Control Structures (IV)
– Adaptive Control (Model Reference)
PROCESSCONTROL
Disturbance
Controlled
Var.Control
Action
sensor
C. Parameter
Adaptation
Model
Reference
ref
my
y
e
Advanced Control Systems
– Non linear control
– Robust control
– Network-based control
– Intelligent Control
– Coordinated control
– Hierarchical control
–…
DYNAMICS & CONTROL
12
13
DYNAMICS & CONTROL
Complex Control Systems
What have we seen today?
Feasibility of the PID
Multi-loop control
Model Predictive Control
Adaptive Control
…
Simple implementable solutions
Complex computation
14
DYNAMICS & CONTROL
Modules:What is next?
Examples of systems and signals
Models of systems and signals
Controlled systems: properties
Control systems design
Control systems structure
Parameters tuning
Control benefits
Topics to study
Module VI (III)
Control systems
Design
Complex Control systems
DYNAMICS and CONTROL
Presented by
Pedro AlbertosProfessor of Systems Engineering and Control - UPV 15
Thank you!