1. Future Perspectives of PID
Controllers
(industrial process control)
IFAC Conference on Advances in PID Control
Brescia, 28-30 March 2012
Willy Wojsznis
Slide 1 IFAC - PID’12 – Brescia Italy
2. Thoughts
• Where PID is?
• Why PID ?
• Direction for evolution
• Examples of PID evolution
• Conclusion
Slide 2
IFAC - PID’12 – Brescia Italy
3. Where PID is?
PID proved it can compete in many
applications with new promising techniques,
like
Fuzzy Logic
Model based controllers
MPC
Slogans “replace all PID” is not used as10-20
years ago
Slide 3
IFAC - PID’12 – Brescia Italy
4. Where PID is ?
• PID “found” its favorite spot, where it is doing the
better than other techniques
This is the low and intermediate level control in
process industry where PID is absolutely dominant
control
MPC reign in multivariable control and optimization.
PID provide good control at the lower level
Instead of competition – good cooperation
Slide 4
IFAC - PID’12 – Brescia Italy
5. Why PID ?
• Feedback is universal control
• Intuitive for the human, appreciated by operators
• P I D - the most natural rules
• PID like control used
in nature on various levels
and time scale
(molecular level
- seconds,
species – thousand
of years)
Slide 5
IFAC - PID’12 – Brescia Italy
6. PID – direction for evolution
Enhanced PID for dealing with special conditions or
applications with added logic and calculations
Examples: saturated conditions, wireless, event driven,
non-linear ….
Robust adaptive tuning and control
Performance monitoring and reporting
Valve diagnostics – mechanical failure can nullify all gains
achieved from improved tuning or control strategy
Slide 6
IFAC - PID’12 – Brescia Italy
7. PID at saturated conditions
• A better response to major upsets can be achieved through the
use of a dynamic pre-load and reducing the filtering that is
applied in the positive feedback path when the output limited
Slide 7
IFAC - PID’12 – Brescia Italy
8. PID – model based adaptive tuning
Why model based adaptation?
Model validation for model switching
adaptation with parameter interpolation is
performed in parallel with parameter
evaluation
Ratio of maximum to minimum errors
signifies how fast is conversion
If the model with the middle parameter value
has smallest error it indicates the optimum is
Well established, intuitive tuning
rules – Lambda, IMC, SIMC within adaptation range
Model can be used for other
purposes – loop diagnostics, Statistical validation – recent model quality,
performance monitoring….
parameters standard deviation, number
of adaptations
Slide 8
IFAC - PID’12 – Brescia Italy
9. PID – model free adaptation
There are number of smart techniques model free
techniques
PVi(t SPi(t)
Fictitious set point ) + +
OUTi(t
)
Controller switching
Balancing controller terms
P
P Pk ; and I I k ;
k k I
1
Ti (k ) Ti (k ) 1
Slide 9
IFAC - PID’12 – Brescia Italy
10. PID – loop diagnostics
Valve diagnostics features – mechanical failure
can nullify all gains achieved from improved
tuning or control strategy
Slide 10
IFAC - PID’12 – Brescia Italy
11. PID – loop diagnostics
Simple valve diagnostics can detect valve dead
band and hysteresis
h 2 A(out ) 2 Ampl ( PV ) Kr
r 2 Ampl ( PV ) b hr
K
Slide 11
IFAC - PID’12 – Brescia Italy
12. PID future - conclusion
PID will continue to be main control on the basic
level in the process industry
PID evolution as discussed will enhance PID
competitiveness
Model free adaptive tuning can be useful in
special applications
Slide 12
IFAC - PID’12 – Brescia Italy