Future Perspectives of PID Control

Future Perspectives of PID Controllers (industrial process control) IFAC Conference on Advances in PID Control Brescia, 28-30 March 2012 Willy WojsznisSlide 1 IFAC - PID’12 – Brescia Italy

Thoughts • Where PID is? • Why PID ? • Direction for evolution • Examples of PID evolution • ConclusionSlide 2 IFAC - PID’12 – Brescia Italy

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 agoSlide 3 IFAC - PID’12 – Brescia Italy

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 cooperationSlide 4 IFAC - PID’12 – Brescia Italy

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

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 strategySlide 6 IFAC - PID’12 – Brescia Italy

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 limitedSlide 7 IFAC - PID’12 – Brescia Italy

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 adaptationsSlide 8 IFAC - PID’12 – Brescia Italy

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

PID – loop diagnostics  Valve diagnostics features – mechanical failure can nullify all gains achieved from improved tuning or control strategySlide 10 IFAC - PID’12 – Brescia Italy

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  hr KSlide 11 IFAC - PID’12 – Brescia Italy

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 applicationsSlide 12 IFAC - PID’12 – Brescia Italy

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