IDR BLOK offers standard and advanced control algorithms.

 

Standard process control algorithms:

• ON/OFF controller
• P3P controller
• PID controller
• position PID
• velocity PID
• ENTHALPY controller

 

Advanced process control algorithms:

Modular PID

o    PID with additional input and output filters

• Set Point filter
• Manipulative Value filter

o    suitable for various control structures (cascade, etc.)

 

Predictive functional controllers – PFCs

 

o    PFC SF (for first order processes), PFC SS (for second order processes), PFC INT (for integral processes)

o    uses a process model to predict and optimize the controller output (MV)

o    control quality depends on the accuracy of the estimated process model

o    more robust than PID

o    easy tuning with Controller Tuning tool

o    suitable for high delayed processes

 

Smith predictor

 

o    PID and a process model with the delay

o    most effective for controlling the delayed processes

o    efficiency of a feedback control using a Smith predictor increases with increasing delay and the order of the process

 

Fuzzy logic controller

 

o    block performs the function of fuzzy logic

o    Fuzzy Logic Controller Designing Tool – specific user interface for FLC design and testing

o     Sugeno 0-order FLC type

o    up to 2 inputs, 1 outputs

o    triangular membership functions for each input

o    most effective for controlling non-linear processes

 

Fuzzy Gain Scheduling Controller – FGSC

 

o    executes the position PID algorithm with fuzzy scheduling of local controller parameters

o    one-dimensional fuzzy scheduling with up to 10 local controllers

o    scheduling variable can be PV, SP, MV or measured disturbance

o    for high nonlinear processes

 

Explicit parametric Model-based Predictive Controller – EMPC

 

o    algorithm for the search of the active region in the state-space partition of the expanded model

o    partition should be determined in advance using Matlab software

o    up to 8 inputs (state vector x typically formed using Kalman filter) and two outputs (change of MV signal)

o    soft and hard limitations on PV can be used

o    significantly improve the control of processes which require control very near the process limit or when the process is not allowed to get beyond a certain limit

 

 

Please contact us for more information.

idr@inea.si

 

Purpose of Controller Tuning is to:

• set the controller parameters for operational state of the process

• for some APC’s, manual setting is not feasible:
  o   difficult to determine parameters – process model must be known

• reduce amount of work and time necessary for designing – setting up the control application

• reduce the depth of knowledge necessary in using the APC:
  o   target objective: plug & play functionality

 

IDR BLOK’s Controller Tuning Tool:

• automatically calculates the parameters and recommends the most suitable controller structure
  o   calculation is  based on a specified process model

• various tuning methods for PID and Smith controllers:
  o   Area method
  o   Ziegler-Nichols
  o   CHR
  o   Balanced method

• Basic and Advanced tuning method for PFC controllers

• every method can tune the controller in the reference-tracking mode or the disturbance elimination mode

• the tuning results:
  o   K_p, T_i, T_d and K_d for PID,
  o   K_p, K_i, K_d, T_{f_MV} and T_{f_SP} for SMITH and modular PID,
  o   T_rbf and H for PFC.

 

Tuning example on real process with PID/M controller

The PID/M controller controls water height in 2nd tank in two tanks system.

 

Please contact us for more information.

idr@inea.si