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Adaptive control

Selftuning regulator


  • Automatic tuning of all regulator gains
  • Adapting to varying process behaviour
  • Easy to use with standard settings
  • No manual tuning is necessary
  • Many regulator parameters can be used
  • Self-tuning feedforward control is included
  • Fast and simple comissioning
  • Improved control accuracy
  • More stable process

Adaptive Control Technique

Regulator structure

First Control is using a general adaptive regulator with self-tuning technique (STR). A self-tuning regulator consists of two parts

  1. Adapting part which creates a control model and computes the regulator setting based on the identified model.
  2. Regulating part which perform the computation of the control value and regulator logics.

The STREGX2 regulator in the MicroController XC library can operate with as many as 20 regulator parameters. The large number of regulator parameters means that, in addition to the PID functions, it automatically performs compensation for time delays, complex dynamics, process disturbances and feedforward control. The regulator is also predictive, i.e. the control action depends on a predicted behaviour the next few sampling instances.

All parameters are automatically tuned by the regulator.


Mathematical methods

The methods used by the STREGX2 regulator are

  1. Control model. A general control model is created by a recursive LSQ identification method with internal protection against wind-up phenomena and degrading model parameters. The model order is specified by the user and may contain up to 20 parameters.
  2. Control strategy. The control strategy is computed using a pole placement method. The feedforward part is ensured a specified degree of stability in case the process is non-minimum phase.

The mathematics is included in the object and is nothing the user has to consider. The user sets the framework for the regulator, as is described in the MicroController XC manual.


Running experience

Experience from a large number of installations shows clearly that First Control’s self-tuning regulators is superior to PID regulators. The improved control accuracy will in the end result in better production and less production waste. According to our long experience, the improvement is normally in the range 50-75%, which means a substantial improvement in production, especially if the requirements on the production quality is high.

Installations have been made in many different processes in the steel and energy area.

Read more

MAN-XC01/09 Adaptive control in MicroController XC systems (pdf 186kB)

Info-004/1 Improved AGC Control using adaptive technique in Cold Rolling Mill (pdf 616kB)

The selftuning regulator

The self-tuning regulator is a standard control object in the MicroController XC function library


  1. Automatic tuning of all regulator gains
  2. Adapting to varying process behaviour
  3. Easy to use with standard settings
  4. No manual tuning is necessary
  5. Many regulator parameters can be used
  6. Self-tuning feedforward control is included
  7. Fast and simple comissioning
  8. Improved control accuracy
  9. More stable process

Case study in cold-rolling mill

The diagram shows the improvements in strip thickness using First Control’s self-tuning regulator in an old Sendzimir Mill at Outokumpu Stainless in Långshyttan Sweden. Each point in the diagram shows  the average standard deviation in strip thickness during one month of production.

The upgrading of the mill was done in steps during about 3 years. The improvement after each new self-tuning function is seen as jumps in the performance curve above. In the end, the strip accuracy achieved (0.0005 mm) was better than most new mills.

The large improvement in strip quality meant that the company could increase their sales and the owner invested in two completely new mills which are also controlled by First Control’s self-tuning regulators.