PID Control System Design and Automatic Tuning using MATLAB/Simulink. Liuping Wang

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PID Control System Design and Automatic Tuning using MATLAB/Simulink - Liuping Wang

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style="font-size:15px;">      1 Can you apply Ziegler-Nichols oscillation tuning method to a first order system? Why?

      2 Can you apply the reaction curve based tuning rules to unstable systems? Why?

      3 How do we decide the sign of the proportional feedback controller gain when using the Ziegler-Nichols oscillation method?

      4 Can you envisage any potential danger when using Ziegler- Nichols oscillation method?

      5 How do you design a step response experiment?

      6 What information will the step response experiment provide?

      7 How do you determine steady-state gain, parameter and time delay from a reaction curve?

      8 What are your observations when comparing Ziegler-Nichols and Cohen-Coon tuning rules, in terms of signs and values of , and ?

      9 Is there any desired closed-loop performance specification among the tuning rules?

      This section will discuss the PID controller tuning rules that are derived based on a first order plus delay model. These tuning rules worked well in applications.

      

      1.4.1 IMC-PID Controller Tuning Rules

      The internal model control (IMC)-PID tuning rules (Rivera et al. (1986)) are proposed on the basis of a first order plus delay model:

equation

      When using the IMC-PID tuning rules, a desired closed-loop response is specified by the transfer function from the reference signal to the output:

equation

      where images is the desired time constant chosen by the user. The PI controller parameters are related to the first order plus delay model and the desired closed-loop time constant images, which are given as:

      (1.46)equation

      If the system has a second order transfer function with time delay in the following form:

equation

      then a PID controller is recommended. Assuming that images, then the PID controller parameters are calculated as

      (1.48)equation

      The IMC-PID controller tuning rules are also extended to integrating systems in Skogestad (2003). Although the system has an integrator as part of its dynamics, integral control is still required for disturbance rejection (see Chapter 2).

      Assuming that the system has the integrator with delay model:

      (1.49)equation

      then a PI controller is recommended with the following parameters:

      (1.50)equation

      If the transfer function for the integrating system has the form:

      (1.51)equation

      then a PID controller is recommended to have the following parameters:

      (1.52)equation

      If the system has a double integrator with the transfer function

      (1.53)equation

      then a PID controller is recommended with the following parameters:

      (1.54)equation

      The IMC-PID controller tuning rules will be studied in Examples 2.1 and 2.2.

      

      1.4.2 Padula and Visioli Tuning Rules

      Several sets of tuning rules were introduced in Padula and Visioli (2011) and Padula and Visioli (2012). These tuning rules are based on the first order plus delay model:

equation
images images
images

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