Table of Contents

1 PID Control Schemes

1.1 Motivation

  • So far, we design controller/compensator based on models of plants(transfer function, Bode plot).
  • However, in many practical situations, we deal with very complicated plants whose mathematical models are difficult to obtain. Hence, the analytical approach of designing a controller is not possible.
  • In this chapter, we shall introduce tuning rules for basic PID controllers.
  • More than half of industrial plants today still employ PID control schemes.

1.2 PID Controller

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  • The standard form of PID controller is \[C(s) = K_p\left(1+\frac{1}{T_is}+T_ds\right) = K_p+\frac{K_I}{s}+K_Ds.\]
  • P(Proportional) action: P-action provides an action which depends on the instantaneous value of the control error. It can be used to improve speed of response and steady-state error but with limited performance.
  • I (Integral) action: I-action gives a controller output that is proportional to the accumulated error, which implies that it is a slow reaction control mode. It is used to achieve zero-steady error in the presence of a step reference and/or disturbance. The shortcomings are: its pole at the origin is detrimental to loop stability and undesirable effect in the presence of actuator saturation, known as wind-up.
  • D (Derivative) action: It acts on the changing rate of the control error, sometimes referred to as a predictive mode. Its limitation is the tendency to yield large control signals in response to high frequency control errors such as error induced by set-point changes or measurement noises.

1.3 Ziegler-Nichols Rules

  • The process of selecting the controller parameters \(K_p\), \(T_i\) and \(T_d\) is known as PID Tuning.
  • Two classical methods for determining the parameters of PID controllers were presented by Ziegler-Nichols in 1942.
    • Step response method
    • Self-oscillation method
  • \(K_p\), \(T_i\) and \(T_d\) from Ziegler-Nichols rule often serve as the starting point for tuning procedures used by manufacturers and process industry.
  • It typically yields an aggressive gain and overshoot. Further tuning is needed if minimizing overshoot is desirable.

1.4 Step Response Method

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  • Many plants, particularly those in the process industries has step response of S-shape (reaction curve):
    • open-loop stable
    • no integrator
    • no dominant complex poles
  • An experiment for deriving step response can be designed as
    • With the plant in open-loop, let the plant run at normal operating condition with constant input \(u_0\) and steady state output \(y_0\) .
    • At the initial time \(t_0\) , apply a step change to the plant, from \(u_0\) to \(u_\infty\) (in the range of 10 to 20% of full scale).
    • Record the output response to get the reaction curve. In the figure, the m.s.t. stands for the maximum slope tangent.
    • Compute \[K = \frac{y_\infty-y_0}{u_\infty-u_0},\,L=t_1-t_0,T = t_2-t_1.\] \(K\) is the system gain. \(L\) and \(T\) are often called the apparent dead time and the apparent time constant.
  • The PID parameters are then chosen according to the table
Controller \(K_p\) \(T_i\) \(T_d\)
P \(T/KL\)    
PI \(0.9T/KL\) \(3L\)  
PID \(1.2T/KL\) \(2L\) \(0.5L\)

1.4.1 Example

Consider a plant with transfer function \[G(s) = \frac{5}{(s+1)^3}.\]

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  • From the unit step response, it is known that \[K = 5/1 = 5,\,L = 0.8,\,T = 4.5-0.8 = 3.7.\]
  • The PID parameters given by Ziegler-Nichols tuning rule is \[K_p = 1.11,\,T_i = 1.60,\,T_d = 0.40.\]

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1.5 Self-Oscillation Method

  • Set the integrator and derivative gain to \(0\).
  • Increase the proportional gain \(K_p\) from \(0\), until the closed-loop system starts oscillation.
  • Record the critical propotional gain \(K_{cr}\) and the oscillation period \(P_{cr}\).
  • Notice that if the open-loop transfer function of the plant is given, then
    • The critical gain is the gain margin, i.e., \(K_{cr} = K_g\).
    • The critical oscillation period is related to the phase crossover frequency: \[P_{cr} = 2\pi/\omega_\phi.\]
  • Set the PID controller according to
Controller \(K_p\) \(T_i\) \(T_d\)
P \(0.5K_{cr}\)    
PI \(0.45K_{cr}\) \(P_{cr}/1.2\)  
PID \(0.6K_{cr}\) \(0.5P_{cr}\) \(0.125P_{cr}\)

1.5.1 Example

  • Consider the same plant with transfer function \[G(s) = \frac{5}{(s+1)^3}.\]
  • The phase crossover happens when \(\angle G(j\omega_\phi) = -180^\circ\), which implies that \[\angle 1+j\omega_\phi = 60^\circ\Rightarrow\omega_\phi = \sqrt{3}.\]
  • The corresponding magnitude is \(|G(j\sqrt{3})| = 5/8\) and hence the gain margin/critical gain is \(1.6\).
  • The critical period is \(2\pi/\sqrt{3} = 3.63\).
  • The PID parameters according to Ziegler-Nichols rule is \[K_p = 0.96,\, T_i=1.81,\,T_d = 0.453.\]

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1.6 Remarks

  • Ziegler-Nichols tuning typically yields an aggressive gain and overshoot, which may be unacceptable in some applications.
  • However, it can serve as a starting point for finer tuning.
  • For example, by increasing \(T_i\) and \(T_d\), we can expect the overshoot will be reduced.
  • However, for certain applications where the measurement noise is significant, we need to be extra careful when increasing \(T_d\).
  • Ziegler-Nichols tuning rules have been widely used in process control where the plant dynamics are unknown. When the plant model is available, other controller design methods exists.
  • Generally, to apply the step response method, one needs to obtain the S-shape response. Plants with complicated dynamics but no integrators are usually the cases.
  • The self-oscillation method requires the plant to be forced into oscillation. This can be expensive and dangerous.