Question 20.4: Consider the transfer function model of Exercise 20.1. For e...

Consider the transfer function model of Exercise 20.1. For each of the four sets of design parameters shown below, design a model predictive controller. Then do the following:

(a) Compare the controllers for a unit step change in set point. Consider both the y and u responses.

(b) Repeat the comparison of (a) for a unit step change in disturbance, assuming that G_{d}(s)=G(s).

(c) Which controller provides the best performance? Justify your answer.

Set No. Δt N M P R
(i) 2 40 1 5 0
(ii) 2 40 20 20 0
(iii) 2 40 3 10 0.01
(iv) 2 40 3 10 0.1
The Blue Check Mark means that this solution has been answered and checked by an expert. This guarantees that the final answer is accurate.
Learn more on how we answer questions.

The step response is obtained from the analytical unit step response as in Example 20.1. The feedback matrix K _{c} is obtained using Eq. 20-65 as in Example 20.5. These results are not reported here for sake of brevity. The closed-loop response for set-point and disturbance changes are shown below for each case. The MATLAB MPC Toolbox was used for the simulations.

K _{c} \triangleq\left( S ^{T} Q S + R \right)^{-1} S ^{T} Q         (20-65)

i) For this model horizon, the step response is over 99 \% complete as in Example 20.5; hence the model is good. The set-point and disturbance responses shown below are non-oscillatory and have long settling times

ii) The set-point response shown below exhibits same overshoot, smaller settling time and undesirable “ringing” in u compared to part i). The disturbance response shows a smaller peak value, a lack of oscillations, and faster settling of the manipulated input.

iii) The set-point and disturbance responses shown below show the same trends as in part i).

iv) The set-point and load responses shown below exhibit the same trends as in parts (i) and (ii). In comparison to part (iii), this controller has a larger penalty on the manipulated input and, as a result, leads to smaller and less oscillatory input effort at the expense of larger overshoot and settling time for the controlled variable.

20.4a
20.4b
20.4c
20.4d
20.4e
20.4f
20.4g
20.4h

Related Answered Questions