Modeling — Question 8

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Question 8

An ideal temperature controller is modeled in dimensionless variables. The room temperature is 00, the target is 11, and the scaled heater output is P(t)P(t). The plant obeys T′=−T+PT'=-T+P. A controller with memory sets P(t)=k∫0t[1−T(τ)]dτ,T(0)=0,k>0.P(t)=k\int_0^t[1-T(\tau)]\,d\tau,\qquad T(0)=0,\qquad k>0. There is no heater saturation, delay or heat-source noise in this ideal model.

Tasks

  1. Convert the plant and controller into a two-state autonomous IVP. Find its equilibrium and explain why PP is a state rather than a fixed parameter.

  2. Shift to the equilibrium and show it attracts every initial state for every k>0k>0. Classify the eigenvalues at the critical gain.

  3. For k=1/4k=1/4, solve the specified IVP. Prove both TT and PP stay in [0,1)[0,1) at finite times and increase toward 11. Sketch them.

  4. Replace the memory controller by the proportional rule P=k(1−T)P=k(1-T), with the same k>0k>0. Find its limiting temperature and explain the difference in steady error and the practical scope of the ideal memory model.

Original worksheet page 1: question and worked solution for 5-12-008
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Question 8 – Solution

Strategy. The accumulated error supplies an additional state; its equilibrium condition eliminates the temperature offset of proportional feedback.

Step 1: Introduce the controller state. Differentiation gives T′=−T+P,P′=k(1−T),(T(0),P(0))=(0,0).\boxed{T'=-T+P,\quad P'=k(1-T),\quad (T(0),P(0))=(0,0).} At equilibrium, T=1T=1 and P=1P=1. Heater output depends on accumulated past error, so two states with the same temperature can have different future motion if their current PP values differ.

Step 2: Check stability and the critical gain. For x=T−1x=T-1, u=P−1u=P-1, the matrix is (−11−k0)\left(\begin{smallmatrix}-1&1\\-k&0\end{smallmatrix}\right). Its roots are (−1±1−4k)/2(-1\pm\sqrt{1-4k})/2. For 0<k<1/40<k<1/4 both are real and negative; at k=1/4k=1/4 there is a repeated root −1/2-1/2; for k>1/4k>1/4 they are complex with real part −1/2-1/2. Every homogeneous mode decays, including the polynomial times exponential at the repeated root. Thus the equilibrium attracts every initial state within this ideal linear model.

Step 3: Solve the critical-gain response. Eliminating PP gives T″+T′+T/4=1/4T''+T'+T/4=1/4, with T(0)=T′(0)=0T(0)=T'(0)=0. The repeated-root solution and P=T′+TP=T'+T yield T=1−(1+t/2)e−t/2,P=1−(1+t/4)e−t/2.\boxed{T=1-(1+t/2)e^{-t/2},\qquad P=1-(1+t/4)e^{-t/2}.} The initial values vanish and T′=te−t/2/4≥0T'=te^{-t/2}/4\ge 0, P′=(1/4+t/8)e−t/2>0P'=(1/4+t/8)e^{-t/2}>0. The latter equals (1−T)/4(1-T)/4, checking the controller equation. The positive subtracted terms and monotonicity imply 0≤T,P<10\le T,P<1 at finite tt, and both tend to 11. Here the heater output stays nonnegative without needing a saturation rule.

Step 4: Compare steady errors. Proportional feedback instead gives T′=k−(1+k)TT'=k-(1+k)T, so T→k/(1+k)T\to k/(1+k) and the steady error is 1/(1+k)>0\boxed{1/(1+k)>0}. The memory controller can retain P=1P=1 even when the current error is zero; a proportional controller would then set P=0P=0. Real actuator limits and delays can change stability or feasibility, so the ideal conclusions apply under the stated assumptions, not to every physical controller.

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