Question 7 of 8: State-space model, controllability/observability, pole placement
Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)
Notes on this paper
Paper format. National Exams, 07-Elec-A2 Systems & Control, May 2014, 3 hours, closed book (approved calculator plus one signed 8.5 × 11" formula sheet). Questions 1 and 2 are compulsory; answer three of the remaining six (Q3–Q8). Each question is worth 20 marks. All eight are worked below so the set is a complete study resource.
Reference texts: N. S. Nise, Control Systems Engineering (7th ed., Wiley) — Routh–Hurwitz and stability (Ch. 6), steady-state error and error constants (Ch. 7), root locus (Ch. 8), PID and lag/lead design (Ch. 9–11), frequency response, Nyquist and gain/phase margins (Ch. 10–11), state space, controllability/observability and pole placement (Ch. 3, 12); K. Ogata, Modern Control Engineering (5th ed., Prentice Hall) — companion treatment of dominant-poles modelling and Mason’s rule; G. F. Franklin, J. D. Powell & A. Emami-Naeini, Feedback Control of Dynamic Systems. All block diagrams, pole–zero maps, root loci, Bode/Nyquist plots and signal-flow graphs below are redrawn as inline figures.
Reading the exam figures. Q1 supplies an open-loop Bode plot and Q6 supplies open-loop Bode plots of the process. Where a transfer function is given exactly in the text (Q1’s system is the same plant as Q2, stated exactly there), every graphical reading is also confirmed analytically and the exact model governs. Q6 is a pure graph-reading problem (no closed form given); its numeric reads are approximate and are flagged accordingly. Note the printed exam mislabels the header of the last two pages “May 2013” — this is the May 2014 sitting throughout.
Given (from Figure Q7.1). Paths give $\dot x_1=u-2x_1-x_3$, $\dot x_2=x_1-2x_3$, $\dot x_3=x_2$, $y=x_1+3x_2+x_3$, i.e. $$A=\begin{bmatrix}-2&0&-1\\1&0&-2\\0&1&0\end{bmatrix},\ B=\begin{bmatrix}1\\0\\0\end{bmatrix},\ C=\begin{bmatrix}1&3&1\end{bmatrix}.$$
Check: figure typo resolved. The extraction shows two branches from $x_2$ into $\dot x_3$ (gains $+1$ and $-1$), which would cancel and make $x_3$ uncontrollable/unobservable — flagged in the source as a likely diagram error. Taking the single integrator path $\dot x_3=x_2$ (drop the spurious $-1$) yields a controllable and observable system, consistent with the pole-placement task, so that reading is adopted.
Part A — State equations, controllability, observability [10]
Target closed-loop poles: $-3$ and $-2\pm j3$ (all in the left half-plane).
Part B — State feedback: $K$ and $k$ [10]
Approach. The control law $u=K(r-k^Tx)=Kr-g^Tx$ with $g^T=Kk^T$ places the poles; $g$ is fixed by matching characteristic polynomials, then the scalar $K$ is set by the zero-step-error (unity DC gain) condition.
Closed-loop polynomial. With $A_{cl}=A-Bg^T$ (feedback enters row 1 only), $$\det(sI-A_{cl})=s^3+(2+g_1)s^2+(2+g_2)s+(5+2g_1+g_3).$$
Match → $g=Kk$. $2+g_1=7,\ 2+g_2=25,\ 5+2g_1+g_3=39$ give $$g=Kk=\begin{bmatrix}5&23&24\end{bmatrix}^T.$$
Fix $K$ from zero step error. Closed-loop DC gain $C(-A_{cl})^{-1}BK=\dfrac{K}{13}$ must equal $1$ (unity reference tracking), so $$\boxed{K=13},\qquad k=\frac{g}{K}=\begin{bmatrix}\tfrac{5}{13}&\tfrac{23}{13}&\tfrac{24}{13}\end{bmatrix}^T=\begin{bmatrix}0.385&1.769&1.846\end{bmatrix}^T.$$
Check. Eigenvalues of $A_{cl}=A-B(Kk)^T=\begin{bmatrix}-7&-23&-25\\1&0&-2\\0&1&0\end{bmatrix}$ are $-3,\,-2\pm j3$ ✓, and the DC gain is exactly $1$ (zero step error) ✓.