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Dielectrophoretic Particle OED: Difference between revisions

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<math>
<math>
  \begin{array}{lll}
  \begin{array}{lll}
  \displaystyle \min_{y,G,F,z,w} && \text{trace} \; \left( F^{-1}(t_f) \right) \\
  \displaystyle \min_{x,G,F,z,w,u} && \text{trace} \; \left( F^{-1}(t_f) \right) \\
  \text{subject to} \\
  \text{subject to} \\
\quad \dot{y}(t) & = & f(y(t),\theta) \\
\quad \dot{x}(t) & = & f(x(t),\theta) \\
\quad \dot{G}(t) & = & f_y(y(t),\theta) G(t) + f_\theta(y(t),\theta) \\
\quad \dot{G}(t) & = & f_x(x(t),\theta) G(t) + f_\theta(x(t),\theta) \\
\quad \dot{F}(t) & = & \sum_{i=1}^{n_o} w_i(t)(h^i_y(y(t))G(t))^T(h^i_y(y(t))G(t)) \\
\quad \dot{F}(t) & = & \sum_{i=1}^{n_o} w_i(t)(h^i_x(x(t))G(t))^T(h^i_x(x(t))G(t)) \\
\quad \dot{z}(t) & = & w(t), \\
\quad \dot{z}(t) & = & w(t), \\
\quad y(0) & = & y_0 \\
\quad x(0) & = & x_0 \\
\quad G(0) & = & \frac{\partial y(0)}{\partial \theta} \\
\quad G(0) & = & \frac{\partial x(0)}{\partial \theta} \\
\quad F(0) & = & 0, \\  
\quad F(0) & = & 0, \\  
\quad z(0) & = & 0 \\
\quad z(0) & = & 0 \\
\quad u(t) & \in & \mathcal{U} \\
\quad w(t) & \in & \mathcal{W} \\
\quad w(t) & \in & \mathcal{W} \\
\quad z_i(t_f) & \leq & M_i
\quad z_i(t_f) & \leq & M_i

Revision as of 07:46, 27 January 2026

Dielectrophoretic Particle OED
State dimension: 1
Differential states: 13
Discrete control functions: 3


The Dielectrophoretic Particle OED problem is a variation of the Dielectrophoretic Particle problem. It looks for optimal time intervals to measure the two states in order to minimize the uncertainty of a follow-up parameter estimation problem for the two unknown parameters.

The mathematical equations form a small-scale ODE model. It also includes state sensitivities, the Fisher information matrix entries and integrated sampling states.

Mathematical formulation

We are interested in estimating the parameters α and c of the initial value problem

x1˙(t)=x2(t)u(t)+αu(t)2,t[0,tf],x1(0)=1,x2˙(t)=cx2(t)+u(t),t[0,tf],x2(0)=0.

The initial values and tf=10 are fixed. We are interested in how to choose the control u and when to measure, with an upper bound M on the measuring time. We can measure the states directly, h1(x(t))=x1(t) and h2(x(t))=x2(t). We use two different sampling functions, w1() and w2() in the same experimental setting. This can be seen either as a two-dimensional measurement function h(x(t)), or as a special case of a multiple experiment, in which u(),x(), and G() are identical.

Now we formulate the OED problem:

minx,G,F,z,w,utrace(F1(tf))subject tox˙(t)=f(x(t),θ)G˙(t)=fx(x(t),θ)G(t)+fθ(x(t),θ)F˙(t)=i=1nowi(t)(hxi(x(t))G(t))T(hxi(x(t))G(t))z˙(t)=w(t),x(0)=x0G(0)=x(0)θF(0)=0,z(0)=0u(t)𝒰w(t)𝒲zi(tf)Mi

The evolution of the symmetric matrix F:[0,tf]2×2 is given by the weighted sum of observability Gramians hyi(y(t))G(t), i=1,2 for each observed function of states.

Parameters

We use tf=8, α=0.75, and c=1. The upper bound on the measurement time intervals is chosen as M1=M2=2.

Reference Solutions

Here is one local solution to the above control problem.

References

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