Name
Abstract | ||
|---|---|---|
An optimal control algorithm is proposed for impulsive differential systems, i.e., systems evolving according to ordinary differential equations between any two control actions, occurring impulsively at discrete-time instants. Measurements are as well acquired at discrete-time instants. A model-based control law is conceived for medical and healthcare frameworks and, indeed, is applied to synthesize a feedback antiangiogenic tumor therapy. To cope with unavailable or temporally sparse measurements, the control law benefits a state observer properly designed for continuous-discrete systems by suitably exploiting recent results on observers for time-delay systems. The closed-loop algorithm is validated by building up an exhaustive simulation campaign on a population of virtual subjects, each sampled from a multivariate Gaussian distribution whose mean and covariance matrix is identified from experimental data taken from the literature.
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In silico</italic>
results are encouraging and pave the way to further clinical verifications. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCST.2018.2861410 | IEEE Transactions on Control Systems Technology |
Keywords | Field | DocType |
Discretization of nonlinear systems,impulsive control,optimal control,tumor therapy | State observer,Population,Differential systems,Experimental data,Ordinary differential equation,Control theory,Optimal control algorithm,Multivariate normal distribution,Covariance matrix,Mathematics | Journal |
Volume | Issue | ISSN |
28 | 1 | 1063-6536 |
Citations | PageRank | References |
2 | 0.40 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| F. Cacace | 1 | 443 | 106.96 |
| Valerio Cusimano | 2 | 6 | 3.83 |
| Pasquale Palumbo | 3 | 86 | 22.15 |