High Fidelity Fast Simulation of Human in the Loop Human in the Plant (HIL-HIP) Systems
This work addresses simulation efficiency for artificial pancreas systems in Type 1 Diabetes management, representing an incremental improvement in domain-specific simulation methods.
The paper tackles the problem of simulation slowdown in wireless network-controlled human-in-the-loop/plant systems due to time-varying non-linearities, achieving accurate simulation with over 2.1 times speedup using a piecewise linear time-invariant approach.
Non-linearities in simulation arise from the time variance in wireless mobile networks when integrated with human in the loop, human in the plant (HIL-HIP) physical systems under dynamic contexts, leading to simulation slowdown. Time variance is handled by deriving a series of piece wise linear time invariant simulations (PLIS) in intervals, which are then concatenated in time domain. In this paper, we conduct a formal analysis of the impact of discretizing time-varying components in wireless network-controlled HIL-HIP systems on simulation accuracy and speedup, and evaluate trade-offs with reliable guarantees. We develop an accurate simulation framework for an artificial pancreas wireless network system that controls blood glucose in Type 1 Diabetes patients with time varying properties such as physiological changes associated with psychological stress and meal patterns. PLIS approach achieves accurate simulation with greater than 2.1 times speedup than a non-linear system simulation for the given dataset.