Strong “bottom-up” influences on small mammal populations: State-space model analyses from long-term studies

Summary Objectives: We developed a robust, long-term clinical prediction model to predict conditions leading to early diabetes using laboratory values other than blood glucose and insulin levels. Our model protects against missing data and noise that occur during long-term analysis. Methods: Results of a 75-g oral glucose tolerance test (OGTT) were divided into three groups: diabetes, impaired glucose tolerance (IGT), and normal (n = 114, 235, and 325, respectively). For glucose metabolic and lipid metabolic parameters, near 30-day mean values and 10-year integrated values were compared. The relation between high-density lipoprotein cholesterol (HDL-C) and variations in HbA1c was analyzed in 158 patients. We also constructed a state space model consisting of an observation model (HDL-C and HbA1c) and an internal model (disorders of lipid metabolism and glucose metabolism) and applied this model to 116 cases. Results: The root mean square error between the observed HbA1c and predicted HbA1c was 0.25. Conclusions: In the observation model, HDL-C levels were useful for prediction of increases in HbA1c. Even with numerous missing values over time, as occurs in clinical practice, clinically valid predictions can be made using this state space model.

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Structural Analysis and Control of a Model of Two-Site Electricity and Heat Supply

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4043703 ◽

2019 ◽

Vol 141 (10) ◽

Author(s):

Hikaru Hoshino ◽

Yoshihiko Susuki ◽

T. John Koo ◽

Takashi Hikihara

Keyword(s):

Control Problem ◽

Equilibrium Point ◽

State Space ◽

Heat Supply ◽

State Space Model ◽

The State ◽

Model Parameters ◽

Space Model ◽

Energy Flows

This paper introduces a control problem of regulation of energy flows in a two-site electricity and heat supply system, where two combined heat and power (CHP) plants are interconnected via electricity and heat flows. The control problem is motivated by recent development of fast operation of CHP plants to provide ancillary services of power system on the order of tens of seconds to minutes. Due to the physical constraint that the responses of the heat subsystem are not necessary as fast as those of the electric subsystem, the target controlled state is not represented by any isolated equilibrium point, implying that stability of the system is lost in the long-term sense on the order of hours. In this paper, we first prove in the context of nonlinear control theory that the state-space model of the two-site system is nonminimum phase due to nonexistence of isolated equilibrium points of the associated zero dynamics. Instead, we locate a one-dimensional (1D) invariant manifold that represents the target controlled flows completely. Then, by utilizing a virtual output under which the state-space model becomes minimum phase, we synthesize a controller that achieves not only the regulation of energy flows in the short-term regime but also stabilization of an equilibrium point in the long-term regime. Effectiveness of the synthesized controller is established with numerical simulations with a practical set of model parameters.

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