Exact(1)
After choosing suitable finite orders for truncation of Carleman linearization, finite dimensional linear and bilinear system representations are obtained for which the design of controllers and state estimators can be performed in a straightforward way.
Similar(59)
A methcxl for the derivation of optimal fuzzy system structures based upon non-linear local system representations is proposed.
A relationship between the phase spaces for both system representations is derived in this article, justifying the equivalence of the representations in the sense of preserving their Hamiltonian functions as well as their Hamiltonian symplectic forms, ultimately resulting in the same Hamiltonian flow.
These "physical systems representations" are well-suited to the prediction of some human behaviors, for example, travel times constrained by physical crowding.
However, physical systems representations are ill-suited to the task of modeling cognitively-derived human behaviors, because the mediating effects of peoples' intentions result in behavioral responses that are poorly correlated with objective measures of environmental stimuli.
In this paper, the synergism and saturation system (S-systems) representations are used to describe signal transduction networks and a control design idea is presented.
For convenience of reference this "agent-based" system representation is denoted ΣABM.
In general, neither controllability nor observability or any specific system representation is required.
A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper.
An alternative system representation is proposed to transform the measured disturbance onto system disturbance, which leads a more adequate observer structure.
Immune system representation was reduced in the top 100 list (6.6%) with multiple features for the same gene, such as T-cell receptor beta chain V region and major histocompatibility complex class II (Supplementary Table 2).
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