Theory of servo-mechanisms

Hazen, H. L.

doi:10.1016/s0016-0032(34)90254-4

Cited by 89 publications

(9 citation statements)

References 6 publications

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“…Tirrill at General Electric in 1902 in order to control electric generators. In the following years, the theory of controllers incorporating relays and discontinuities was further elaborated (Házen, 1934;Andronov & Chaikin, 1937Oldenbourg & Sartorius, 1948;Truxal, 1955;Smith, 1958;Zypkin, 1958). Based on the knowledge of these relay controls, controls switching between several subcontrollers were developed over the period 1940 through 1960 and those controls might well be the first to be rightly called "variablestructure controls" (VSC).…”

Section: Early Discontinuous Controlsmentioning

confidence: 99%

Soft variable-structure controls: a survey

2004

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Variable-structure controls are normally understood to be controls that have sliding modes and robustness as their main objective. In addition to sliding-mode controls, there are also variable-structure controls, which were developed for the purpose of intentionally precluding sliding modes and achieving high regulation rates and short settling times. Two types of such controls may be distinguished, variable-structure controls that switch between different parameters and a systematic further development of them called "soft variable-structure controls" that continuously vary controllers' parameters or structures and achieve nearly time-optimal control performance. This paper surveys soft variable-structure controls, compares them to other controls, taking a submarine dive-control as an example, and presents an outlook on their auspicious further development.

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Section: Early Discontinuous Controlsmentioning

confidence: 99%

Soft variable-structure controls: a survey

2004

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“…In this view, disruption of plus‐end function of microtubules near the site might cause differences in delivery of signaling components; such differences would then become amplified. In controlled systems, including servo systems (Hanzen, ) and electronic amplifiers (Armstrong, ; Franklin, ; Meissner, ), positive feedbacks can improve performance, but without damping or negative feedback, such systems are prone to instability (Bennett, ). In the PRS, impact of positive feedbacks on system performance is further affected by the fact that system components are in limited supply [for example there are only ~2,000 molecules of the Gβ, Ste4, per cell (Thomson et al , )], so that the autostimulatory molecular events that generate a robust second signaling site can only occur after a first site falls apart.…”

Section: Discussionmentioning

confidence: 99%

Single‐cell profiling screen identifies microtubule‐dependent reduction of variability in signaling

Pesce

Zdraljevic

Peria

et al. 2018

Molecular Systems Biology

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Populations of isogenic cells often respond coherently to signals, despite differences in protein abundance and cell state. Previously, we uncovered processes in the Saccharomyces cerevisiae pheromone response system (PRS) that reduced cell‐to‐cell variability in signal strength and cellular response. Here, we screened 1,141 non‐essential genes to identify 50 “variability genes”. Most had distinct, separable effects on strength and variability of the PRS, defining these quantities as genetically distinct “axes” of system behavior. Three genes affected cytoplasmic microtubule function: BIM1, GIM2, and GIM4. We used genetic and chemical perturbations to show that, without microtubules, PRS output is reduced but variability is unaffected, while, when microtubules are present but their function is perturbed, output is sometimes lowered, but its variability is always high. The increased variability caused by microtubule perturbations required the PRS MAP kinase Fus3 and a process at or upstream of Ste5, the membrane‐localized scaffold to which Fus3 must bind to be activated. Visualization of Ste5 localization dynamics demonstrated that perturbing microtubules destabilized Ste5 at the membrane signaling site. The fact that such microtubule perturbations cause aberrant fate and polarity decisions in mammals suggests that microtubule‐dependent signal stabilization might also operate throughout metazoans.

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“…According to the control system models, control analysis and design can be done in either time or frequency domain, which are based on the state-space or transfer function models. Classical (versus modern) control theory based on frequency-domain modelling was matured before 1950s [47][48][49]. The frequency response function GðjxÞ can be formally derived from the transfer function G(s) in Eq.…”

Section: A Brief Introduction To Analysis and Design Methodologiesmentioning

confidence: 99%