Some practical insights into the relationship between initial state uncertainty and mesoscale predictability

1983 ◽  
Author(s):  
Thomas T. Warner ◽  
Daniel Keyser ◽  
Louis W. Uccellini
Keyword(s):  
Initial State ◽  
State Uncertainty ◽  
The Relationship

scholarly journals Design and Optimal Control of a Multistable, Cooperative Microactuator

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 183
Author(s):  
Michael Olbrich ◽  
Arwed Schütz ◽  
Tamara Bechtold ◽  
Christoph Ament
Keyword(s):  
Deflection Angle ◽  
Initial State ◽  
New Concepts ◽  
Vertical Displacements ◽  
State Uncertainty ◽  
Stable Equilibria ◽  
Freely Moving ◽  
Time And Energy ◽  
Multiple Stable Equilibria ◽  
Optimal Trajectory Planning

In order to satisfy the demand for the high functionality of future microdevices, research on new concepts for multistable microactuators with enlarged working ranges becomes increasingly important. A challenge for the design of such actuators lies in overcoming the mechanical connections of the moved object, which limit its deflection angle or traveling distance. Although numerous approaches have already been proposed to solve this issue, only a few have considered multiple asymptotically stable resting positions. In order to fill this gap, we present a microactuator that allows large vertical displacements of a freely moving permanent magnet on a millimeter-scale. Multiple stable equilibria are generated at predefined positions by superimposing permanent magnetic fields, thus removing the need for constant energy input. In order to achieve fast object movements with low solenoid currents, we apply a combination of piezoelectric and electromagnetic actuation, which work as cooperative manipulators. Optimal trajectory planning and flatness-based control ensure time- and energy-efficient motion while being able to compensate for disturbances. We demonstrate the advantage of the proposed actuator in terms of its expandability and show the effectiveness of the controller with regard to the initial state uncertainty.

Research the Influence of Part State Sliding Surface on SMC Chattering

2014 ◽  
Vol 543-547 ◽  
pp. 203-206
Author(s):  
Yu Shen ◽  
Yi Fan
Keyword(s):  
Accurate Estimation ◽  
Sliding Surface ◽  
Describing Function ◽  
Response Curves ◽  
Initial State ◽  
Surface Design ◽  
State Selection ◽  
The Relationship

The influence of sliding surface on SMC design is considered. How the sliding surface affect the chattering frequency and amplitude is investigated by describing function (DF) approach. In part-state sliding surface SMC, the chattering can be changed by feedback state selection. The relationship between chattering types and initial state values is analyzed. The proposed approach is proved has sufficient accurate estimation and judgment by simulation response curves. Simulation curves show that sliding surface design plays important roles in chattering frequency and amplitude.

scholarly journals Implicit Coordination Using FOND Planning

2020 ◽  
Vol 34 (05) ◽  
pp. 7151-7159
Author(s):  
Thorsten Engesser ◽  
Tim Miller
Keyword(s):  
Computational Complexity ◽  
The Other ◽  
Path Finding ◽  
Initial State ◽  
Arbitrary Initial State ◽  
State Uncertainty ◽  
Multi Agent ◽  
Decidable Fragment ◽  
Implicit Coordination

Epistemic planning can be used to achieve implicit coordination in cooperative multi-agent settings where knowledge and capabilities are distributed between the agents. In these scenarios, agents plan and act on their own without having to agree on a common plan or protocol beforehand. However, epistemic planning is undecidable in general. In this paper, we show how implicit coordination can be achieved in a simpler, propositional setting by using nondeterminism as a means to allow the agents to take the other agents' perspectives. We identify a decidable fragment of epistemic planning that allows for arbitrary initial state uncertainty and non-determinism, but where actions can never increase the uncertainty of the agents. We show that in this fragment, planning for implicit coordination can be reduced to a version of fully observable nondeterministic (FOND) planning and that it thus has the same computational complexity as FOND planning. We provide a small case study, modeling the problem of multi-agent path finding with destination uncertainty in FOND, to show that our approach can be successfully applied in practice.

scholarly journals Stress states and moment rates of a two-asperity fault in the presence of viscoelastic relaxation

2015 ◽  
Vol 2 (1) ◽  
pp. 297-327
Author(s):  
M. Dragoni ◽  
E. Lorenzano
Keyword(s):  
Discrete Dynamical System ◽  
Constant Strain Rate ◽  
The State ◽  
Viscoelastic Deformation ◽  
Initial State ◽  
Tectonic Plates ◽  
Stress States ◽  
The Moment ◽  
Postseismic Relaxation ◽  
The Relationship

Abstract. A fault containing two asperities with different strengths is considered. The fault is embedded in a viscoelastic shear zone, subject to a constant strain rate by the motions of adjacent tectonic plates. The fault is modelled as a discrete dynamical system where the average values of stress, friction and slip on each asperity are considered. The state of the fault is described by three variables: the slip deficits of the asperities and the viscoelastic deformation. The system has four dynamic modes, for which the analytical solutions are calculated. The relationship between the state of the fault before a seismic event and the sequence of slipping modes in the event is enlightened. Since the moment rate depends on the number and sequence of slipping modes, the knowledge of the source function of an earthquake constrains the orbit of the system in the phase space. If the source functions of a larger number of consecutive earthquakes were known, the orbit could be constrained more and more and its evolution could be predicted with a smaller uncertainty. The model is applied to the 1964 Alaska earthquake, which was the effect of the failure of two asperities and for which a remarkable postseismic relaxation has been observed in the subsequent decades. The evolution of the system after the 1964 event depends on the state from which the event was originated, that is constrained by the observed moment rate. The possible durations of the interseismic interval and the possible moment rates of the next earthquake are calculated as functions of the initial state.

Issues in Linguistics: A View From the Outside

1988 ◽  
Vol 33 (4) ◽  
pp. 507-511
Author(s):  
Jayant K. Lele
Keyword(s):  
Physical Mechanism ◽  
Native Speaker ◽  
Ideal Type ◽  
Linguistic Theory ◽  
State Condition ◽  
Initial State ◽  
Language Faculty ◽  
External Evidence ◽  
Species Specific ◽  
The Relationship

To an outsider looking at linguistic theory, the problem of internal vs. external evidence seems to arise out of a conflation of two relatively distinct enterprises. The first of these tries to establish a claim that there is a distinct, organic, language faculty (a language organ), that is, a species-specific characteristic common to all humans. The second is an attempt to abstract from the facts of diversity a structure that has equivalent universal characteristics and thus can be seen as an ideal type or as an ideal initial state condition (of a pure and uniform experience) under which a language is acquired by a native speaker. As I understand it, the relationship between these two enterprises is yet to be fully determined given the fact that the physical mechanism that has been deduced to correspond to a property of mind is as of now largely unknown.

scholarly journals Persistent Neural States: Stationary Localized Activity Patterns in Nonlinear Continuous n-Population, q-Dimensional Neural Networks

2009 ◽  
Vol 21 (1) ◽  
pp. 147-187 ◽  
Author(s):  
Olivier Faugeras ◽  
Romain Veltz ◽  
François Grimbert
Keyword(s):  
Activity Patterns ◽  
Sufficient Conditions ◽  
Independent Solution ◽  
Heaviside Function ◽  
Time Behavior ◽  
Initial State ◽  
Neuron Populations ◽  
Domain Of Existence ◽  
The Relationship ◽  
Theoretical Results

Neural continuum networks are an important aspect of the modeling of macroscopic parts of the cortex. Two classes of such networks are considered: voltage and activity based. In both cases, our networks contain an arbitrary number, n, of interacting neuron populations. Spatial nonsymmetric connectivity functions represent cortico-cortical, local connections, and external inputs represent nonlocal connections. Sigmoidal nonlinearities model the relationship between (average) membrane potential and activity. Departing from most of the previous work in this area, we do not assume the nonlinearity to be singular, that is, represented by the discontinuous Heaviside function. Another important difference from previous work is that we relax the assumption that the domain of definition where we study these networks is infinite, that is, equal to [Formula: see text] or [Formula: see text]. We explicitly consider the biologically more relevant case of a bounded subset Ω of [Formula: see text], a better model of a piece of cortex. The time behavior of these networks is described by systems of integro-differential equations. Using methods of functional analysis, we study the existence and uniqueness of a stationary (i.e., time-independent) solution of these equations in the case of a stationary input. These solutions can be seen as ‘persistent’; they are also sometimes called bumps. We show that under very mild assumptions on the connectivity functions and because we do not use the Heaviside function for the nonlinearities, such solutions always exist. We also give sufficient conditions on the connectivity functions for the solution to be absolutely stable, that is, independent of the initial state of the network. We then study the sensitivity of the solutions to variations of such parameters as the connectivity functions, the sigmoids, the external inputs, and, last but not least, the shape of the domain of existence Ω of the neural continuum networks. These theoretical results are illustrated and corroborated by a large number of numerical experiments in most of the cases 2 ⩽ n ⩽ 3, 2 ⩽ q ⩽ 3.

S-R Theory and Dynamic Theory 1

1971 ◽  
Vol 1 (2) ◽  
pp. 173-184
Author(s):  
Joseph Schubert
Keyword(s):  
Dynamic Theory ◽  
The State ◽  
Initial State ◽  
Wide Range ◽  
External Events ◽  
The Law ◽  
The Relationship ◽  
Methodological Difficulties ◽  
Observed Behavior

AbstractS-R theorists formulate psychological laws in terms of the relationship between external events and observed behavior. The state of the organism delimits the applicability of the law. Dynamic theorists formulate psychological laws in terms of the relationship between the initial state of the organism Oa and its subsequent state On. The significance of the stimulus is determined by .Oa and the principle of equifinality implies the equivalence of a wide range of behaviors by which On may be reached. It is maintained that regardless of the methodological difficulties inherent in a theory which is based on variables that cannot be observed directly, dynamic theory is testable in principle and in practice. It is suggested that recent neurophysiological theory is incompatible with an S-R approach.

State Estimation With Initial State Uncertainty

2008 ◽  
Vol 54 (1) ◽  
pp. 235-254 ◽  
Author(s):  
Yoav Levinbook ◽  
Tan F. Wong
Keyword(s):  
State Estimation ◽  
Initial State ◽  
State Uncertainty

scholarly journals Comparison between two generalized Nash models with a same non-zero initial condition

2021 ◽  
Author(s):  
Baowei Yan ◽  
Yu Liu ◽  
Zhengkun Li ◽  
Huining Jiang
Keyword(s):  
Cascade Model ◽  
Initial Condition ◽  
Initial State ◽  
Zero Initial Condition ◽  
Current State ◽  
Forecast Precision ◽  
Saint Venant Equations ◽  
Streamflow Data ◽  
Initial Storage ◽  
The Relationship

Abstract Initial condition can impact the forecast precision especially in a real-time forecasting stage. The discrete linear cascade model (DLCM) and the generalized Nash model (GNM), though expressed in different ways, are both the generalization of the Nash cascade model considering the initial condition. This paper investigates the relationship and difference between DLCM and GNM both mathematically and experimentally. Mathematically, the main difference lies in the way to estimate the initial storage state. In the DLCM, the initial state is estimated and not unique, while that in the GNM is observed and unique. Hence, the GNM is the exact solution of the Nash cascade model, while the DLCM is an approximate solution and it can be transformed to the GNM when the initial storage state is calculated by the approach suggested in the GNM. As a discrete solution, the DLCM can be directly applied to the practical discrete streamflow data system. However, the numerical calculation approach such as the finite difference method is often used to make the GNM practically applicable. At last, a test example obtained by the solution of the Saint-Venant equations is used to illustrate this difference. The results show that the GNM provides a unique solution while the DLCM has multiple solutions, whose forecast precision depends upon the estimate accuracy of the current state.

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