Networks of theta neurons with time-varying excitability: Macroscopic chaos, multistability, and final-state uncertainty

2014 ◽  
Vol 267 ◽  
pp. 16-26 ◽  
Author(s):  
Paul So ◽  
Tanushree B. Luke ◽  
Ernest Barreto
Keyword(s):  
Time Varying ◽  
Final State ◽  
State Uncertainty ◽  
Theta Neurons

On the Design of Finite Time Settling Control for Linear Systems

1992 ◽  
Vol 114 (3) ◽  
pp. 359-368 ◽  
Author(s):  
S. Choura
Keyword(s):  
Linear System ◽  
Linear Systems ◽  
Finite Time ◽  
Linear Time ◽  
Minimum Energy ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Final State ◽  
Variable Function ◽  
Time Varying Systems

The design of controllers combining feedback and feedforward for the finite time settling control of linear systems, including linear time-varying systems, is considered. The feedforward part transfers the initial state of a linear system to a desired final state in finite time, and the feedback part reduces the effects of uncertainties and disturbances on the system performance. Two methods for determining the feedforward part, without requiring the knowledge of the explicit state solutions, are proposed. In the first method, a numerical procedure for approximating combined controls that drive linear time-varying systems to their final state in finite time is given. The feedforward part is a variable function of time and is selected based on a set of necessary conditions, such as magnitude constraints. In the second method, an analytical procedure for constructing combined controls for linear time-invariant systems is presented, where the feedforward part is accurately determined and it is of the minimum energy control type. It is shown that both methods facilitate the design of the feedforward part of combined controllers for the finite time settling of linear systems. The robustness of driving a linear system to its desired state in finite time is analyzed for three types of uncertainties. The robustness analysis suggests a modification of the feedforward control law to assure the robustness of the control strategy to parameter uncertainties for arbitrary final times.

Software Development of Large-Span Structure Hoisting on the Time-Varying Analysis

2011 ◽  
Vol 99-100 ◽  
pp. 1269-1273
Author(s):  
Xiao Yan Jiang ◽  
Hai Ying Wan ◽  
Jian Guo Wang
Keyword(s):  
Three Dimensional ◽  
Internal Force ◽  
Simulation Software ◽  
Transformation Matrix ◽  
Time Varying ◽  
State Matrix ◽  
Final State ◽  
Large Span ◽  
Analysis Theory ◽  
Open Inventor

According to the time-varying analysis theory of large-span structure hoisting, the structure transformation matrix around three-dimensional translation and rotation is obtained. Based on the obtained transformation matrix, the final state matrix after structure hoisting can be described, and the structural internal force of any position can be calculated. Using the Coin3d Open Inventor that is an open source graphics development kit, developers exploited simulation software of large-span structure hoisting. The software can analyze structural security with the time-varying analysis theory, and it has been applied in the simulation of hoisting construction at the Hefei Xinqiao international airport. The results indicated the software is reliable to protect safety of structure hoisting.

On the Final States of Shallow Arches on Elastic Foundations Subjected to Dynamical Loads

1968 ◽  
Vol 35 (4) ◽  
pp. 713-723 ◽  
Author(s):  
C. S. Hsu ◽  
C. T. Kuo ◽  
S. S. Lee
Keyword(s):  
Sufficient Conditions ◽  
Spatial Distributions ◽  
Time Varying ◽  
Final State ◽  
Shallow Arches ◽  
Elastic Foundations ◽  
Linear Elastic ◽  
Wide Range ◽  
Sinusoidal Shape ◽  
Necessary And Sufficient

Given in this paper is a nonlinear analysis of snap-through problems of shallow arches on linear elastic foundations subjected to time-varying loads which have a time-independent character as τ → ∞. Specific problems studied in detail are simply supported sinusoidal arches under impulsive loads, under time-varying loads with asymptotic spatial distributions of sinusoidal shape, and under time-varying loads with uniform asymptotic spatial distributions. It is found that for a very wide range of the foundation modulus a necessary and sufficient condition for stability against snap-through can be established and the final state of the arch predicted. Outside this range and when the loads are timewise step loads, useful sufficient conditions for instability and sufficient conditions for stability can be found separately. The nonlinear treatment presented here is exact in the sense that no approximation is made or is required in the mathematical analysis.

scholarly journals Leveraging experience for robust, adaptive nonlinear MPC on computationally constrained systems with time-varying state uncertainty

2018 ◽  
Vol 37 (13-14) ◽  
pp. 1690-1712 ◽  
Author(s):  
Vishnu R Desaraju ◽  
Alexander E Spitzer ◽  
Cormac O’Meadhra ◽  
Lauren Lieu ◽  
Nathan Michael
Keyword(s):  
Predictive Control ◽  
Constraint Satisfaction ◽  
Constrained Systems ◽  
Time Varying ◽  
Localization System ◽  
Uncertainty Estimates ◽  
Aerial Robot ◽  
State Uncertainty ◽  
Uncertainty Set ◽  
Robust Adaptive

This paper presents a robust-adaptive nonlinear model predictive control (MPC) technique that leverages past experiences to achieve tractability on computationally constrained systems. We propose a robust extension of the Experience-driven Predictive Control (EPC) algorithm via a Gaussian belief propagation strategy that computes an uncertainty set, bounding the evolution of the system state in the presence of time-varying state uncertainty. This uncertainty set is used to tighten the constraints in the predictive control formulation via a chance-constrained approach, thereby providing a probabilistic guarantee of constraint satisfaction. The parameterized form of the controllers produced by EPC coupled with online uncertainty estimates ensures that this robust constraint satisfaction property persists, even as the system switches controllers and experiences variations in the uncertainty model. We validate the online performance and robust constraint satisfaction of the proposed Robust EPC algorithm through a series of trials with a simulated ground robot and three experimental platforms: (1) a small quadrotor aerial robot executing aggressive maneuvers in wind with degraded state estimates, (2) a skid-steer ground robot equipped with a laser-based localization system, and (3) a hexarotor aerial robot equipped with a vision-based localization system.

Time-varying Macroeconomic Risk of Real Estate Returns

2016 ◽  
Author(s):  
Felix Schindler ◽  
Bertram Steininger ◽  
Tim Kroencke
Keyword(s):  
Real Estate ◽  
Time Varying ◽  
Macroeconomic Risk ◽  
Real Estate Returns
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