Pseudo-state system modelling and a discrete-time separation principle for LQG control

1999 ◽  
Keyword(s):  
Discrete Time ◽  
State System ◽  
System Modelling ◽  
Separation Principle ◽  
Time Separation ◽  
Lqg Control

Robustness of adaptive discrete-time LQG control for first-order systems

2010 ◽  
Vol 58 (1) ◽  
pp. 89-97
Author(s):  
A. Królikowski ◽  
D. Horla
Keyword(s):  
Control System ◽  
Discrete Time ◽  
Point Of View ◽  
Constrained Control ◽  
Certainty Equivalence ◽  
First Order ◽  
Lqg Control ◽  
Self Tuning ◽  
And Performance ◽  
Performance Robustness

Robustness of adaptive discrete-time LQG control for first-order systemsThe discrete-time adaptive LQG control of first-order systems is considered from robustness point of view. Both stability and performance robustness are analyzed for different control system structures. A case of amplitude-constrained control is presented, and application of certainty equivalence for self-tuning implementation is also discussed.

Quantized state simulation of spiking neural networks

SIMULATION ◽  
2011 ◽  
Vol 88 (3) ◽  
pp. 299-313 ◽  
Author(s):  
Guillermo L Grinblat ◽  
Hernán Ahumada ◽  
Ernesto Kofman
Keyword(s):  
Neural Networks ◽  
Discrete Time ◽  
Discrete Event ◽  
State System ◽  
Spiking Neurons ◽  
Spiking Neural Networks ◽  
Computational Costs ◽  
Simulation Results ◽  
Neuroscience Community

In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity.

LQG control on mixed H2/H∞ problem: the discrete-time case

2019 ◽  
Vol 51 (1) ◽  
pp. 191-201
Author(s):  
Xiaoqian Li ◽  
Wei Wang ◽  
Juanjuan Xu ◽  
Huanshui Zhang
Keyword(s):  
Discrete Time ◽  
Lqg Control ◽  
Discrete Time Case

On steady-state queue size distributions of the discrete-time GI/G/1 queue

1996 ◽  
Vol 28 (04) ◽  
pp. 1177-1200 ◽  
Author(s):  
Tao Yang ◽  
M. L. Chaudhry
Keyword(s):  
Steady State ◽  
Discrete Time ◽  
Linear Transformation ◽  
State System ◽  
Interarrival Time ◽  
Steady State Distribution ◽  
State Distribution ◽  
The Matrix ◽  
Matrix Geometric Solution ◽  
System Length

In this paper, we present results for the steady-state system length distributions of the discrete-timeGI/G/1 queue. We examine the system at customer arrival epochs (customer departure epochs) and use the residual service time (residual interarrival time) as the supplementary variable. The embedded Markov chain is ofGI/M/1 type if the embedding points are arrival epochs and is ofM/G/1 type if the embedding points are departure epochs. Using the matrix analytic method, we identify the necessary and sufficient condition for both Markov chains to be positive recurrent. For theGI/M/1 type chain, we derive a matrix-geometric solution for its steady-state distribution and for theM/G/1 type chain, we develop a simple linear transformation that relates it to theGI/M/1 type chain and leads to a simple analytic solution for its steady-state distribution. We also show that the steady-state system length distribution at an arbitrary point in time can be obtained by a simple linear transformation of the matrix-geometric solution for theGI/M/1 type chain. A number of applications of the model to communication systems and numerical examples are also discussed.

Nonlinear Compensation and Stochastic Control

1988 ◽  
Vol 110 (4) ◽  
pp. 430-433 ◽  
Author(s):  
M. J. Grimble
Keyword(s):  
Asymptotic Stability ◽  
Stochastic Control ◽  
Discrete Time ◽  
Nonlinear Characteristic ◽  
Compensation Scheme ◽  
Discrete Time System ◽  
Time System ◽  
Control Approach ◽  
Lqg Control ◽  
Nonlinear Compensation

The usual ARMAX linear model for a discrete-time system is generalized to include a nonlinear characteristic. A nonlinear compensation scheme is proposed which enables a modified LQG control approach to be applied to the precompensated system. The solution is relatively simple and if the plant matches the modelled situation asymptotic stability is guaranteed.

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