Order Determination and Parameter Identification of Time-Invariant State Variable Models

1972 ◽  
Vol 5 (1) ◽  
pp. 278-285 ◽  
Author(s):  
M. Djorović ◽  
S.P. Bingulac
Keyword(s):  
Parameter Identification ◽  
Invariant State ◽  
State Variable ◽  
Time Invariant ◽  
Order Determination

Modelin and analysis of nonideal polyphase diode converters

SIMULATION ◽  
1971 ◽  
Vol 17 (6) ◽  
pp. 237-243 ◽  
Author(s):  
Michael J. Smith
Keyword(s):  
Mathematical Model ◽  
Digital Computer ◽  
Linear Time ◽  
Piecewise Linear ◽  
Invariant State ◽  
Computer Solution ◽  
Linear Time Invariant ◽  
State Variable ◽  
Time Invariant ◽  
The Mathematical Model

The mathematical model of the diode proposed in this investigation for the analysis of nonideal poly phase converters has finite forward and reverse resistances. Since current-dependent diode impedances exist at all times, only one set of piecewise-linear time-invariant state-variable equations is required to describe the nonideal polyphase diode converter completely. A digital computer solution of the state- variable equations was obtained to verify the inte grity and tractability of this method of analysis.

Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg
Keyword(s):  
Activated Sludge ◽  
Nitrate Concentration ◽  
State Space Model ◽  
Activated Sludge Process ◽  
Invariant State ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Space Model ◽  
And Control ◽  
Time Invariant

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

On krylov matrices and controllability of n-dimensional linear time-invariant state equations

1996 ◽  
Vol 3 (1-2) ◽  
pp. 99-109
Author(s):  
Andrzej Maćkiewicz ◽  
Francisco López Almansa ◽  
José A. Inaudi
Keyword(s):  
Linear Time ◽  
Invariant State ◽  
State Equations ◽  
Linear Time Invariant ◽  
Time Invariant

Application of Supervisory Predictive Control Based on T-S Model in pH Neutralization Process

2014 ◽  
Vol 511-512 ◽  
pp. 867-870
Author(s):  
Su Zhen Li ◽  
Xiang Jie Liu ◽  
Gang Yuan
Keyword(s):  
Predictive Control ◽  
Linear Time ◽  
Control Performance ◽  
Invariant State ◽  
Linear Time Invariant ◽  
Neutralization Process ◽  
S Model ◽  
Time Invariant ◽  
Ph Neutralization ◽  
Ph Neutralization Process

T-S model is linearized at sampling points into the form of linear time-invariant state space , and using supervisory predictive control and muti-step predictive control strategy, which reduces amount of calculation and improves the control performance. Introduction

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