scholarly journals Novel Method for State Space Modeling of Full Bridge Converter

2019 ◽  
Vol 8 (12) ◽  
pp. 4421-4426
Keyword(s):  
State Space ◽  
Power Conversion ◽  
State Space Model ◽  
Space Model ◽  
Space Modeling ◽  
Novel Method ◽  
Converter Design ◽  
Efficient Power ◽  
Wire Resistance ◽  
The Ideal

The requirement of converters is increasing with the increase in demand for the power conversion devices. For efficient power conversion, stability and time response of the system must be improved. For improving characteristics a mathematical model of the system must be determined. In this paper, an improvised state space model of full bridge converter is presented which can be used in converter design. This state-space model incorporates the non-idealities of the transformers like discharge time of primary inductance and secondary inductance as well as the wire resistance. The interdependency of the parameters affects the state space model of the converter compared to the ideal modeling. This variation in state space model of the converter has an impact on design of compensator which improves the system efficiency of the converter.

scholarly journals State Space Modeling with Non-Negativity Constraints Using Quadratic Forms

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1908
Author(s):  
Ourania Theodosiadou ◽  
George Tsaklidis
Keyword(s):  
State Space ◽  
Quadratic Forms ◽  
Hidden Variables ◽  
State Space Model ◽  
Estimation Procedure ◽  
Positive Component ◽  
Filtering Algorithm ◽  
Space Model ◽  
Space Modeling ◽  
The Difference

State space model representation is widely used for the estimation of nonobservable (hidden) random variables when noisy observations of the associated stochastic process are available. In case the state vector is subject to constraints, the standard Kalman filtering algorithm can no longer be used in the estimation procedure, since it assumes the linearity of the model. This kind of issue is considered in what follows for the case of hidden variables that have to be non-negative. This restriction, which is common in many real applications, can be faced by describing the dynamic system of the hidden variables through non-negative definite quadratic forms. Such a model could describe any process where a positive component represents “gain”, while the negative one represents “loss”; the observation is derived from the difference between the two components, which stands for the “surplus”. Here, a thorough analysis of the conditions that have to be satisfied regarding the existence of non-negative estimations of the hidden variables is presented via the use of the Karush–Kuhn–Tucker conditions.

scholarly journals Representation of multi-connected system of Fuzzy State Space Modeling (FSSM) in potential method based on a network context

2017 ◽  
Vol 13 (4) ◽  
pp. 711-716 ◽  
Author(s):  
Jibril Aminu ◽  
Tahir Ahmad ◽  
Surajo Sulaiman
Keyword(s):  
State Space ◽  
State Space Model ◽  
Type A ◽  
Potential Method ◽  
Network System ◽  
Space Model ◽  
Space Modeling ◽  
State Space Modeling ◽  
Fuzzy State

The complexity of a system of Fuzzy State Space Modeling (FSSM) is the reason that leads to the main objective of this research. A multi-connected system of Fuzzy State Space Model is made up of several components, each of which performs a function. These components are interconnected in some manner and determine how the overall system operates. In this study, we study the concept of graph, network system and network projections which are the requisite knowledge to potential method. Finally, the multi-connected system of FSSM of type A namely feeder, common feeder and greatest common feeder are transformed into potential method using various method of transformation.

State Space Modeling of an Acoustic Duct With an End-Mounted Speaker

1998 ◽  
Vol 120 (3) ◽  
pp. 770-775 ◽  
Author(s):  
R. Venugopal ◽  
D. S. Bernstein
Keyword(s):  
Boundary Conditions ◽  
State Space ◽  
State Space Model ◽  
Positive Real ◽  
Feedback Analysis ◽  
Space Model ◽  
Space Modeling ◽  
Loop Feedback ◽  
Closed Loop Feedback ◽  
And Shifts

This paper develops a state space model of the dynamics of an acoustic duct with end-mounted speakers. The initial model formulation includes the forcing term as part of the boundary conditions. The shifted particle velocity is then defined to transform the nonhomogeneous boundary conditions into homogeneous boundary conditions and thus develop the state space model. It is shown that the speaker and acoustic dynamics interact by means of feedback in which the speaker creates an acoustic field, which, in turn, affects the motion of the speaker cone. This interaction is studied using positive real closed-loop feedback analysis, and shifts in the modal frequencies of the duct due to the presence of the end-mounted speaker are predicted.

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

2021 ◽  
pp. 095965182199617
Author(s):  
Mahyar Akbari ◽  
Abdol Majid Khoshnood ◽  
Saied Irani
Keyword(s):  
Fault Detection ◽  
State Space ◽  
Gas Turbine ◽  
Sliding Mode ◽  
State Space Model ◽  
Sensor Fault ◽  
Space Model ◽  
Decision Logic ◽  
Sensor Fault Detection ◽  
Industrial Gas Turbine

In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

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