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.

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 Fuzzy state space model for a pressurizer in a nuclear power plant

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
A. Ashaari ◽  
T. Ahmad ◽  
Mustaffa Shamsuddin ◽  
S. Zenian
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
State Space ◽  
Nuclear Power ◽  
State Space Model ◽  
Published Data ◽  
State Space Approach ◽  
Space Model ◽  
Fuzzy State ◽  
Space Approach

In this paper, Fuzzy State Space Model (FSSM) for a nuclear power plant is proposed. Pressurizer is used to control pressure and temperature in a nuclear power plant. In order to maintain the pressure and the temperature of the system, the effectiveness of the system needs to be monitored frequently. Hence, fuzzy state space approach is used to model the pressurizer. The influence of input to output of the pressurizer is established and presented in this paper. The result from the model is then verified against published data.

Hybrid State Space Modeling of a Spark Ignition Engine for Online Fault Diagnosis

2017 ◽  
Vol 140 (4) ◽  
Author(s):  
E. P. Nadeer ◽  
Amit Patra ◽  
Siddhartha Mukhopadhyay
Keyword(s):  
State Space ◽  
Gasoline Engine ◽  
State Space Model ◽  
Control Unit ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Intake Manifold ◽  
Hybrid State ◽  
Space Modeling ◽  
State Space Modeling

In this work, a nonlinear hybrid state space model of a complete spark ignition (SI) gasoline engine system from throttle to muffler is developed using the mass and energy balance equations. It provides within-cycle dynamics of all the engine variables such as temperature, pressure, and mass of individual gas species in the intake manifold (IM), cylinder, and exhaust manifold (EM). The inputs to the model are the same as that commonly exercised by the engine control unit (ECU), and its outputs correspond to available engine sensors. It uses generally known engine parameters, does not require extensive engine maps found in mean value models (MVMs), and requires minimal experimentation for tuning. It is demonstrated that the model is able to capture a variety of engine faults by suitable parameterization. The state space modeling is parsimonious in having the minimum number of integrators in the model by appropriate choice of state. It leads to great computational efficiency due to the possibility of deriving the Jacobian expressions analytically in applications such as on-board state estimation. The model was validated both with data from an industry standard engine simulation and those from an actual engine after relevant modifications. For the test engine, the engine speed and crank angle were extracted from the crank position sensor signal. The model was seen to match the true values of engine variables both in simulation and experiments.

scholarly journals Fuzzy State Space Model of Multivariable Control Systems

2009 ◽  
Vol 2 (2) ◽  
Author(s):  
R. Ismail ◽  
K. Jusoff ◽  
T. Ahmad ◽  
S. Ahmad ◽  
R.S. Ahmad
Keyword(s):  
State Space ◽  
Control Systems ◽  
State Space Model ◽  
Multivariable Control ◽  
Space Model ◽  
Multivariable Control Systems ◽  
Fuzzy State
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