Fuzzy Edge Connectivity of Graphical Fuzzy State Space Model in Multi‐connected System

2010 ◽  
Author(s):  
Noor Ainy Harish ◽  
Razidah Ismail ◽  
Tahir Ahmad
Keyword(s):  
State Space ◽  
State Space Model ◽  
Edge Connectivity ◽  
Space Model ◽  
Fuzzy State

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.

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

DECENTRALIZED STABILIZATION OF COMPLEX SYSTEMS BY COMBINATION OF CONVENTIONAL AND FUZZY CONTROLS

1999 ◽  
Vol 07 (04) ◽  
pp. 423-427
Author(s):  
QUANG VINH THAI ◽  
MANH DAO HA ◽  
SI BANG HO
Keyword(s):  
Complex System ◽  
Robust Control ◽  
State Space ◽  
Control Method ◽  
State Space Model ◽  
Linear Interaction ◽  
Decentralized Stabilization ◽  
Space Model ◽  
Decentralized Robust Control ◽  
Fuzzy State

In this paper, we deal with the problem of how to achieve stability for a complex system in which the subsystems are stable, but the non-linear interaction between the subsystems may cause instability. We assume that the uncertainties with which we know the parameters of the system are bounded, but that these bounds are not known. For such systems, we propose a new control method: a decentralized robust control with fuzzy estimation of the bounds of uncertainties, implemented as a combination of conventional and fuzzy controllers. The use of fuzzy control is motivated by the equivalent dynamic fuzzy state-space model of the system consisting of interconnected uncertain subsystems.

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.

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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