The state presumption using the error presumptive observer loosen the restriction range by the sliding mode observer

2006 ◽  
Author(s):  
Ryoko Shiraki ◽  
Yasuchika Mori
Keyword(s):  
Sliding Mode ◽  
The State ◽  
Sliding Mode Observer

scholarly journals Estimating the State of Charge of Lithium-ion Battery based on Sliding Mode Observer

2016 ◽  
Vol 49 (11) ◽  
pp. 54-61 ◽  
Author(s):  
Yan Ma ◽  
Bingsi Li ◽  
Yongqiang Xie ◽  
Hong Chen
Keyword(s):  
Lithium Ion Battery ◽  
Sliding Mode ◽  
Lithium Ion ◽  
The State ◽  
Sliding Mode Observer ◽  
State Of Charge

scholarly journals Adaptive Fuzzy Fault-Tolerant Control against Time-Varying Faults via a New Sliding Mode Observer Method

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1615
Author(s):  
Yi Zhang ◽  
Yingying Nie ◽  
Liheng Chen
Keyword(s):  
State Vector ◽  
Sliding Mode ◽  
External Disturbance ◽  
The State ◽  
Sliding Mode Observer ◽  
Time Varying ◽  
Actuator Faults ◽  
Adaptive Fuzzy ◽  
Degradation Factor ◽  
Actuator Degradation

In this study, the problem of observer-based adaptive sliding mode control is discussed for nonlinear systems with sensor and actuator faults. The time-varying actuator degradation factor and external disturbance are considered in the system simultaneously. In this study, the original system is described as a new normal system by combining the state vector, sensor faults, and external disturbance into a new state vector. For the augmented system, a new sliding mode observer is designed, where a discontinuous term is introduced such that the effects of sensor and actuator faults and external disturbance will be eliminated. In addition, based on a tricky design of the observer, the time-varying actuator degradation factor term is developed in the error system. On the basis of the state estimation, an integral-type adaptive fuzzy sliding mode controller is constructed to ensure the stability of the closed-loop system. Finally, the effectiveness of the proposed control methods can be illustrated with a numerical example.

scholarly journals Adaptive Fuzzy Fault-Tolerant Control against Time-Varying Faults via a New Sliding Mode Observer Method

2021 ◽  
Author(s):  
Yi Zhang ◽  
Yingying Nie ◽  
Zhiyuan Dong ◽  
Liheng Chen
Keyword(s):  
State Vector ◽  
Sliding Mode ◽  
External Disturbance ◽  
The State ◽  
Sliding Mode Observer ◽  
Time Varying ◽  
Actuator Faults ◽  
Adaptive Fuzzy ◽  
Degradation Factor ◽  
Actuator Degradation

In this paper, the problem of observer-based adaptive sliding mode control is discussed for nonlinear systems with sensor and actuator faults. The time-varying actuator degradation factor and external disturbance are considered in the system simultaneously. In this study, the original system is described as a new normal system by combining the state vector, sensor faults and external disturbance into a new state vector. For the augmented system, a new sliding mode observer is designed, where a discontinuous term is introduced such that the effects of sensor and actuator faults and external disturbance will be eliminated. In addition, based on a tricky design of the observer, the time-varying actuator degradation factor term is developed in the error system. On the basis of the state estimation, an integral-type adaptive fuzzy sliding mode controller is constructed to ensure the stability of the closed-loop system. Finally, the effectiveness of the proposed control methods can be illustrated with a numerical example.

An efficient sliding mode observer-based model predictive control: experimental implementation on a DC/DC power converter

2018 ◽  
Vol 40 (8) ◽  
pp. 2488-2497 ◽  
Author(s):  
Bedri Bahtiyar ◽  
Meriç Çetin ◽  
Selami Beyhan ◽  
Serdar İplikçi
Keyword(s):  
Sliding Mode ◽  
Power Converter ◽  
The State ◽  
Sliding Mode Observer ◽  
Convergence Properties ◽  
Dc Power ◽  
Experimental Implementation ◽  
Model Predictive Controllers ◽  
The Stability ◽  
Predictive Controllers

In this paper, a discretization-based sliding mode observer (DBSMO) is proposed for the state and parameter estimation of nonlinear systems. In the DBSMO structure, an accurate discretized dynamics are derived for the state and parameter update of the sliding mode observer (SMO) instead of integration-based state update. In this way, faster converging observer dynamics are obtained. The stability properties of the conventional SMO remain the same for DBSMO. In the application presented here, first a real-time DC/DC power converter is designed with a computer interface. Then, to show the enhancement of convergence properties, conventional SMO and DBSMO-based model predictive controllers are designed and applied to control of the DC/DC power converter. Through simulation and experimental results, it is shown that the estimation performance of SMO is greatly improved so that the tracking performance is also increased, which are the main contributions of the paper.

State of Charge Estimation of Power Lithium-Ion Battery Based on Sliding Mode Observer

2013 ◽  
Vol 805-806 ◽  
pp. 1692-1699 ◽  
Author(s):  
Tie Zhou Wu ◽  
Ming Yue Wang ◽  
Qin Xiao
Keyword(s):  
Sliding Mode ◽  
Estimation Error ◽  
Lithium Ion ◽  
Value Theory ◽  
The State ◽  
Sliding Mode Observer ◽  
State Of Charge ◽  
Estimation Accuracy ◽  
Design Parameters ◽  
State Of Charge Estimation

The study of the application of the sliding mode observer method that estimates the state of charge. Based on the state space model of battery established on the model of improved EMF equivalent circuit, a sliding mode state observer is designed to help improve the jitter problem. Considering the nonlinear terms in the model for the analysis of the stability of the observer and the characteristics of the industry under its derivative, and using Lagrange mean value theory to guarantee the convergence conditions of the observer, the design parameters of the observer can thus be determined .Then, this thesis compares the simulation of this method under Matlab environment with the extended Kalman filter method. The results show that the method has higher estimation accuracy in the case of the same battery modeling errors. Therefore, the SOC estimation of the sliding mode observer can effectively reduce the state of charge estimation error introduced by the model error.

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