Sliding Mode Observer and Event Triggering Mechanism Co-design

Sliding mode observer and event triggering mechanism co-design is the subject of this paper. The synthesis of a sliding mode observer under any event triggering mechanism is given, where the proposed observer can be viewed as a special structure of the Kalman filter. Then, the event triggering condition is updated according to the coverage index value computed with the help of the reachability set representation. A numerical example illustrates the effectiveness of the proposed approach.

Download Full-text

Discrete-time high-order neural network identifier trained with high-order sliding mode observer and unscented Kalman filter

Neurocomputing ◽

10.1016/j.neucom.2019.12.005 ◽

2019 ◽

Cited By ~ 1

Author(s):

M. Hernandez-Gonzalez ◽

M.V. Basin ◽

E.A. Hernandez-Vargas

Keyword(s):

Neural Network ◽

Kalman Filter ◽

Discrete Time ◽

Unscented Kalman Filter ◽

Sliding Mode ◽

High Order ◽

Sliding Mode Observer ◽

High Order Neural Network

Download Full-text

Research on Sensorless Control Method of PMSM Based on a Kalman Filter Sliding Mode Observer

2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) ◽

10.1109/icmtma.2018.00077 ◽

2018 ◽

Cited By ~ 1

Author(s):

Haiyang Tang ◽

Haixia Li ◽

Jican Lin

Keyword(s):

Kalman Filter ◽

Control Method ◽

Sliding Mode ◽

Sensorless Control ◽

Sliding Mode Observer

Download Full-text

Experimental evaluation of a sliding mode observer for tire-road forces and an extended Kalman filter for vehicle sideslip angle

2007 46th IEEE Conference on Decision and Control ◽

10.1109/cdc.2007.4434162 ◽

2007 ◽

Cited By ~ 12

Author(s):

Guillaume Baffet ◽

Ali Charara ◽

Daniel Lechner

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Experimental Evaluation ◽

Sliding Mode ◽

Sliding Mode Observer ◽

Sideslip Angle

Download Full-text

Heavy vehicle state estimation and rollover risk evaluation using Kalman Filter and Sliding Mode Observer

2007 European Control Conference (ECC) ◽

10.23919/ecc.2007.7068741 ◽

2007 ◽

Cited By ~ 3

Author(s):

J. Dakhlallah ◽

H. Imine ◽

Y. Sellami ◽

D. Bellot

Keyword(s):

Kalman Filter ◽

State Estimation ◽

Risk Evaluation ◽

Sliding Mode ◽

Sliding Mode Observer ◽

Heavy Vehicle ◽

Rollover Risk ◽

Vehicle State Estimation

Download Full-text

A new sensorless vector control method for PMSM based on adaptive fuzzy sliding mode observer and Kalman filter

Emerging Developments in the Power and Energy Industry ◽

10.1201/9780429295300-4 ◽

2019 ◽

pp. 31-38

Author(s):

Siqi Peng ◽

Dongxiang Li

Keyword(s):

Kalman Filter ◽

Vector Control ◽

Control Method ◽

Sliding Mode ◽

Sliding Mode Observer ◽

Adaptive Fuzzy ◽

Sensorless Vector Control ◽

Adaptive Fuzzy Sliding Mode ◽

Fuzzy Sliding Mode

Download Full-text

Sensorless control of Switched Reluctance Motor with unknown load torque for EV application using Extended Kalman Filter and second order sliding mode observer

2018 IEEE International Conference on Industrial Technology (ICIT) ◽

10.1109/icit.2018.8352231 ◽

2018 ◽

Cited By ~ 1

Author(s):

Yakoub Saadi ◽

Rabia Sehab ◽

Ahmed Chaibet ◽

Mousaa Boukhnifer ◽

Demba Diallo

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Sliding Mode ◽

Switched Reluctance Motor ◽

Sliding Mode Observer ◽

Load Torque ◽

Switched Reluctance ◽

Reluctance Motor ◽

Unknown Load ◽

Second Order Sliding Mode

Download Full-text

A robust sensorless SMC of PMSM based on sliding mode observer and extended Kalman filter

2015 4th International Conference on Electrical Engineering (ICEE) ◽

10.1109/intee.2015.7416838 ◽

2015 ◽

Cited By ~ 5

Author(s):

L. Saihi ◽

A. Bouhenna ◽

M. Chenafa ◽

A. Mansouri

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Sliding Mode ◽

Sliding Mode Observer

Download Full-text

Kalman filter and sliding mode observer in artificial pancreas: an in-silico comparison

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.617 ◽

2020 ◽

Vol 53 (2) ◽

pp. 16227-16232

Author(s):

I. Sala-Mira ◽

M. Siket ◽

Gy. Eigner ◽

J. Bondia ◽

L. Kovacs

Keyword(s):

Kalman Filter ◽

In Silico ◽

Sliding Mode ◽

Artificial Pancreas ◽

Sliding Mode Observer

Download Full-text

A Comparison State of Charge Estimation Between Kalman Filter and Sliding Mode Observer for Lithium Battery

Advances in Green Energies and Materials Technology - Springer Proceedings in Energy ◽

10.1007/978-981-16-0378-5_15 ◽

2021 ◽

pp. 107-114

Author(s):

Maamar Souaihia ◽

Bachir Belmadani ◽

Fayçal Chabni ◽

Abdelatif Gadoum

Keyword(s):

Kalman Filter ◽

Lithium Battery ◽

Sliding Mode ◽

Sliding Mode Observer ◽

State Of Charge ◽

State Of Charge Estimation

Download Full-text

Comparative Study of a Super-Twisting Sliding Mode Observer and an Extended Kalman Filter for a Freeway Traffic System

Cybernetics and Information Technologies ◽

10.1515/cait-2015-0034 ◽

2015 ◽

Vol 15 (2) ◽

pp. 141-158 ◽

Cited By ~ 2

Author(s):

H. Majid ◽

H. Abouaïssa

Keyword(s):

Kalman Filter ◽

Comparative Study ◽

Extended Kalman Filter ◽

Sliding Mode ◽

Dynamic Performance ◽

Sliding Mode Observer ◽

State Variables ◽

Highway Traffic ◽

Traffic State ◽

Geometric Conditions

Abstract Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the estimation of traffic state variables (density and speed), using the so called Super- Twisting Sliding Mode Observer (STSM). Several numerical simulations, using simulated and real data, show the relevance of the proposed approach. In addition, a comparative study with the Extended Kalman Filter (EKF) is carried-out. The comparison indices concern convergence and stability, dynamic performance and robustness. The design of the two observers is achieved using a nonlinear second order traffic flow model in the same highway traffic and geometric conditions.

Download Full-text