A linear parameter-varying flux observer: design and experimentation

Author(s):  
C. Darengosse ◽  
P. Chevrel ◽  
R. Le Doeuff
Author(s):  
Denis Efimov ◽  
Tarek Raïssi ◽  
Ali Zolghadri

This paper deals with the problem of joint state and parameter estimation based on a set adaptive observer design. The problem is formulated and solved for an LPV (linear parameter-varying) system. The resolution methodology avoids the exponential complexity obstruction usually encountered in the set-membership parameter estimation. A simulation example is presented to illustrate the efficiency of the proposed approach.


2021 ◽  
Author(s):  
F. Benmessaoud ◽  
M. Bensmaine ◽  
D. Khamari ◽  
I. Benlaloui ◽  
Boutabba ◽  
...  

Author(s):  
Yan Chen ◽  
Junmin Wang

A new estimation method for estimating the vehicle sideslip angle, mainly based on a linear parameter varying (LPV) model with independently estimated tire friction forces, is proposed for electric ground vehicles (EGVs) with four independent in-wheel motors. By utilizing the individual wheel dynamics, the longitudinal ground friction force is estimated from a PID observer based on a descriptor linear system approach. Moreover, the lateral ground friction force for each wheel is estimated through the friction ellipse relationship given the estimated longitudinal friction force, without relying on explicit tire models. Since the estimation errors of friction forces may bring parameter uncertainty for the LPV system, robust analysis with desired H-infinity performance is given for the observer design of the LPV modeling. This method is specially proposed for large tire slip angles and lateral friction forces. Simulation results for different maneuvers validate this novel sideslip angle estimation method.


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