DocumentCode
226459
Title
Model-based Takagi-Sugeno fuzzy approach for vehicle longitudinal velocity estimation during braking
Author
Haiping Du ; Weihua Li
Author_Institution
Sch. of Electr., Comput. & Telecommun. Eng., Univ. of Wollongong, Wollongong, NSW, Australia
fYear
2014
fDate
6-11 July 2014
Firstpage
1851
Lastpage
1858
Abstract
Accurate vehicle longitudinal velocity estimation is important for wheel slip ratio control in antilock braking systems. To overcome the problem of nonlinear tyre-road friction characteristic when designing an observer for velocity estimation, this paper presents a novel approach by using the model-based fuzzy technique. The nonlinear vehicle braking system is modelled by a Takagi-Sugeno fuzzy model first. A fuzzy observer is then constructed by using the available measurements of wheel angular velocity and braking torque with the estimated premise variables. All the possible disturbances and uncertainties are considered so that the designed observer is robust under an Hoo performance index from the disturbances to the estimation error. The design of the observer is achieved by solving a set of linear matrix inequalities. Numerical simulations on a quarter-vehicle braking model are used to validate the effectiveness of the proposed approach.
Keywords
H∞ control; braking; fuzzy control; linear matrix inequalities; nonlinear control systems; observers; performance index; road vehicles; torque measurement; velocity measurement; H∞ performance index; antilock braking systems; braking torque; estimation error; fuzzy observer; linear matrix inequalities; model-based Takagi-Sugeno fuzzy approach; nonlinear tyre-road friction characteristic; numerical simulations; quarter-vehicle braking model; vehicle longitudinal velocity estimation; wheel angular velocity; wheel slip ratio control; Friction; Mathematical model; Observers; Roads; Torque; Vehicles; Wheels; T-S fuzzy model; antilock braking; longitudinal dynamics; velocity estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-2073-0
Type
conf
DOI
10.1109/FUZZ-IEEE.2014.6891553
Filename
6891553
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