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
Link To Document :
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