Regenerative-braking sliding mode control of electric vehicle based on neural network identification

IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Volumn , Issue , 2008, Pages 1219-1224

  Cao, Jianbo ^a   Cao, Binggang ^a   Xu, Peng ^a   Bai, Zhifeng ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Electric vehicle; Neural network; Regenerative braking; Sliding mode control

Indexed keywords

ARTIFICIAL INTELLIGENCE; ASYMPTOTIC ANALYSIS; AUTOMOBILES; BRAKING; CODES (SYMBOLS); ELECTRIC AUTOMOBILES; ELECTRIC VEHICLES; ELECTRONICS INDUSTRY; ENERGY CONSERVATION; FEEDFORWARD NEURAL NETWORKS; IMAGE CLASSIFICATION; MATHEMATICAL MODELS; MECHATRONICS; NEURAL NETWORKS; PARAMETER ESTIMATION; RADIAL BASIS FUNCTION NETWORKS; SLIDING MODE CONTROL; SYSTEM STABILITY; VEHICLES;

BACK PROPAGATION; BRAKING CONTROLLER; DRIVING RANGE; ELECTRIC VEHICLE; INTELLIGENT MECHATRONICS; INTERNATIONAL CONFERENCES; MAIN CIRCUIT; MODEL PARAMETERS; NEURAL NETWORK; NEURAL NETWORK (NN); PARAMETER PREDICTION; RADIAL BASIS FUNCTION NN; REGENERATIVE BRAKING; RESPONSE SPEED; SAVING ENERGY; SLIDING-MODE CONTROLLERS; STEADY-STATE TRACKING; SWITCHING GAIN; SYSTEM IDENTIFICATION;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 52449126346     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AIM.2008.4601836     Document Type: Conference Paper

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