Title :
Discrete-time backstepping control of a light weighted all-electric vehicle
Author :
Sharma, Vishal ; Purwar, Shubhi
Author_Institution :
Dept. of Electr. Eng., Motilal Nehru Nat. Inst. of Technol., Allahabad, India
Abstract :
In this paper, discrete-time backstepping control is proposed for a light weighted all-electric vehicle. The electric vehicle (EV) is driven by DC motor. Firstly, state feedback control is presented via backstepping, applied to a strict feedback form of the EV system. Here Chebyshev Neural Network (CNN) is used to solve the causality contradiction problem in the strict feedback discrete-time EV system. The CNN based control algorithm for the EV system is developed and a new European driving cycle test is performed to test the control performance. Through simulation results the effectiveness of the proposed control schemes are shown.
Keywords :
discrete time systems; electric vehicles; neurocontrollers; state feedback; CNN based control algorithm; Chebyshev neural network; DC motor; European driving cycle test; causality contradiction problem; discrete time backstepping control; light weighted all electric vehicle; state feedback control; strict feedback discrete time EV system; Aerodynamics; Backstepping; Chebyshev approximation; DC motors; Neural networks; Vehicle dynamics; backstepping control; chebyshev neural network; dc. motor; discrete-time ev system; new European driving cycle;
Conference_Titel :
India Conference (INDICON), 2013 Annual IEEE
Conference_Location :
Mumbai
Print_ISBN :
978-1-4799-2274-1
DOI :
10.1109/INDCON.2013.6725985
