Model-free adaptive sliding mode control for intelligent vehicle longitudinal dynamics

Vehicle longitudinal dynamics system has the characteristics of being strongly non-linear, time-varying, and multiple-perturbed, so, it is difficult to build the mathematical model accurately. The control algorithms, based on accurate mathematical model, can hardly achieve the ideal effect, but cont...

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Bibliographic Details
Published in:Advances in mechanical engineering 2022-07, Vol.14 (7)
Main Authors: Zhang-qi, Feng, Hao-bin, Jiang, Qi-zhi, Wei, Yang-ke, Hong, Abiodun Oluwaleke, Ojo
Format: Article
Language:English
Subjects:
Adaptive control
Control methods
Feedforward control
Genetic algorithms
Intelligent vehicles
Robustness (mathematics)
Sliding mode control
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Summary:Vehicle longitudinal dynamics system has the characteristics of being strongly non-linear, time-varying, and multiple-perturbed, so, it is difficult to build the mathematical model accurately. The control algorithms, based on accurate mathematical model, can hardly achieve the ideal effect, but control methods, which merely adopt input/output data (I/O) of a system, provides a solution. In this paper, by means of combing model-free adaptive control (MFAC) and sliding-mode control (SMC), the model-free adaptive sliding mode control (MFASMC) method is proposed. By comparison with feedback-feedforward control method, the MFASMC method can better improve the control effect and anti-disturbance performance. Meanwhile, the stability of MFASMC method was proven mathematically. Besides, the parameters of MFASMC method were optimized using genetic algorithm. Results of simulation and HiL test shows that the MFASMC method has fast response, strong robustness and smooth output. It would be better to apply it to the longitudinal dynamics control of intelligent vehicles.
ISSN:1687-8132
1687-8140
DOI:10.1177/16878132221110131