A Robust Intelligent Controller for Autonomous Ground Vehicle Longitudinal Dynamics
Lhoussain El Hajjamia, El Mehdi Melloulib, Vidas Žuraulisc✉, Mohammed Berradaa, Ismail Boumhidid
- aLaboratory of Artificial Intelligence, Data Sciences and Emerging Systems, School of Applied Sciences, Sidi Mohamed Ben Abdellah University, BP 72, My Abdallah Avenue Km. 5 Imouzzer Road, Fez 30000, Morocco
- bLaboratory of Engineering, Systems, and Applications, School of Applied Sciences, Sidi Mohamed Ben Abdellah University, BP 72, My Abdallah Avenue Km. 5 Imouzzer Road, Fez 30000, Morocco
- cDepartment of Automobile Engineering, Vilnius Gediminas Technical University, J. Basanavičiaus St. 28, 03224 Vilnius, Lithuania
- dLISAC Laboratory, Faculty of Science Dhar El Mahrez, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco
- ✉Corresponding author
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Abstract
In this paper, a novel adaptive sliding mode controller (SMC) was designed based on a robust law considering disturbances and uncertainties for autonomous ground vehicle (AGV) longitudinal dynamics. The robust law was utilized in an innovative method involving the upper bounds of disturbances and uncertainties. Estimating this lumped uncertainty upper limit based on a neural network approach allowed its online knowledge. It guided the controller to withstand the disturbance and to compensate for the uncertainties. A stability analysis, according to Lyapunov, was completed to confirm the asymptotic convergence of the states to the desired state. The effectiveness and benefits of the planned approach were scrutinized by simulations and comparative studies.