Adaptive Backstepping Hierarchical Sliding Mode Control for 3-Wheeled Mobile Robots Based on RBF Neural Networks

This paper proposes a new adaptive controller for three-wheeled mobile robots (3WMRs) called the ABHSMC controller. is developed through cooperative approach, combining backstepping and Radial Basis Function (RBF) neural network-based Hierarchical Sliding Mode Controller (HSMC). Notably, RBF network exhibits remarkable capability to estimate both uncertainty components of model systematically adapt its parameters, leading enhanced output trajectory responses. A novel navigational model, constructed by connection BHSMC controller, Timed Elastic Band (TEB) Local Planner, A-star (A*) Global navigation stack, it applied effectively solve tracking issue obstacle avoidance 3-Wheeled Mobile Robot (3WMR). The simulation results implemented in Matlab/Simulink platform demonstrate that 3WMRs can precisely follow desired trajectory, even presence disturbances changes parameters. Furthermore, controller’s reliability endorsed on our self-driving car model. achieved experimental indicate proposed structure control actual vehicle track with small enough error avoid sudden simultaneously.