A Novel Terramechanics-Based Path-Tracking Control of Terrain-Based Wheeled Robot Vehicle With Matched-Mismatched Uncertainties

Path-tracking control of a wheeled robot is a complex dynamical problem due to the system nonlinearities, external disturbances, and modeled and unstructured uncertainties. The problem is profoundly exacerbated for the robot traversing deformable terrains. This paper mainly addresses this problem by the following contributions: i) path-tracking control of terrain-based robots considering deformable soil dynamics for deriving tractive forces and moments arising from wheel-terrain interactions; ii) a novel modified moving integral sliding surface, where the dynamics of the sliding surface is regulated by an adaptive inverse neural network; and iii) path-tracking controller synthesis considering the terrain-induced uncertainties. For this purpose, a novel adaptive indirect controller is proposed to address the path-tracking control of a wheeled robot in the presence of external disturbances and wheel slippage using an integrated modified Integral Sliding-Mode Control (ISMC) and adaptive neural networks (NNs). A compensating controller term is introduced to minimize abrupt variations in control demand that may arise from uncertainties related to terrain properties and the resulting wheel slippage and motion resistance. The adaptive rules are formulated considering the ISMC based control dynamics, while the stability of the closed-loop system is ensured via Lyapunov stability theorem. The effectiveness of the proposed controller is demonstrated considering a typical sandy loam soil for linear and curved trajectories. It is inferred that the proposed adaptive indirect ISMC-NN robust controller has the capacity to reach a satisfactory path-tracking control performance in the presence of disturbance and uncertainties arising from robots interactions with the deformable terrain.