Global Fuzzy Adaptive Hierarchical Path Tracking Control of a Mobile Robot With Experimental Validation

Abstract

Due to the nature of the complete model with motor dynamics, virtual control input (i.e., desired motor current) is designed by the first sliding surface so that the indirect output (i.e., 3-D pose of mobile robot) is controlled by the direct output (i.e., motor current). Subsequently, the linear dynamic tracking error of the virtual control input is employed to establish the second sliding surface. Then, the hierarchical path tracking control (HPTC) is constructed so that the direct output asymptotically and robustly tracks the virtual control input. In the meanwhile, the asymptotic tracking of the indirect output is achieved. To improve only asymptotical tracking to convex set due to the existence of huge uncertainties (e.g., different ground conditions, time-varying system parameters, external disturbances), two online fuzzy models of uncertainties are plunged into the HPTC with a switching mechanism to design the so-called global fuzzy adaptive HPTC for a mobile robot. Moreover, the global adaptive path tracking control for different initial system states outside of approximated set is achieved. The simulations confirm the effectiveness, efficiency, and practicality of the proposed technique. Two compared experiments also validate the consistence with the simulation result.