Bio-inspired neurodynamics-based cascade tracking control for automated guided vehicles

Nowadays, the automated guided vehicles (AGV) have been widely used with increasing missions in a variety of fields such as the industry, military, and research. Due to the nonholonomic constraints, fulfilling satisfactory control of the AGV becomes a big challenge. In the present work, a bio-inspired neurodynamics-based cascade tracking control strategy was proposed. Specifically, the bio-inspired neurodynamics module was utilized to generate smooth forward velocities for overcoming the sharp velocity jump. Moreover, with the cascade tracking approach, the nonholonomic system was transformed into a chained system. Additionally, a state differential feedback controller was applied to improve the tracking accuracy. Finally, simulation investigations based on Matlab codes with various parameter settings were carried out to verify the effectiveness of the proposed strategy. The simulation results showed that the proposed strategy in the present work is able to produce accurate, smooth, robust, and globally stable control for the AGV.