Abstract
As key equipment in logistics system of modern manufacturing factories, the automated guided vehicle (AGV) plays an increasingly important role. Although many strategies for AGV motion control are available, in most cases, only a single control method is utilized during the entire process, which inevitably leads to the lack of flexibility in dealing with problems encountered in various stages of the AGV motion. In this paper, a new approach called sectionalized motion control (SMC) was proposed in order to achieve superb comprehensive performance (i.e., high precision, low energy consumption, and good stability) for the entire AGV tracking process. In this method, considering AGV’s various characteristics in different motion stages (early, middle, and terminal), the neural dynamics-based tracking, energy-efficient tracking, and model predictive control technologies were adopted. Furthermore, a simulation using Matlab software was performed in order to verify the proposed approach. The simulated results showed that the SMC is capable of providing smooth, energy-efficient, robust, and globally stable control for the AGV system.
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