摘要

The use of pneumatic devices is widespread among different industrial fields, in tasks like handling or assembly. Pneumatic systems are low-cost, reliable, and compact solutions. However, its use is typically restricted to simple tasks due to the poor performance achieved in applications where accurate motion control is required. This paper presents a novel nonlinear controller, using neural network-based models, that allows the use of common industrial servopneumatic components in applications where fine trajectory following tasks is required. Furthermore, several experimental trials show that the system is highly robust to payload variation without any controller retuning. These results encourage the use of pneumatics actuators in a set of applications for which they have not been traditionally considered.

  • 出版日期2012-7