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. One of the key elements required to achieve a good control performance is the model of the servopneumatic system. An accurate model may be of vital importance not only in the simulation steps needed to test the control strategy but also as a part of the controller itself. This work presents a new servopneumatic system model primarily developed for control tasks, namely, to predict pneumatic and friction forces in dynamic tests. The model can also be used in simulation tasks to predict the piston position and velocity. The performance on both applications is validated experimentally.
A Neural Network Based Nonlinear Model of a Servopneumatic System
Falcão Carneiro, J., and Gomes de Almeida, F. (December 30, 2011). "A Neural Network Based Nonlinear Model of a Servopneumatic System." ASME. J. Dyn. Sys., Meas., Control. March 2012; 134(2): 024502. https://doi.org/10.1115/1.4005360
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