J. Falcão Carneiro

Reduced-order thermodynamic models for servo-pneumatic actuator chambers

Abstract This paper discusses thermodynamic models of air inside pneumatic actuator chambers. In servo-pneumatics common practice, these models are simplified by neglecting the temperature dynamics. Classical models in the literature assume the temperature inside the pneumatic chamber either to be constant or to follow a polytropic law. Furthermore, the mixing process of air entering the chamber and heat transfer between air and cylinder walls is often neglected or only implicitly taken into account. This work evaluates the impact of these simplifications and order reductions in the prediction of pressure inside the actuator chamber. Classical models are compared with several others not only taking into account the mixing process but also explicitly including the heat transfer between air and cylinder walls. Simulation studies show that the reduced-order models proposed in this paper can lead to a mean square error in pressure prediction of only 10 per cent of that obtained using classical models.

Pneumatic servo valve models based on artificial neural networks

This paper presents a study where static models for the flow stage of three-port pneumatic servo valves are obtained using artificial neural networks. A new approach to build the models is introduced in detail. This approach considers two distinct models: for simulation purposes, the air mass flow is determined for a given working pressure and command input; for control purposes, the command input is determined given the working pressure and the desired air mass flow. This approach enables the use of air mass flow as the synthesized control action, thus rendering the overall pneumatic system affine. Therefore, control techniques requiring this condition on the system model can be directly used. The use of this approach in two different industrial pneumatic servo valves is presented in detail. A comparison between the different characteristics of each servo valve is also provided.This paper presents a study where static models for the flow stage of three-port pneumatic servo valves are obtained using artificial neural networks. A new approach to build the models is introduced in detail. This approach considers two distinct models: for simulation purposes, the air mass flow is determined for a given working pressure and command input; for control purposes, the command input is determined given the working pressure and the desired air mass flow. This approach enables the use of air mass flow as the synthesized control action, thus rendering the overall pneumatic system affine. Therefore, control techniques requiring this condition on the system model can be directly used. The use of this approach in two different industrial pneumatic servo valves is presented in detail. A comparison between the different characteristics of each servo valve is also provided.

Using a Conventional Servopneumatic System for Robust Motion Control in the Micrometer Range

Conventional pneumatic systems present several advantages over competitive technologies, as they do not exhibit significant heat or magnetic fields and present high force to volume ratios. Nevertheless, they are very difficult to control due to their inherent nonlinearities like friction forces or air compressibility. As a consequence, their use is limited to simple motion tasks. This paper uses a nonlinear control law, previously developed by the authors, to control a servopneumatic system in the micro meter range. Preliminary experimental results show that the control law leads to very accurate motion control in micro meter positioning tasks in any position of the piston stroke. The paper also shows, through experimental results, that the control law is robust to parametric variations (change of payloads) and to external constant disturbances (gravity force).Copyright