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(Qiang et al., 2006). presented the results on the modeling and control of a pneumatic system. With Levenberg-Marquardt method, a neural network model, from which a third-order ARX model was derived, has been developed for the pneumatic system. Based on the built ARX model, a direct digital controller was designed with Ragazzini method. To reject external noise, a disturbance observer (DOB) was constructed as shown in figure (4) to improve the control accuracy. The experimental results of the position control for the pneumatic system were given to demonstrate the performance of the DOB-based controller. The accuracy and response speed were satisfactory for both steady state and dynamic tracking.

Figure 5 (Qiang et al., 2006). presented the results on the modeling and control of a pneumatic system. With Levenberg-Marquardt method, a neural network model, from which a third-order ARX model was derived, has been developed for the pneumatic system. Based on the built ARX model, a direct digital controller was designed with Ragazzini method. To reject external noise, a disturbance observer (DOB) was constructed as shown in figure (4) to improve the control accuracy. The experimental results of the position control for the pneumatic system were given to demonstrate the performance of the DOB-based controller. The accuracy and response speed were satisfactory for both steady state and dynamic tracking.

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Fig. (1b): Vane rotary pneumatic actuator. Pneumatic Actuators: Applications and Related Work: Pneumatic servos have advantages over hydraulics in high temperature and nuclear environments. The actuator, rather than the servo valve, generally limits system response and stiffness. Where simplicity and cost are paramount, the piston cylinder is probably the best choice. But if minimum fuel consumption is desired rotary type of motor is indicated. (Taplin et a/., 1963). also have been shown the rotary servo has nearly twice the band pass of the piston cylinder servo. This result is typical for many applications. In short duration missile applications, the weight of a self-contained solid propellant pneumatic servo may be half that of an equivalent self contained hydraulic system. Where a pneumatic system is to replace a heavier hydraulic system, maximum dynamic response and output stiffness are essential. The outstanding difference between pneumatic and hydraulic systems arises from the low bulk modulus of the pneumatic working medium. The bulk modulus of a gas is p, where hh is the ratio of specific heats for the gas and p is the instantaneous pressure. This is the major obstacle in achieving a high response pneumatic system.
Fig. (1b): Vane rotary pneumatic actuator. Pneumatic Actuators: Applications and Related Work: Pneumatic servos have advantages over hydraulics in high temperature and nuclear environments. The actuator, rather than the servo valve, generally limits system response and stiffness. Where simplicity and cost are paramount, the piston cylinder is probably the best choice. But if minimum fuel consumption is desired rotary type of motor is indicated. (Taplin et a/., 1963). also have been shown the rotary servo has nearly twice the band pass of the piston cylinder servo. This result is typical for many applications. In short duration missile applications, the weight of a self-contained solid propellant pneumatic servo may be half that of an equivalent self contained hydraulic system. Where a pneumatic system is to replace a heavier hydraulic system, maximum dynamic response and output stiffness are essential. The outstanding difference between pneumatic and hydraulic systems arises from the low bulk modulus of the pneumatic working medium. The bulk modulus of a gas is p, where hh is the ratio of specific heats for the gas and p is the instantaneous pressure. This is the major obstacle in achieving a high response pneumatic system.
A robust control method using the dynamic impedance matching method was proposed by Shigeru et al 1995). This method was presented to make pneumatic actuator robust to load variation so that velocity (c force) output characteristics remain the same under load (or velocity) change. Complete robustness of actuato velocity output applied load requires actuator internal impedance to be strictly zero. Achievement of thi condition is actually difficult, due to errors in actuator modeling and insufficient output measurement: However, actuator internal impedance can be made small by using proper feedbacks from two outputs, forc and velocity and by supporting the existence of energy dissipating element in environment for system stability To overcome the problems of the din and vibration that are resulted from the control valve in the pneumati system, (Morioka et al., 2000). proposed a simple controller structure shown in figure (2) using loop-shapin nethod. In this design scheme, the change of distance between the pneumatic actuator and the control valve are considered. As a result, the control valves, that are a source of a din and vibration, can be set apart fror he pneumatic actuators. The proposed pneumatic servo systems, that can reduce a din and vibration, can b stalled in the medical and welfare facilities. At the same time, the proposed control is very simple. Therefor it can be implemented on the cheap one board microcomputer. It also be noted that the proposed metho admits the change of the plumbing route. The payload variation and external disturbance uncertainties are nc aken in account. Fig. 2: Two degree of freedom control.
A robust control method using the dynamic impedance matching method was proposed by Shigeru et al 1995). This method was presented to make pneumatic actuator robust to load variation so that velocity (c force) output characteristics remain the same under load (or velocity) change. Complete robustness of actuato velocity output applied load requires actuator internal impedance to be strictly zero. Achievement of thi condition is actually difficult, due to errors in actuator modeling and insufficient output measurement: However, actuator internal impedance can be made small by using proper feedbacks from two outputs, forc and velocity and by supporting the existence of energy dissipating element in environment for system stability To overcome the problems of the din and vibration that are resulted from the control valve in the pneumati system, (Morioka et al., 2000). proposed a simple controller structure shown in figure (2) using loop-shapin nethod. In this design scheme, the change of distance between the pneumatic actuator and the control valve are considered. As a result, the control valves, that are a source of a din and vibration, can be set apart fror he pneumatic actuators. The proposed pneumatic servo systems, that can reduce a din and vibration, can b stalled in the medical and welfare facilities. At the same time, the proposed control is very simple. Therefor it can be implemented on the cheap one board microcomputer. It also be noted that the proposed metho admits the change of the plumbing route. The payload variation and external disturbance uncertainties are nc aken in account. Fig. 2: Two degree of freedom control.
Fig. 3: Internal model controller with DRNN. (Xuesong eft al., 2003). studied the modeling and motion control of manipulators driven by single rod pneumatic actuators. The dynamics model of pneumatic manipulator is analyzed profoundly at first. Then aim at the highly nonlinear, strong coupling, time various of pneumatic manipulator dynamics, a new internal model controller for pneumatic robot servo system is presented, which has a three layer feedforward neural network as controller (NNC) and a diagonal recurrent neural network (DRNN) as model predictor (NNM). Computer simulation results indicate that the system has strong robustness and significantly improves the control performance of pneumatic manipulator. As shown in figure (3) NNC and NNM represent neural network controller and neural network model predictor respectively.
Fig. 3: Internal model controller with DRNN. (Xuesong eft al., 2003). studied the modeling and motion control of manipulators driven by single rod pneumatic actuators. The dynamics model of pneumatic manipulator is analyzed profoundly at first. Then aim at the highly nonlinear, strong coupling, time various of pneumatic manipulator dynamics, a new internal model controller for pneumatic robot servo system is presented, which has a three layer feedforward neural network as controller (NNC) and a diagonal recurrent neural network (DRNN) as model predictor (NNM). Computer simulation results indicate that the system has strong robustness and significantly improves the control performance of pneumatic manipulator. As shown in figure (3) NNC and NNM represent neural network controller and neural network model predictor respectively.
Fig. 7: Two degree of freedom QFT control structure. In order to track the desired position and desired pressure in the pneumatic actuator chambers, a slidin mode control law was presented in different ways as stated in the following: okie - a ae 2 Py - ¥ ee ae Z 7 ae s = wa 7 7 Ps (Samaoui et al., 2004) introduced a second order sliding mode control approach in the context of position control of an electropneumatic system. The main objective was to demonstrate through this approach the undesired chattering phenomenon can be avoided while retaining the same robustness of first order sliding mode control.
Fig. 7: Two degree of freedom QFT control structure. In order to track the desired position and desired pressure in the pneumatic actuator chambers, a slidin mode control law was presented in different ways as stated in the following: okie - a ae 2 Py - ¥ ee ae Z 7 ae s = wa 7 7 Ps (Samaoui et al., 2004) introduced a second order sliding mode control approach in the context of position control of an electropneumatic system. The main objective was to demonstrate through this approach the undesired chattering phenomenon can be avoided while retaining the same robustness of first order sliding mode control.
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