The purpose of this paper is to examine the supporting characteristics of the air-cushion pads with a suction and reaction force. The supporting characteristics are experimentally given by the relationship between the air-cushion force, flow rate and supporting clearance in order to understand the effect of the shape of the pads. The dimensions of the shape of the pads are obtained by the diameter of the nozzle, height and diameter of the chamber, and the diameter of the diffuser. To clarify the characteristics of the non-contact and suspending support, the relationship between the maximum suction force and shape of the pads are examined. The following results ware able to be obtained : (1) the air-cushion pads have a suction and reaction force acting on the supporting body. (2) In the case of the non-contacting and suspending support, it is pointed out to be the most suitable value for the dimensions of the shape of the suction pads in considerations of the suction force and the supporting clearance. (3) The value of the supporting clearance by the suction force is much larger than that by the reaction force.

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Recently, the fuzzy control algorithm is frequently applied to various kinds of systems due to its simple algorithm, good adaptability to complex and nonlinear systems, etc. One of the problems when applying the fuzzy control algorithm is the tuning method of fuzzy control parameters for obtaining the optimum conditions. This study deals with a neuro self-tuning fuzzy controller (NSFC) applied to an electro-hydraulic servo system. The NSFC has a hierarchical structure consisting of a fuzzy algorithm being identical to the fuzzy controller at the lower loop, and a neural networek algorithm being adopted for constructing the neuro self-tuner at the upper loop. The whole procedure of NSFC was repeatedly performed by tuning input and output gains of the fuzzy controller with the neuro self-tunner, until an acceptable control level was achieved. The basic functions of NSFC can be summarized as follows : (a) to provide appropriate control action while evaluating the performance, (b) to modify the control action based on this evaluation.
It could be verified by experiment and digital simulation that the NSFC developed in this study was useful and effective for the control of an electro-hydraulic servo system.

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In this paper, a self-tuning control method for PI parameters based on the back-propagation algorithm of a multi-layered neural network is applied for position control of a pneumatic motor driving system. A set of mathematical models of the controlled object is derived. Then, the computer simulations (off-line learning) are carried out to determine the learning rate and sigmoid parameters of the neural network. In addition, a method using off-line learning is applied to shorten the time period of learning using an experimental system (on-line learning).
Computer simulations and experiments of the position control were carried out for the change in the reference trajectory or load mass. From the results summarized below, the effectiveness of the self-tuning type neural controller could be confirmed :
(1) Appropriate parameters of PI controller were identified by the applied neural controller, and the steady-state positioning accuracies of with in ±0.5mm could be obtained.
(2) The weights of neural network obtained by the off-line learning were applied to the on-line learning as initial values. The learning time was much shorter than the case using random numbers as the initial values.

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A logic valve is a controllable check valve consisting of a poppet, a sleeve and a return spring. This type of valve is mostly used as an on/off valve. Since the demands for proportional control of flow rate have been increased, these valves have been used for the proportional control. However, a seat valve is not suitable for flow control.In this paper, to make the logic valve controllable for flow, a new poppet structure is proposed.
The new poppet has been designed based on balance of forces by rearranging area ratio of the poppet. Determining areas so that unbalance force caused by supply pressure and pilot pressure is canceled by spring force, the valve lift can be proportionally controlled by the pilot pressure.
PWM control of the pilot pressure is also investigated. An attenuator is used to reduce pressure fluctuation caused by PWM drive of a pilot valve. Combination of the new type poppet and the attenuator is the PWM-controlled logic valve. Using the simulation model of the attenuator circuit, flow characteristics of the PWM-controlled logic valve can be calculated.

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