This paper deals with a sliding mode control algorithm when it is applied to an electro-hydraulic servo system. It is well known that, in such a servo system, a steady-state error can appear in time responses that originate from disturbances external to the system. We propose that, as a method for overcoming this problem, a disturbance observer be used in the sliding mode control algorithm. In the proposed algorithm, an input for the suppression of disturbance is estimated by the disturbance observer. It was verified by experiments and simulations that, in spite of the existence of unknown disturbances, the steady-state error and chatter phenomena were notably reduced by such use of a disturbance observer.

抄録全体を表示

A hydraulic servo system, which has a quick-response characteristic, high positioning accuracy and high power by itself is often used in airplanes, a construction machinery and the center of vibratory testing machines. Several papers for application of a Neural Network to servo systems have been reported. Most of them were for systems, which have slow speed response characteristics such as pneumatic servo systems. Recently application to improve the characteristics of a hydraulic servo system, a vibratory waveform control system and so forth are studied. In this study, we directly applied a Neural Network to the hydraulic pressure-waveform control system and discussed the basic characteristics such as the convergent problem of the output waveform for reference input signal and the stability problem of the system. The results were as follow :
(1) When the Neural Network is applied to the pressure-waveform control system and learns several times in one sampling period, the theoretical convergent condition equation could be obtained and confirmed by simulation and experiment.
(2) In this control system, there are convergent and divergent domains. We found that stable and unstable areas existed in the convergent domain.

抄録全体を表示

A new adaptive control algorithm is proposed for pneumatic actuators using the model-based sliding mode control approach. The design is based on the full, fourth-order, nonlinear dynamics. To overcome the need for feedback of acceleration and jerk variables, we use difference pressure between the chambers and its derivative as states. A method for adaptively estimating the unknown parameters is given. The proposed controller is simple, easy to implement, and robust to payload and parametric variations. The effectiveness of the new scheme is illustrated by implementation on an industrial piston-driven cylindrical actuator with proportional valves.

抄録全体を表示

The open-loop response of a double-rod linear actuator controlled by an electro-hydraulic servovalve is investigated for unloaded conditions using the identification method, which is conducted by the self-excited oscillation system. According to the identified parameters, the Neural Network velocity controller with a constant gain characteristic is incorporated with the inner feedback line of the position control system. A quasi model reference control approach is proposed for adapting the controller structure to considerable system changes. Thus, the Neural Network is trained under on-line conditions by the simulation. The usefulness of this technique is also experimentally verified with a real-time implementation to the servo-cylinder drive.

抄録全体を表示