Hu Hongjie

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In this paper, a novel control scheme based on RBF Neural Network is proposed for High-precision Servo System. The aim of this study is to reduce the influence which arises from modeling error, unknown model dynamics, parameter variation and disturbance acted on the practical system and to achieve high tracking precision. This scheme consists of a Neural(More)
This paper developed a model reference control scheme by introducing a PI controller and CMAC neural network (CMACNN) controller for speed control of high precision servo systems. It contemporarily improved the conception mapping algorithm of the CMACNN, which gave a determined expression of the physical memory size and designed a physical memory address(More)
This paper discusses adaptive control method used in high performance servo system based on Cerebellar Model Articulation Controller(CMAC). It analyzes the uncertain and nonlinear factors of the servo system, studies the modeling method using the frequency property of the system, and then uses an additional item to instead of the non-modeling factor. In the(More)
This paper developed a control scheme of neural network based on feedforward and PD(proportional and derivative) control for high-precision flight simulator. A radial basis-function neural network (RBFNN) controller was used to learn and to compensate the unknown model dynamics, parameter variation and disturbance of the system on-line. The iterative(More)
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