• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.05b
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• pp.170-174
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• 2005

The purpose of this study is to design the digital surge counter for lightning arresters. The used detecting method for surges is using the signal of both ends of ZnO varistor. The electronic detecting parts of the digital counter are arranged in outside of main processer for protecting it from noise. The detecting parts change detected signals into small signals. The countermeasures for noises are (1) Shielding (2) Reinforcement of power circuits (3) Cables & Circ1e core (4) Watch-doc & control of input signals.