• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• ETRI Journal
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• v.31 no.6
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• pp.732-740
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• 2009

This paper describes the implementation of a digital audio effect system-on-a-chip (SoC), which integrates an embedded digital signal processor (DSP) core, audio codec intellectual property, a number of peripheral blocks, and various audio effect algorithms. The audio effect SoC is developed using a software and hardware co-design method. In the design of the SoC, the embedded DSP and some dedicated hardware blocks are developed as a hardware design, while the audio effect algorithms are realized using a software centric method. Most of the audio effect algorithms are implemented using a C code with primitive functions that run on the embedded DSP, while the equalization effect, which requires a large amount of computation, is implemented using a dedicated hardware block with high flexibility. For the optimized implementation of audio effects, we exploit the primitive functions of the embedded DSP compiler, which is a very efficient way to reduce the code size and computation. The audio effect SoC was fabricated using a 0.18 ${\mu}m$ CMOS process and evaluated successfully on a real-time test board.

• Speech Sciences
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• v.9 no.3
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• pp.17-24
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• 2002

The goal of this research is the real-time implementation of an AEC (Acoustic Echo Canceller) using the floating-point digital signal processor of TMS320C31. We employ an FIR-type adaptive filter with the conventional NLMS (Normalized Least Mean Square) algorithm for the adaptation of filter coefficients. We program and optimize the system in the assembler level to make it run in real-time. With 8 kHz sampling rate, the implemented AEC requires $46\;\mu$sec and $77\;\mu$sec computational time per sample for 128-and 256-tap filter, respectively. It corresponds to 37% and 62% of maximum computational ability of TMS320C31 DSP.

• MALSORI
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• no.49
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• pp.145-158
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• 2004

This paper is aiming at implementation of real-time speaker verification system using DSP board. Dialog/4, which is based on microprocessor and DSP processor, is selected to easily control telephone signals and to process audio/voice signals. Speaker verification system performs signal processing and feature extraction after receiving voice and its ID. Then through computing the likelihood ratio of claimed speaker model to the background model, it makes real-time decision on acceptance or rejection. For the verification experiments, total 15 speaker models and 6 background models are adopted. The experimental results show that verification accuracy rates are 99.5% for using telephone speech-based speaker models.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.11-14
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• 2004

This paper presents an implementation of compact vector control system for induction motor using a digital signal processor (DSP) and a smart power module (SPM). The DSP TMS320F2812 has most necessary functions for ac motor control in a single chip and SPM provides a compact power stage. The indirect vector control algorithm is implemented in the drive system using these devices. The developed system is applied by 0.8kW induction servo motor and the all functions are verified through the experiments.

• Speech Sciences
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• v.14 no.4
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• pp.157-167
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• 2007

In this paper, we implemented a single-chip speech recognizer using the TMS320C2000 DSPs. For this implementation, we had developed very small-sized speaker-dependent recognition engine based on dynamic time warping, which is especially suited for embedded systems where the system resources are severely limited. We carried out some optimizations including speed optimization by programming time-critical functions in assembly language, and code size optimization and effective memory allocation. For the TMS320F2801 DSP which has 12Kbyte SRAM and 32Kbyte flash ROM, the recognizer developed can recognize 10 commands. For the TMS320F2808 DSP which has 36Kbyte SRAM and 128Kbyte flash ROM, it has additional capability of outputting the speech sound corresponding to the recognition result. The speech sounds for response, which are captured when the user trains commands, are encoded using ADPCM and saved on flash ROM. The single-chip recognizer needs few parts except for a DSP itself and an OP amp for amplifying microphone output and anti-aliasing. Therefore, this recognizer may play a similar role to dedicated speech recognition chips.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.923-928
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• 1990

This paper describes the design and implementation of a real-time, high-precision vision system and its application to SMT(surface mounting technology) automation. The vision system employs a 32 bit MC68030 as a main processor, and consists of image acquisition unit. DSP56001 DSP based vision processor, and several algorithmically dedicated hardware modules. The image acquisition unit provides 512*480*8 bit image for high-precision vision tasks. The DSP vision processor and hardware modules, such as histogram extractor and feature extractor, are designed for a real-time excution of vision algorithms. Especially, the implementation of multi-processing architecture based on DSP vision processors allows us to employ more sophisticated and flexible vision algorithms for real-time operation. The developed vision system is combined with an Adept Robot system to form a complete SMD system. It has been found that the vision guided SMD assembly system is able to provide a satisfactory performance for SND automation.

• Journal of Power Electronics
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• v.7 no.1
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• pp.1-12
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• 2007

Novel nonlinear backstepping control with integrated adaptive control function is developed for high-performance positioning control systems. The proposed schemes are synthesized by a systematic approach and implemented based on a modern low-cost DSP controller, TMS320C32. A baseline backstepping control scheme is derived first, and is then extended to include a nonlinear adaptive control against the system parameter changes and load variations. The backstepping control utilizes Lyapunov function to guarantee the convergence of the position tracking error. The final control algorithm is a convenient in the implementation of a practical 32-bit DSP controller. The new control system can achieve superior performance over the conventional nested PI controllers, with improved position tracking, control bandwidth, and robustness against external disturbances, which is demonstrated by experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.69-74
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• 1999

This paper describes the principles of IDEA(international data encryption algorithm) which has been widely accepted as a data encryption algorithm and the implementation of the algorithm on the TMS320C54X DSP board is addressed. It is also shown that the processing time is significantly reduced by adapting high speed multiplication modulo (2^16+1) algorithm. The result shows data rates of about 250∼300Mbyte/sec.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.268-270
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• 1993

The implementation of Nonlinear Feedback Linearization control for Electro-Magnetic Suspension system is presented. The controller using TMS320C31 DSP chip was proposed and the experiments were performed Control law for EMS system using feedback linearization is derived and implemented in the DSP. Some tests were constructed far experimental comparison between feedback linearization and classical state feedback The experimental results demonstrate that the feedback linearization controller shows bettor performance than that of the classical state feedback controller and it is robust with respect to disturbance and parameter variation, though some steady-state errors appear.