• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.114-123
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• 2005

A nonlinear speed control of a PMSM using a sequential parameter auto-tuning algorithm for servo equipments is presented. The nonlinear control scheme gives an undesirable output performance under the mismatch of the system parameters and load conditions. Recently, to improve the performance, an adaptive linearization scheme, a sliding mode control and an observer-based technique have been reported. Although a good performance can be obtained, the performance is not satisfactory any more under specific conditions such as a large inertia variation, a fast speed transient or an increased sampling time. The simultaneous estimation of principal parameters giving a direct influence on speed dynamics is generally not simple. To overcome this problem, a a sequential parameter auto-tuning algorithm at start-up is proposed, where dominant parameters are estimated in a prescribed regular sequence based on the method that one parameter is estimated during each interval. The proposed scheme is implemented on a PMSM using DSP TMS320C31 and the effectiveness is verified through simulations and experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.334-336
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• 2005

This paper proposes a simple MPPT control scheme of a Current- Control-Loop Error system Based that can be obtains a lot of advantage to compare with another digital control method, P&O and IncCond algorithm, that is applied mostly a PV system. An existent method is needed an expensive processor such as DSP that calculated to change the measure power of a using current and voltage sensor at the once. But, a proposed method is easy to solve the cost reduction and power unbalance problems that it is used by control scheme to limit error of a current control of common sensor. This proposed algorithm had verified through a simulation and an experiment on battery charger using PIC that is the microprocessor of a low price.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.160-163
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• 2005

This paper proposes a simple MPPT control scheme of a Current-Control-Loop Error system Based that can be obtains a lot of advantage to compare with another digital control method, P&O and IncCond algorithm, that is applied mostly a PV system. An existent method is needed an expensive processor such as DSP that calculated to change the measure power of a using current and voltage sensor at the once. Therefore, it is applied a small home power generation system that required many expenses. But, a proposed method is easy to solve the cost reduction and power unbalance problems that it is used by control scheme to limit error of a current control of common sensor. This proposed algorithm had verified through a simulation and an experiment on battery charger using PIC that is the microprocessor of a low price.

• Journal of Power Electronics
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• v.7 no.3
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• pp.265-270
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• 2007

Equal rating DC-DC converter modules can be connected in series at the input for circuits requiring higher input voltages and in parallel at the output for circuits requiring higher output currents. Since the converter modules may not be practically identical, closed loop control has to ensure that each module equally shares the total input voltage and the load current. A control scheme consisting of a common output voltage loop, individual inner current loops and individual input voltage loops have been designed in this work to achieve input voltage and load current sharing as well as load voltage regulation under supply and load disturbances. The output voltage loop provides the basic reference for the inner current loops, which are also modified by the respective input voltage loops. The average of the converter input voltages, which is dynamically varying, is chosen as the reference for input voltage loops. This choice of reference eliminates interaction among different control loops. Type II compensators and Fuzzy Logic Controllers (FLCs) are designed and compared through MATLAB based simulation and FLC is found to be satisfactory. Hence TMS320F2407A DSP based FLC is implemented and the results are presented which prove the superiority of the FLC developed for this research.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1578-1586
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• 2016

A power quality improvement scheme for grid connected inverters, even in the presence of the disturbances in grid voltages due to harmonic distortions and three-phase imbalance, is presented for distributed generation (DG) power systems. The control objective is to force the inverter currents to follow their references with robustness even under external disturbances in grid voltages. The proposed scheme is realized by a disturbance observer (DOB) based current control scheme. Since the uncertainty in a system can be effectively canceled out using an estimated disturbance by the DOB, the resultant system behaves like a closed-loop system consisting of a disturbance-free nominal model. For experimental verification, a 2 kVA laboratory prototype of a grid connected inverter has been built using a digital signal processor (DSP) TMS320F28335. Through comparative simulations and experimental results under grid disturbances such as harmonic distortion and imbalance, the effectiveness of the proposed DOB based current control scheme is demonstrated.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.680-683
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• 2005

This paper proposes a simple MPPT control scheme of a Current-Control-Loop Error system Based that can be obtains a lot of advantage to compare with another digital control method, P&O and IncCond algorithm that is applied mostly a PV system. An existent method is needed an expensive processor such as DSP that calculated to change the measure power of a using current and voltage sensor at the once. Therefore, it is applied a small home power generation system that required many expenses. But, a proposed method is easy to solve the cost reduction and power unbalance problems that it is used by control scheme to limit error of a current control of common sensor. This proposed algorithm had verified through a simulation and an experiment on battery charger using PIC that is the microprocessor of a low price.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.3
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• pp.61-68
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• 2012

This paper deals with a fault diagnosis algorithm for open faults in the switching devices of PWM inverter-fed IPMSM (Interior Permanent Magnet Synchronous Motor) drive. The proposed diagnostic algorithm is realized in the controller using the informations of three-phase currents or reference line-to-line voltages, without requiring additional equipments for fault detection. Under switch open fault conditions, the conventional dq model used to control an AC motor cannot directly be applied for the analysis of drive system, since three-phase balanced condition does not hold. To overcome this limitation, a fault model based on the line-to-line voltages is employed for the simulation studies. For comparative performance evaluation through the experiments, the entire control system is implemented using digital signal processor (DSP) TMS320F28335. Simulations and experimental results are presented to verify the validity of the proposed diagnosis algorithm.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.35-47
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• 2004

In this paper presents a new approach to the design and real-time implementation of fuzzy control system based-on digital signal processors(DSP:IMS320C80) in order to improve the precision and robustness for system of industrial robot(Dual-Arm with 8 joint Robot). The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The IMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a FLC(Fuzzy Logic Controller), one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed SOFC scheme is simple in structure, Int in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.