• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.227-229
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• 1997

The torque of SRM is developed by phase currents and inductance variation. The inductance of torque generation region is nonlinearly varied according to phase current. By this nonlinear characteristics, torque ripple can be generated on the condition of constant current. Otherwise, phase current should be controlled instantaneously in accordance with inductance to reduce torque ripple. In this paper, the control system with neural network that can reduce torque ripple is suggested. In this control system, instantaneous inductance and optimal current waveform for smallest torque ripple is obtained by neural network. And this required optimal current waveform is regulated by voltage control.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.780_781
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using hybrid intelligent controller(HIC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The optimal current can be decided according to the operating speed and the load conditions. This paper proposes speed control of IPMSM using ALM-FNN, current control of model reference adaptive fuzzy control(MTC) and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HIC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1813-1820
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• 2016

Dual-mode photovoltaic power system should be capable of operating in grid-connected (GC) and stand-alone (SA) modes for distributed generation. Under different working modes, the optimal parameters of inverter output filters vary. Inverters commonly operate in GC mode, and thus, a small capacitance is beneficial to the GC topology for achieving a reasonable compromise. A predictive current control scheme is proposed to control the grid current in GC mode and thereby obtain high-performance power. As filter are not optimal under SA mode, a compound control strategy consisting of predictive current control, instantaneous voltage control, and repetitive control is proposed to achieve low total harmonic distortion and improve the output voltage spectrum. The seamless transfer between GC mode and SA mode is illustrated in detail. Finally, the simulation and experimental results of a 4 kVA prototype demonstrate the effectiveness of the proposed control strategy.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.91-94
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• 2000

This paper is focussed on an optimal efficiency control which is operated by voltage-current pattern such as to maintain the maximum efficiency output characteristics of the motor. The voltage control is realized by phase control thyristers.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.6
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• pp.920-927
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• 1998

This paper presents a synthetic control algorithm that generates the rudder command angle to track the optimal route which is composed of straight-lines among way-points with keeping a required error limit. The control algorithm comprises three main lgorithms that is a course-keeping algorithm that eliminates the yaw angle difference between optimal route and current route a track-keeping algorithm that tracks the optimal route among way-points and a turning-control algorithm that includes the generation of optimal turning routes and control method. The effectiveness of the proposed control algorithm is assured through computer simulation.

• Journal of Power Electronics
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• v.19 no.2
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.359-362
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using multi adaptive fuzzy learning controller(AFLC). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of Welding and Joining
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• v.33 no.6
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• pp.13-20
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• 2015

Many automotive companies are endeavoring to improve the quality of resistance spot welding by updating body-in-white (BIW) production line with adaptive control spot welding system to compensate the process disturbances such as gap, electrode wear, oxidized surfaces, poor fit up and adhesive etc. Most of the commercial adaptive weld controllers require proper "Initial Welding Schedule" or "Reference weld" to achieve compensation in welding parameters during real time welding. In this study, the compensation of a commercial adaptive weld controller had been observed and analyzed thoroughly for various process disturbances to find optimal initial welding schedule. It was observed that 90 percent of the expulsion current in constant current control as reference welding schedule conferred the maximum button diameter in adaptive control welding. Finally, effects of each disturbance in combined field disturbances system with adaptive control had also been confirmed with the design of experiment (DOE) by minitab(R)16 for combined disturbances situation and suitability of optimum initial weld current had also established with real body part validation test.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.213-216
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• 2005

In this research, we explore how to manage the transition of technology generations considering incremental innovation of the existing technology generation. Firms can slow down decaying of the existing technology by continuous incremental improvements rather than introducing a new generation technology at the first time if the former strategy is better. We characterize optimal technology transition problem by setting up an optimal control model. The model which is originally designed and solved by Thompson(1968) as a ‘Machine maintenance problem’ has been cited to build the main body of our model. With this analytical model, we derive optimal ‘incremental innovation’ strategy which is considering transition to the next technology. Our analysis indicates that there exists an unique ‘stopping incremental innovation timing’. Before the point of time, the decision maker should make his effort at a maximum level to enhance the current technology. However from the stopping timing to the final time horizon where the new technology is introduced, it is found that not to invest to the current technology any more is optimal.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.104-105
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• 2013

When actual IPMSM is driving, it is difficult to figure out the correct current during the current control period due to the operation speed limit of digital signal processing. Therefore, in order to control IPMSM for electric vehicle efficiently, we should design 2D Look-up Table to find out optimal current reference corresponding to speed and torque of IPMSM. This paper explains the design method of 2D Look-up Table for optimal current control of constant torque area and constant output area of IPMSM for electric vehicle. Finally, experimental results are presented to verify the reliability of 2D Look-up Table.