• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.211-219
• /
• 2018

This paper designs a nonlinear PI-type controller for the robust control of a boost DC-DC converter using a particle swarm optimization (PSO) algorithm. Based on the common knowledge that the transient responses can be improved if the P and I gains increase when the transient error is big, a nonlinear PI-type control design method is developed. A design procedure to autotune the nonlinear P and I gains is given based on a PSO algorithm. The proposed nonlinear PI-type controller is implemented in real time on a Texas Instruments TMS320F28335 floating-point DSP. Simulation and experimental results are given to demonstrate the effectiveness and practicality of the proposed method.

• Transactions on Electrical and Electronic Materials
• /
• v.18 no.3
• /
• pp.129-135
• /
• 2017

This paper introduces a design and a simulation of a hybrid active power filter (HAPF) for harmonics reduction given an ideal supply source. The synchronous reference frame method has been used here to identify the reference currents. The proposed HAPF uses a new artificial- intelligence technique called Particle Swarm Optimization (PSO) for tuning the parameters of a proportional and integral controller called PI-PSO. The PI-PSO controller is used to archive optimality for the DC-link voltage of the HAPF-inverter. The hysteresis non-linear current control method is used in this approach to compare the extracted reference and the actual currents in order to generate the pulse gate required for the HAPF. Results obtained by simulations with Matlab/Simuling show that the proposed approach is very flexible and effective for eliminating harmonic currents generated by the non-linear load with the HAPF based PSO tuning.

• Journal of Power Electronics
• /
• v.9 no.2
• /
• pp.207-214
• /
• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.3
• /
• pp.715-723
• /
• 2016

This paper proposes a design of optimal PI(D) controller for brushless DC (BLDC) motor speed control by the particle swarm optimization (PSO), one of the powerful metaheuristic optimization search techniques. The proposed control system is implemented on the TMS320F28335 DSP board interfacing to MATLAB/SIMULINK. With Back EMF detection, the proposed system is considered as a class of sensorless control. This scheme leads to the speed adjustment of the BLDC motor by PWM. In this work, the BLDC motor of 100 watt is conducted to investigate the control performance. As results, it was found that the speed response of BLDC motor can be regulated at the operating speed of 800 and 1200 rpm in both no load and full load conditions. Very satisfactory responses of the BLDC system can be successfully achieved by the proposed control structure and PSO-based design approach.

• Smart Structures and Systems
• /
• v.20 no.4
• /
• pp.499-508
• /
• 2017

The ionic polymer-metal composite (IPMC) is an electroactive polymer material and has a promising potential as actuators for propulsion and locomotion in underwater systems. In this paper a physics based model is used to analyse the actuation dynamics of the IPMC propulsor. Moreover, proportional-integral (PI) controller is used for position control of the tip displacement of IPMC propulsor. PI parameter tuning is performed using particle swarm optimization (PSO) algorithm. Several performance indices have been used as an objective function to optimize the error of the system. Finally, the best tuning method is found out by comparing the results under various performance indices.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1948-1949
• /
• 2011

본 논문은 볼빔시스템 제어에 대해 입자군집최적화(Particle Swarm Optimization; PSO)을 이용한 최적 퍼지제어기 설계방법을 연구한다. 볼빔 시스템은 모터와 빔, 움직이는 볼로 구성되며 볼의 위치제어를 기본 동작으로 한다. 본 논문에서는 제어성능이 우수한 퍼지제어기를 사용하여 제어시스템을 설계하는데, 퍼지제어구조는 1차 제어기와 2차 제어기로 구성되고, 최적 퍼지제어기 설계를 위해 PSO를 사용하며 PSO는 초기값에 영향이 적고 일반적인 탐색알고리즘과 달리 초기 수렴의 문제를 극복한다. 본 논문에서는 퍼지제어기와 기존의 PD 제어기의 성능비교를 시도 하였다.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.53 no.11
• /
• pp.671-679
• /
• 2004

This paper presents the on-line current controller tuning method of grid-connected inverter using PSO(particle swarm optimization) technique for minimizing the harmonic current. Synchronous frame PI current regulator is commonly used in most distributed generation. However, due to the source voltage distortion, specially in weak AC power system, current may contain large harmonic components, which increase THD(total harmonic distortion) and deteriorates power quality. Therefore, some tuning method is necessary to improve response of current controller. This paper used the PSO technique to tune the current regulator and through simulation and experiments, usefulness of the tuning method has been verified. Especially in simulating the tuning process, ASM(average switching model) of inverter is used to shorten execution time.

• Journal of Power Electronics
• /
• v.6 no.4
• /
• pp.322-329
• /
• 2006

In the last decade, the increasing restrictions imposed on the exhaust emissions from internal combustion engines and traffic limitations have increased the development of electrical propulsion systems for automotive applications. The goal of electrical and hybrid vehicles is the reduction of global emissions, which in turn leads to a decrease in fuel resource exploitation. This paper presents a novel approach for control of Induction Motors (IM) using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the Proportional Integral Controller (PI-Controller). The overall system is simulated under various operating conditions. The use of PSO as an optimization algorithm makes the drive robust and insensitive to load variation with faster dynamic response and higher accuracy. The system is tested under variable operating conditions. The simulation results show a positive dynamic response with fast recovery time.

• Journal of Power Electronics
• /
• v.19 no.4
• /
• pp.835-845
• /
• 2019

This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.

• Proceedings of the KIPE Conference
• /
• 2005.07a
• /
• pp.532-534
• /
• 2005

본 논문은 신${\cdot}$재생에너지원을 이용한 분산전원용 계통연계 인버터의 전류고조파저감에 관한 연구로서 전류고조파는 진력풍질 측면에서 중요한 요소 중의 하나이나 전원전압의 불평형, 왜곡 및 부적절한 전류제어기의 조정 등의 원인으로 인하여 이런 목적의 달성이 어렵게 된다. 전류제어기법 중에는 동기좌표게 상에서 동작하는 전향보상부 PI 제어기가 일반적으로 사용되고 있으며 본 논문에서는 전원전압 왜곡 하에서 전류제어기 이득과 전류고조파의 관계를 분석하고 Particle Swarm Optimization(PSO) 알고리즘을 이용하여 PI 제어기를 최적 조정하는 방법을 제안하였으며 모의시험과 적용실험을 통하여 그 유용성을 입증하였다.