• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.63-71
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• 2000

This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithm(GA) to improve system stability. Genetic algorithms(GAs) are search algorithms based on the mechanics of natural selection and natural genetics. To verify the validity of the proposed method, investigated damping ratio of the eigenvalues of the electro-mechanical modes system with and without SVC. Also, we considered dynamic response of terminal speed deviation and terminal voltage deviation by applying a power fluctuation at heavy load, normal load and light to verify the robustness of the proposed. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-bus with SVC system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.3
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• pp.313-319
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• 2017

This study presents a genetic algorithm (GA) to design a PID controller systematically for an inchworm operated by piezoelectric actuators. The performance index considering overshoot and settling time is adopted to search an optimal PID gain using GA. The piezoelectric actuator shows nonlinear characteristics including hysteresis and residual displacement. The PID feedback system combined with an integrator is used to improve the ability of tracking the complex input signals and suppressing the steady state error. The PID controller tuned by GA can track the various motion contours effectively. However, the PID controller shows an improper residual vibration under the application of high-frequency square input. The input shaper combined with the feedback system can overcome this limitation of the PID controller.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.820-823
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• 2003

In this paper, we describe a design procedure for cascade controller for induction motor drives based on Genetic Algorithms(GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps(firstly the current controller and then the speed controller). We search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.4
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• pp.271-276
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• 2006

To implement a generalization of value functions in Adaptive Search Element (ASE)-reinforcement learning, CMAC (Cerebellar Model Articulation Controller) is integrated into ASE controller. ASE-reinforcement learning scheme is briefly studied to discuss how CMAC is integrated into ASE controller. Neighbourhood Sequential Training for CMAC is utilized to establish the look-up table and to produce discrete control outputs. In computer simulation, an ASE controller and a couple of ASE-CMAC neural network are trained to balance the inverted pendulum on a cart. The number of trials until the controllers are established and the learning performance of the controllers are evaluated to find that generalization ability of the CMAC improves the speed of the ASE-reinforcement learning enough to realize the cartpole control system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.1
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• pp.36-43
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• 2003

This paper presents an optimal tuning method for Fuzzy Logic Controller (FLC) of current controller for HVDC using Genetic Algorithm(GA). GA is probabilistic search method based on genetics and evolution theory. The scaling factors of FLC are tuned by using real-time GA. The proposed tuning method is applied to the scaled-down HVDC simulator at Korea Electrotechnology Research Institute(KERI). Experimental result shows that disturbances are well-damped and the dynamic performances of FLC have the better responses than those of PI controller for small and large disturbances such as ULTC tap change, reference DC current change and DC ground fault.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.345-347
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• 2005

The electric demands increase, financial need for new power plant constructions and environmental problem have led to search for more efficient energy production and load management. To minimize the construction of power plants and reduce total power consumption include installation of demand controller to industrial applications. Accordingly to maximize the load control by the diffusion of demand controller, govermental economic supports as well as the analysis of energy saving effects. This paper presents the cost-effectiveness analysis for DSM program evaluation and case study to analyze demand controller DSM program.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.246-254
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1327-1332
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• 2003

In this paper, an ATC(Automated Transfer Crane) control system is required rapid transportation to get highest productivity with low cost. Therefore, the container paths should be built in terms of the least time and least sway when container is transferred from the initial coordinate to the finial coordinate. So we applied the best-first search method for forming the container path, and calculated the anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the neural network two degree of freedom PID (TDOFPID) controller to control the precise navigation. For simulation, we constructed the container profiles so that we analyzed the state of formed path and the performance of TDOFPID controller to the formatted path. Then we compared the performance of ES-tuned PID controller with our proposed controller in terms of trolley position, anti-sway, path change, disturbance, and the load of containers. The computer simulation results show that the proposed controller has better the other on the various conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.93-101
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• 2016

This study presents a simple genetic algorithm to systematically design a PID controller for a hydraulic positioning system operated by a proportional solenoid valve. The inverse dead-zone compensator with nonlinear characteristics is used to cancel out the dead-zone phenomenon in the hydraulic system. The object function considering overshoot, settling time, and control input is adopted to search for optimal PID gains. The designed PID controller is compared with the LQG/LTR controller to check the performance of the hydraulic positioning system in the time and frequency domains. The experimental results show that the hydraulic servo system with the proposed PID controller responds effectively to the various types of reference input.