• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제48권3호
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• pp.131-138
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• 1999

Generally, the digital controller has many advantages such as high precision, robustness to electrical noise, capability of flexible programming and fast response to the load variation. In this study, we have established proper mathematical equivalent model of Brushless DC (BLDC) motor and estimated the motor parameter by means of the back-emf measurement as being the step input to the controlled target BLDC motor. And the validity of proposed estimation method is confirmed by the test result of step response. As well, we have designed the reasonable digital controller as a consequence of the root locus method which is obtained from the open-loop transfer function of BLDC motor with hall sensor, and the determination of control gain for variable speed control. Here, revised Ziegler-Nichols tuning method is applied for the proper digital gain establishment, and the system stability is verified by the frequency domain analysis with Bode-plot and experimentation.

• Journal of Advanced Marine Engineering and Technology
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• 제24권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.226-228
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• 2006

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.471-476
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• 1994

In this paper a new controller is proposed which gives the resultant system the appointed input-output properties, low sensitivity and robust stability. The proposed controller consists of a reference model and a robust compensator. The reference model determines the input-output properties of the total system and is constructed by using the nominal model of the plant. We can design the reference model by applying design techniques which pay attention to steady robustness and no attention to sensitivity and robust stability, and need all state variables of the plant. The robust compensator is obtained as a solution of the mixed sensitivity problem in H infinity control theory. Therefore, low sensitivity and robust stability are guaranteed in the resultant system. The simulation experiments show that the proposed controller is effective and useful.

• 대한전기학회논문지:전력기술부문A
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• 제49권10호
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• pp.509-515
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• 2000

This paper addresses a damping control strategy of Static Synchronous Series Compensator(SSSC) and analysis model for stability study. The effect of injected voltage source generated by SSSC is modelled as equivalent load. This model is thought to be reasonable for the stability study because the dynamics of SSSC is very fast compared with that of power system. Damping controller of SSSC is based on Transient Energy Function method. The proposed control strategy is insensitive to the operating conditions like power flow level because control law depends on the phase angles. The proposed analysis model and control strategy was confirmed by WSCC 9 bus system and two area system. Especially, the robustness of proposed control strategy is demonstrated with respect to multiple operating conditions in two area system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.161-163
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• 2005

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system. we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem. and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.193-196
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• 1992

When there exist parameter uncertainty, modelling errors and nonminimum phase zeros in control object system. the stability robustness of conventional LQG and LOG/LTR methods are not satisfactory[2, 8]. Since these methods are performed on the infinite horizon, it is very hard to establish exact design parameters and thus they have lots of problems to be applied to real systems, So in this paper we propose RHLQG/FIRF optimal controller which has robust stability against parameter uncertainty, nonminimum phase zeros and modelling errors. This method uses only the information around at present and therefore shows good performance even when we do not know exact design parameters. We here compare LQG and LQG/LTR method with RHLQG/FIRF controller and exemplify that RHLQG/FIRF controller has better robust stability performance via simulations.

• 한국소음진동공학회논문집
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• 제22권7호
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• pp.650-658
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• 2012

This paper proposes a high performance position controller for a driving system using a time optimal controller which has been widely used to control driving systems to achieve desired reference position or velocity in a minimum response time. The main purpose of this research lies in an improvement of transient response performance rather than that of steady-state response in comparison with other control strategies. In order to refine the scheme of time optimal control, Lyapunov stability proofs are incorporated in a controller of standard second order system model. This scheme is applied to the control of a driving system. In view of the simulation and experiment results, the standard second order system model exhibits better minimum-time control performance and robustness than double integral system model does.

• 대한기계학회논문집A
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• 제24권4호
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• pp.1007-1015
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• 2000

This paper proposes an adaptive trajectory generation strategy of using on-line ZMP information and an impedance control method for biped robots. Since robots experience various disturbances during their locomotion, their walking mechanism should have the robustness against those disturbances, which requires an on-line adaptation capability. In this context, an on-line trajectory planner is proposed to compensate the required moment for recovering stability. The ZMP equation and sensed ZMP information are used in this trajectory generation strategy. In order to control a biped robot to be able to walk stably, its controller should guarantee stable footing at the moment of feet contacts with the ground as well as maintaining good trajectory tracking performance. Otherwise, the stability of robot will be significantly compromised. To reduce the magnitude of an impact and guarantee a stable footing when a foot contacts with the ground, this paper. proposes to increase the damping of the leg drastically and to modify the reference trajectory of the leg. In the proposed control scheme, the constrained leg is controlled by impedance control using the impedance model with respect to the base link. Computer simulations performed with a 3-dof environment model that consists of combination of a nonlinear and linear compliant contact model show that the proposed controller performs well and that it has robustness against unknown uneven surface. Moreover, the biped robot with the proposed trajectory generator can walk even when it is pushed with a certain amount of external force.

• Structural Engineering and Mechanics
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• 제90권1호
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.