• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.9
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• pp.1234-1240
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• 2002

A new feedback control law is proposed and tested for suppressing the vortex shedding from a circular cylinder in a uniform flow. The lift coefficient ( $C_{L}$) is employed as a feedback control signal and the control forcing is given by a rotational oscillation of the cylinder. The influence of the feedback transfer function on the $C_{L}$ reduction is examined. The main rationale of the feedback control is that a feedback control forcing is imposed at a phase which is located outside the range of lock-on. By applying the feedback control law, $C_{L}$ is reduced significantly. Furthermore, the reduction mechanism of $C_{L}$ is analyzed by showing the vortex formation modes with respect to the forcing phase.e.ase.e.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.526-528
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• 2006

An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

• Structural Engineering and Mechanics
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• v.12 no.6
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• pp.633-656
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• 2001

In this paper, modal control with direct output feedback is formulated in a systematic manner for easy implementation. Its application to the seismic protection of structural systems is verified by a shaking table test, which involves a full-scale building model and an active bracing system as the control device. Two modal control cases, namely, one full-state feedback and one direct output feedback control were tested and compared. The experimental result shows that in mitigating the seismic response of building structures, modal control with direct output feedback can be as effective and efficient as that with full-state feedback control. For practical concerns, the control performance of the proposed method in the presence of sensor noise and stiffness modeling error was also investigated. The numerical result shows that although the control force may be increased, the maximum floor displacements of the controlled structure are very insensitive to sensor noise and modeling error.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.1
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• pp.27-33
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• 2009

Human postural responses appeared to have stereotyped modality, such as ankle mode, knee mode and hip mode in response to various perturbations. We examined whether human postural control gain of full-state feedback could be decoupled along with the eigenvector. To verify the model, postural responses subjected to fast backward perturbation were used. Upright posture was modeled as 3-segment inverted pendulum incorporated with feedback control, and joint torques were calculated using inverse dynamics. Postural modalities such as ankle, knee and hip mode were obtained from eigenvectors of biomechanical model. As oppose to the full-state feedback control, independent eigenvector control assumes that modal control input is determined by the linear combination of corresponding modality. We used optimization method to obtain and compare the feedback gains for both independent eigenvector control and full-state feedback control. As a result, we found that simulation result of eigenvector feedback was not competitive in comparison with that of full-state feedback control. This implies that the CNS would make use of full-state body information to generate compensative joint torques.

• Earthquakes and Structures
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• v.6 no.2
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• pp.217-235
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• 2014

In this paper, different feedback control strategies are presented for active seismic control using proportional-integral-derivative (PID) type controllers. The parameters of PID controller are found by using an numerical algorithm considering time delay, maximum allowed control force and time domain analyses of shear buildings under different earthquake excitations. The numerical algorithm scans combinations of different controller parameters such as proportional gain ($K_p$), integral time ($T_i$) and derivative time ($T_d$) in order to minimize a defined response of the structure. The controllers for displacement, velocity and acceleration feedback control strategies are tuned for structures with active control at the first story and all stories. The performance and robustness of different feedback controls on time and frequency responses of structures are evaluated. All feedback controls are generally robust for the changing properties of the structure, but acceleration feedback control is the best one for efficiency and stability of control system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• Proceedings of the KAIS Fall Conference
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• 2005.05a
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• pp.191-193
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• 2005

In this paper new, inverter control system for TG feedback a formula Control was developed. The motor control system with TG feedback controller as an effect of load disturbance, it is very difficult to guarantee the robustness of control system. The function of the implementation we TG feedback type, and temperature scheme. The Inverter Control System approach is based on master-slave control concept. To show validity of the developed new inverter control system, several experiments are illustrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1911-1916
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• 2005

In this study, the basic motor control system had been investigated. The Discrete-Time Feedback Error Learning (DTFEL) method is used to control this system. This method is anologous to the original continuous-time version Feedback Error Learning(FEL) control which is proposed as a control model of cerebellum in the field of computational neuroscience. The DTFEL controller consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such the tracking perfect, the adaptive law is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The PD control theory is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.