• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.47-55
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• 2003

This paper Presents active control algorithm using probability density function of structural energy. It is assumed that the structural energy under excitation has Rayleigh probability distribution. This assumption is based on the fact that Rayleigh distribution satisfies the condition that the structural energy is always positive and the occurrence probability of minimum energy is zero. The magnitude of control force is determined by the probability that the structural energy exceeds the specified target critical energy, and the sign of control force is determined by Lyapunov controller design method. Proposed control algorithm shows much reduction of peak responses under seismic excitation compared to LQR controller, and it can consider control force limit in the controller design. Also, chattering problem which sometimes occurs in Lyapunov controller can be avoided.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1018-1020
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• 1996

In this paper, when a robust active noise controller for a small cavity to control the noise induced in the cavity is designed, the Graphical method based on the robust stability and performance requirements is studied. The problem of designing controller that achieve these robust performance conditions is related to minimizing the $H_{\infty}$ norm of the mixed sensitivity function by using $H_{\infty}$ control theory. Also, For design the controller, the loopshaping method which control the weight functions to satisfy the design specification without loss of a robust performance can be used. Therefore, we determined the acceptable design specification with the system characteristics of the small cavity and obtained its robust controller with the robust performance specifications by stability margin.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.28-31
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• 2014

This paper is concerned with the active vibration control of washing machine. To this end, a new control algorithm utilizing an acceleration signal as a sensor signal is newly developed based on the principle of a dynamic absorber. The resulting control algorithm was implemented digitally on the DSP board. The accelerometer and the active linear actuator were used as sensor and actuator for the active vibration control of washing machine. Experimental results show that the proposed control algorithm can be effectively used for a controller which uses an accelerometer.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.378-381
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• 1991

In this paper, the active noise controll system in duct is analyzed with real time implementation. The primary noise signal detected by microphone is modeled using adaptive algorithm and the secondary signal which has the same amplitude and $180^{\circ}$ phase shift with the primary noise signal is generated in the controller. The signal processor DSP56001 is used to implement the real-time controller and the experimental results shows that our system can reduce the noise level in duct to $20{\sim}40$ [db].

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.267-275
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• 2004

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller is tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.3 s.108
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• pp.298-306
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• 2006

In our previous paper, we developed a robust saturation controller for the linear time-invariant (LTI) system involving both actuator's saturation and structured real parameter uncertainties. This controller can only guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. But we cannot analytically make any comment on control performance of this controller. In this paper, we suggest a method to use linear matrix inequality (LMI) optimization problem which can analytically explain control performance of this robust saturation controller only in nominal system. The availability of design method using LMI optimization problem for this robust saturation controller is verified through a numerical example for the building with an active mass damper (AMD) system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.227-231
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• 2004

In this paper, a robust Sliding Mode Variable Structure (SMVS) controller is designed for Active Queue Management (AQM). This type of controller is insensitive to noise and variance of the parameters, thus it is suitable to time varying network systems. Simulation results conform the robust performance of SMVS controller against the disturbance. At the same time, a complete comparison between SMVS and PI controllers is made. The conclusion is that both transient and steady state performance of SMVS controller is better than that of PI one.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.9-22
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• 2019

In this paper, we propose a method that can be applied to the efficient implementation of multi-channel active noise controller. Since the normalized MFxLMS (Modified Filtered-x Least Mean Square) algorithm for the multi-channel active noise control requires a large amount of computation, the difficulty has lied in implementing the algorithm using a low-cost MCU (Microcontoller Unit). We implement the multi-channel active noise controller efficiently by optimizing the software based on the features of the MCU. By maximizing the usage of single-cycle MAC (Multiply- Accumulate) operations and minimizing move operations of the delay memory, we can achieve more than 3 times the performance in the aspect of computational optimization, and by parellel processing using the auxillary processor included in the MCU, we can also obtain more than 4 times the performance. In addition, the usage of additional parts can be minimized by maximizing the usage of the peripherals embedded in the MCU.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1964-1966
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• 2001

Active Noise control(ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. This research presents ANFIS (Adaptive Network Fuzzy Inference System) controller for adaptively noise cancelling in a duct. ANC system generates secondary control sound pressure with same amplitude and with opposite phase as noise to be eliminated. ANFIS controller is trained to optimize its parameters for adaptively cancelling noise. That is ANFIS train its parameters by gradient descent and LSE method so called hybrid method. This paper present ANFIS in active noise control which provides an improvement convergence speed and limitation of linearity condition. It can model nonlinear functions of arbitrary complexity and ANFIS can construct an input-ouput mapping based on both human knowledge in the form of Takagi and Sugeno's fuzzy if-then rules and stipulated input-output data pairs. This paper also shows that the proposed ANFIS active noise control system successfully cancelled noise.