• Journal of KSNVE
• /
• v.11 no.1
• /
• pp.147-155
• /
• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• Journal of Advanced Navigation Technology
• /
• v.16 no.6
• /
• pp.1123-1133
• /
• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method and vector control system of the speed estimation a using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.986-988
• /
• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). Some drawbacks of the classical DTC are the relatively large torque ripple in a low speed range and notable current pulsation during steady state. They are reflected speed response and increased acoustical noise. In this paper, the DTC quick response are preserved at transient state, while better qualify steady state performance is produced by space vector modulation (SVM). The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAC) with rotor flux linkages for the speed fuming signal at low speed range, two hysteresis controllers and optimal switching look-up table. Simulation results of the suggest system for the 2.2 [kW] general purposed induction motor are presented and discussed.

• Journal of KSNVE
• /
• v.9 no.1
• /
• pp.121-130
• /
• 1999

Generally, A Dynamic Absorber by using Active viscous Damping is highlighted for effective suspension system, such as improved ride comfort and handling in the market. Lately, this system based on the Sky-Hook damper theory is introduced by the name of "Active Dynamic Absorber" to us. This system has an excellent performance in contrast to Passive. Adaptive Dynamic Absorber, besides having low cost components of system, low energy consumption. light weight of system. In this viewpoint. most of car-maker will adopt this system in the near future. For this reason, we developed Dynamic Absorber by using Active viscous Damping which is equipped with continuously variable Dynamic Absorber and Control logic consisting Filter and Estimator. control apparatus of Dynamic Absorber operated by 16-bit microprocessor of high performance. variable device of viscous Damping. G-sensor so on. In this paper. several important points of development procedure for realizing this system will be described with results in which is obtained from experiment by simulation and Full car test in Proving ground. respectively.pectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.10A
• /
• pp.1223-1229
• /
• 2004

A variable-gain low-voltage low noise amplifier MMIC operating at 5GHz frequency band is designed and implemented using the ETRI 0.5$\mu\textrm{m}$ GaAs MESFET library process. This low noise amplifier is designed to have the variable gain for adaptive antenna array combined in HIPERLAN/2. The feedback circuit of a resistor and channel resistance controlled by the gate voltage of enhancement MESFET is proposed for the variable-gain low noise amplifier consisted of cascaded two stages. The fabricated variable gain amplifier exhibits 5.5GHz center frequency, 14.7dB small signal gain, 10.6dB input return loss, 10.7dB output return loss, 14.4dB variable gain, and 2.98dB noise figure at V$\_$DD/=1.5V, V$\_$GGl/=0.4V, and V$\_$GG2/=0.5V. This low noise amplifier also shows-19.7dBm input PldB, -10dBm IIP3, 52.6dB SFDR, and 9.5mW power consumption.

• Journal of international Conference on Electrical Machines and Systems
• /
• v.3 no.3
• /
• pp.272-275
• /
• 2014

An improved fuzzy Kalman filtering speed estimation scheme was proposed by means of measuring stator side voltage and current value based on vector control state equation of induction motor. The designed fuzzy adaptive controller conducted recursive online correction of measurement noise covariance matrix by monitoring the ratio of theory residuals and actual residuals to make it approach real noise level gradually, allowing the filter to perform optimal estimation to improve estimation accuracy of EKF. Meanwhile, co-simulation scheme based on MATLAB and Ansoft was proposed in order to improve simulation accuracy. Field-circuit coupling problems of induction motor under the action of vector control were solved and the parameter optimization accuracy was improved dramatically. The simulation and experimental results show that this algorithm has a strong ability to inhibit the random measurement noise. It is able to estimate motor speed accurately, and has superior static and dynamic characteristics.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.6
• /
• pp.375-382
• /
• 2014

In many practical active noise control applications, the primary noise contains multiple closely-spaced harmonics. A narrowband ANC system consists of adaptive filters excited by a composite reference signal, which is the set or sum of sinusoids. This paper analyzes and shows that the convergence speeds of the direct form, parallel form, and simplified parallel form narrowband ANC systems are affected by the fundamental frequency and frequency separation between two adjacent sinusoids in the reference signal. This paper also proposes the new simplified parallel form narrowband ANC system whose convergence speed is independent on the frequency of the reference signal. Computer simulations are conducted to verify the analysis presented in the paper and to compare the proposed narrowband ANC system with the conventional narrowband ANC system.

• Journal of Power Electronics
• /
• v.15 no.3
• /
• pp.730-740
• /
• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

• Smart Structures and Systems
• /
• v.15 no.1
• /
• pp.227-244
• /
• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• International Journal of Aeronautical and Space Sciences
• /
• v.13 no.4
• /
• pp.491-498
• /
• 2012

A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft's precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.