• Smart Structures and Systems
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• v.22 no.5
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• pp.547-560
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• 2018

This paper investigates the operation of the $H_{\infty}$ static output-feedback controller to reduce dynamic responses under seismic excitation on the five-story and benchmark 20 story building with parametric uncertainties. Linear matrix inequality (LMI) control theory is applied in this system and then to achieve the desired LMI formulations, some transformations of the LMI variables is used. Conversely uncertainties due to material properties, environmental loads such as earthquake and wind hazards make the uncertain system. This problem and its effects are studied in this research. Also to decrease the transition of large amount of data between sensors and controller, avoiding the disruption of whole control system and economy problems, the operation of the decentralized controllers is investigated in this paper. For this purpose the comparison between the performance of the centralized, fully decentralized and partial decentralized controllers in uncoupled and coupled cases is performed. Also, the effect of the changing the number of stories in substructures is considered. Based on the numerical results, the used control algorithm is very robust against the parametric uncertainties and structural responses are decreased considerably in all the control cases but partial decentralized controller in coupled form gets the closest results to the centralized case. The results indicate the high applicability of the used control algorithm in the tall shear buildings to reduce the structural responses and its robustness against the uncertainties.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.6
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• pp.669-676
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• 2008

The adaptive resource optimization problem in multi-input multi-output orthogonal frequency division multiple access (MIMO-OFDMA) systems is addressed. This paper, adaptive modulation and coding(AMC) and power control algorithms is proposed with SFC(Space-Frequency Coding), which aims to maximize the system capacity based on the CQI(Channel Quality Information). Firstly, power level is decided to each sub-channels with received feedback signal to noise ratio(SNR). In the second step, sub-carriers are allocated according to modulation type. Simulation results show that the proposed algorithm achieves a better performance than conventional algorithm in terms of capacity.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.78-83
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• 2011

Traditional autopilot design requires an accurate aerodynamic model and relies on a gain schedule to account for system nonlinearities. This paper presents the control architecture applied to a dynamic model inversion at a single flight condition with an on-line neural network (NN) in order to regulate errors caused by approximate inversion. This eliminates the need for an extensive design process and accurate aerodynamic data. The simulation results using a developed full nonlinear 6 degree of freedom model are presented. This paper also presents the stability evaluation for control systems to which NNs were applied. Although feedback can accommodate uncertainty to meet system performance specifications, uncertainty can also affect the stability of the control system. The importance of robustness has long been recognized and stability margins were developed to quantify it. However, the traditional stability margin techniques based on linear control theory can not be applied to control systems upon which a representative non-linear control method, such as NNs, has been applied. This paper presents an alternative stability margin technique for NNs applied to control systems based on the system responses to an inserted gain multiplier or time delay element.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1629-1638
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• 2016

Differential power processing (DPP) systems are among the most effective architectures for photovoltaic (PV) power systems because they are highly efficient as a result of their distributed local maximum power point tracking ability, which allows the fractional processing of the total generated power. However, DPP systems require a high-efficiency, high step-up/down bidirectional converter with broad operating ranges and galvanic isolation. This study proposes a single, magnetic, high-efficiency, high step-up/down bidirectional DC-DC converter. The proposed converter is composed of a bidirectional flyback and a bidirectional isolated switched-capacitor cell, which are competitively cheap. The output terminals of the flyback converter and switched-capacitor cell are connected in series to obtain the voltage step-up. In the reverse power flow, the converter reciprocally operates with high efficiency across a broad operating range because it uses hard switching instead of soft switching. The proposed topology achieves a genuine on-off interleaved energy transfer at the transformer core and windings, thus providing an excellent utilization ratio. The dynamic characteristics of the converter are analyzed for the controller design. Finally, a 240 W hardware prototype is constructed to demonstrate the operation of the bidirectional converter under a current feedback control loop. To improve the efficiency of a PV system, the maximum power point tracking method is applied to the proposed converter.

• Journal of KSNVE
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• v.10 no.6
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• pp.1048-1058
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• 2000

Thipaper presents a methodology to suppress the vibration of thin rectangular plate clamped all edges using piezo-ceramic material as actuators and sensors. Dynamic characteristics of the structure bonded with distributed actuators/sensors are identified by the Multi-Input Multi-Output (MIMO) frequency domain modeling technique based on the experimental data. Hybrid control scheme is adopted and feedback controller is designed by LQG(Linear Quadratic Gaussian). Feedforward controller is adapted by multiple filtered -$x$ LMS(least mean square) algorithm. Experiment result demonstrates the effective reduction of the vibration label for both the transient and persistent external disturbances.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.1
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• pp.84-92
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• 2000

A GaAs MESFET MMIC transmitter for 2.4 GHz wireless local loop handset is designed and fabricated. The transmitter consists of a double balanced active mixer and a two stage driver amplifier with voltage negative feedback. In particular, a pair of CS-CG(common source-common gate) structure compensates the reduction in dynamic range caused by unbalanced complementary IF input signals. And to suppress the leakage local power at RF port, the mixer is designed by using phase characteristic between the ports of MESFET. At the bias condition of 2.7 V and 55.2 mA, the fabricated MMIC transmitter with chip dimensions of $0.75\times1.75 mm^2$ obtains a measured conversion gain of 38.6 dB, output $P_{idB}$ of 11.6 dBm, and IMD3 at -5 dBm RF output power of -31.3 dBc. This transmitter is well suited for WLL handset.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.632-639
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• 2018

This paper presents a single antenna radar sensor with a Ku-band radar transceiver IC realized by 130 nm CMOS processes. In this radar receiver, sensitivity time control using a DC offset cancellation feedback loop is employed to achieve a constant SNR, irrespective of distance. In addition, the receiver RF block has gain control to adjust high dynamic range. The RF output power is 9 dBm and the full chain gain of the Rx is 82 dB. To reduce the direct-coupled Tx signal to the Rx in a single antenna radar, a stub-tuned hybrid coupler is adopted instead of a bulky circulator. The maximum measured distance between the horn antenna and a metal plate target is 6 m.

• Journal of Power Electronics
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• v.5 no.2
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• Journal of Power Electronics
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• v.14 no.1
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• pp.175-182
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• 2014

Tracking harmonic current quickly and precisely is one of the keys to designing active power filters (APF). In the past, the current state feedback decoupling PI control was an effective means for three-phase systems in the current control of constant voltage constant frequency inverters and high frequency PWM reversible rectifiers. This paper analyzes in detail the limitation of the conventional PI conditioner in the APF application field and presents a novel PI control method. Canceling the delay of one sampling period and the misadjustment for tracking the harmonic current is the key problem of this PI control. In this PI control, the predictive output current value is obtained by a state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by a repetitive predictor synchronously. The repetitive predictor can achieve better predictions of the harmonic current. By this means, the misadjustment of the conventional PI control for tracking the harmonic current is cancelled. The experiment results with a three-level NPC APF indicate that the steady-state accuracy and dynamic response of this method are satisfying when the proposed control scheme is implemented.