Earticle

This paper studies the problem of $H_{\infty}$ model reference tracking control for continuous time networked control systems (NCSs) with communication constraints. By using the continuous Jensen inequality, linear matrix inequality (LMI)-based $H_{\infty}$ model reference tracking controller design for nominal NCSs with controller-to-actuator communication constraints is presented, and a new method is proposed to design $H_{\infty}$ model reference tracking controllers for NCSs with both controller-to-actuator and sensor-to-controller communication constraints. The results are also extended to NCSs with norm-bounded parameter uncertainties. The merits of the proposed methods lie in their less computational complexity and less conservatism, which are achieved by adopting continuous Jensen inequality and proposing new controller design methods, respectively. The simulation results illustrate the effectiveness of the proposed $H_{\infty}$ model reference tracking controller design for NCSs with communication constraints.

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system.

In the area of tracking control, it is important to design not only the controllers but also the trajectories to which a system has to follow. $5^{th}$ order polynomial is often used with constraints of initial and final states. Smooth ending with possible minimum time is important for many systems because of vibration or jerky motions. Examples are increased with development of technology in smaller, more accurate systems. On the base of a polynomial like trajectory generation method from a paper in ACC2002 and RIC(Robust Internal-loop Compensator) control scheme of Robotics and Bio-mechanics lab. of POSTECH, generalized and expanded polynomial like trajectory generation method is showed.

A narrow loop noise bandwidth method is desirable to reduce the error of raw measurements due to the thermal noise. However, it degrades the performance of GPS initial synchronization such as mean acquisition time. And it restricts the loop noise bandwidth to a fixed value determined by the lower bound of the allowable range of carrier-to-noise power ratio, so that it is difficult to optimally track GPS signal. In order to make up for the weak points of the fixed-type narrow loop noise bandwidth method and simultaneously minimize the error of code and carrier measurements, this paper proposes a stepwise-type adaptive bandwidth algorithm for DGPS reference receivers. In this paper, it is shown that the proposed adaptive bandwidth algorithm can provide more accurate measurements than those of the fixed-type narrow loop noise bandwidth method, in view of analyzing the simulation results between two signal tracking algorithms. This paper also carries out sensitivity analysis of the proposed adaptive bandwidth algorithm due to the estimation uncertainty of carrier-to-noise power ratio. Finally the analysis results are verified by the experiment using GPS simulator.

This paper focuses on online speaker tracking for telephone conversations and broadcast news. Since the online applicability imposes some limitations on the tracking strategy, such as data insufficiency, a reliable approach should be applied to compensate for this shortage. In this framework, a set of reference speaker models are used as side information to facilitate online tracking. To improve the indexing accuracy, adaptation approaches in eigenvoice decomposition space are proposed in this paper. We believe that the eigenvoice adaptation techniques would help to embed the speaker space in the models and hence enrich the generality of the selected speaker models. Also, an index structure of the reference models is proposed to speed up the search in the model space. The proposed framework is evaluated on 2002 Rich Transcription Broadcast News and Conversational Telephone Speech corpus as well as a synthetic dataset. The indexing errors of the proposed framework on telephone conversations, broadcast news, and synthetic dataset are 8.77%, 9.36%, and 12.4%, respectively. Using the index tree structure approach, the run time of the proposed framework is improved by 22%.

A novel decision reference based method for the maximum power point tracking (MPPT) of PV arrays is presented in this paper. The proposed decision reference was derived from a simplified solar cell model. This method solves the problems of conventional MPPT algorithms, such as oscillation of the operating point at the steady state and confusion under rapidly changing insolation. It is shown by simulation and experimental results that the method properly tracks a rapidly changing insolation profile. The signal to noise ratio (SNR) of the new decision reference is also higher than those of conventional P&O and INC methods. An updating subroutine was included in the proposed MPPT algorithm to compensate for temperature and aging effects.

When size and shape of moving object have been changed, a correlator often accumulates walk-off error. A success of correlation-based tracking largely depends on choosing suitable window size and position and thus transferring the proper reference image to the next frame. For this, we propose the Adaptive Window Algorithm with Four-Direction Sizing Factors (AWA-FSF) for fast adjusting a reference region to enhance reliability of correlation-based image tracking in complex cluttered environments. Since the AWA-FSF is capable of adjusting a reference image size more rapidly and properly, we can minimize the influence of complex background and clutter. In addition, we can finely tune the center point of the reference image repeatedly after main tracking process. Thus we have increased stability and reliability of correlation-based image tracking. We tested performance of the AWA-FSF using 45 real image sequences made of over 3400 images and had the satisfied results for most of them.

In this paper, the sine reference tracing state feedback current controller for the grid-connected inverter using the pole placement technique is proposed. The proposed state feedback controller can help to design the systematic current controller by using the pole arrangement technique according to given system requirements on the AC grid voltage conditions. Therefore, the state feedback control algorithm that can track the sign input voltage is designed using the average model of the inverter, and the proposed method are verified from experimental results of the 200W scale-down two-stage photovoltaic power conversion system.

R/C helicopter has been used to several fields of military affairs, investigation searching and toys because it has small size hovering and vortical take-off characteristics etc. Therefore it needs more realizable control method. The paper introduces simulation and experimental results for control of a helicopter training simulator by self tuning control method. To realize the disturbance rejection and the given reference tracking, a least common multiple polynomial between the reference and disturbance model polynomials is operated to the plant model. The effectiveness of the method is shown by simulation and experimental results for a helicopter training simulator with two degree of freedom.

본 논문에서는 AR drone의 위치 이동 제어 문제를 고려하고자 한다. 본 제어 문제를 해결함에 있어서 제어 환경은 다음과 같은 제약조건이 존재한다. x,y,z의 공간 좌표를 측정하는 센서가 부재하며, roll, pitch의 각을 센서로 측정할 수 있다. 이러한 하드웨어적인 제약조건을 극복하기 위해서 먼저 AR drone의 움직이는 궤적에 따른 roll, pitch의 각을 역으로 계산하여 roll, pitch의 레퍼런스 각을 생성한다. 그리고, 잘 알려진 PID제어기와 슬라이딩 제어기를 사용하여 AR drone의 roll, pitch각이 레퍼런스 각을 추종하게 만든다. 그리고, 레퍼런스 궤적의 미세한 조정을 통해서 AR drone이 원하는 위치로 이동을 할 수 있게 된다. 본 논문에서 제안된 제어 기법의 유용성을 실험을 통해서 입증한다.

In this paper, we consider a positive control problem of an AR drone. The given control environment is that due to the lack of x,y,z-coordinate sensors, we can only use the sensors that measure the roll, pitch angles. To overcome this hardware disadvantage, we first develop roll and pitch reference trajectories based upon the pre-defined movement of an AR drone. Then, we utilize the well-developed PID and sliding mode controller to make an AR drone track the developed roll and pitch trajectories. Through the fine-tuning mapping process, we show that our proposed control method can move an AR drone to the desired position in the experiment.

An Inertial Measurement Unit (IMU)-based Attitude and Heading Reference System (AHRS) can calculate attitude and heading information with long-term accuracy and stability by combining gyro, accelerometer, and magnetic compass signals. Motivated by this characteristic of the AHRS, this paper presents a Motion-Tracking and Localization (MTL) method for a person or walking robot using multi-AHRSs. Five AHRSs are attached to the two calves, two thighs, and waist of a person/walking robot. Joints, links, and coordinate frames are defined on the body. The outputs of the AHRSs are integrated with link data. In addition, a supporting foot is distinguished from a moving foot. With this information, the locations of the joints on the local coordinate frame are calculated. The experimental results show that the presented MTL method can track the motion of and localize a person/walking robot with long-term accuracy in an infra-less environment.