• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5305-5321
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• 2016

In wireless communication, the multiple-input multiple-output (MIMO) system is a well-known approach to improve the reliability as well as the data rate. In MIMO systems, channel state information (CSI) is typically required at the receiver to detect transmitted signals; however, in practical systems, the CSI is imperfect and contains errors, which affect the overall system performance. In this paper, we propose a novel maximum likelihood (ML) scheme for MIMO systems that is robust to the CSI errors. We apply an optimization method to estimate an instantaneous covariance matrix of the CSI errors in order to improve the detection performance. Furthermore, we propose the employment of the list sphere decoding (LSD) scheme to reduce the computational complexity, which is capable of efficiently finding a reduced set of the candidate symbol vectors for the computation of the covariance matrix of the CSI errors. An iterative detection scheme is also proposed to further improve the detection performance.

• Smart Structures and Systems
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• v.24 no.3
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• pp.293-301
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• 2019

Bolted joints are commonly used in civil infrastructure and mechanical assembly structures. Monitoring and identifying the connection status of bolts is the frontier problem of structural research. The existing research is mainly on the looseness of a single bolt. This article presents a study of assessing the loosening/tightening health state and identifying the loose bolt by using ultrasonic guided wave in a bolt group joint. A bolt-tightening index was proposed for evaluating the looseness of a bolt connection based on correlation coefficient. The tightening/loosening state of the bolt was simulated by changing the bolt torque. More than 180 different measurement tests for total of six bolts were conducted. The results showed that with the bolt torque increases, value of the proposed bolt-tightening index increases. The proposed bolt-tightening index trend was very well reproduced by an analytical expression using a function of the torque applied with an overall percentage error lower than 5%. The developed damage index based on the proposed bolt-tightening index can also be applied to locate the loosest bolt in a bolt group joint. To verify the effectiveness of the proposed method, a bolt group joint experiment with different positions of bolt looseness was performed. Experimental results show that the proposed approach is effective to detect and locate bolt looseness and has a good prospect of finding applications in real-time structural monitoring.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.1-15
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• 2007

Consider a Rayleigh distribution with $$pdf\;p(x/{\theta})\;=\;2x{\theta}^{-1}\;{\exp}\;({-x^2}/{\theta})$$ and mean lifetime ${\mu}\;=\;\sqrt{\pi\theta}/2$. We study the two-action problem of testing the hypotheses $H_{0}\;:\;{\mu}{\leq}{\mu}_{0}$ against $H_{1}\;:\;{\mu}\;>\;{\mu}_{0}$ using a linear error loss of ${\mid}{\mu}\;-\;{\mu}_{0}{\mid}$ via the empirical Bayes approach. We construct a monotone empirical Bayes test ${\delta}^{*}_{n}$ and study its associated asymptotic optimality. It is shown that the regret of ${\delta}^{*}_{n}$ converges to zero at a rate $\frac{{\ln}^{2}n}{n}$, where n is the number of past data available when the present testing problem is considered.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.731-737
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• 2013

In this paper, we propose an image-based output feedback robust controller of robot manipulators which have bounded parametric uncertainty. The proposed controller contains an integral action and high-gain observer in order to improve steady state error of joint position and performance deterioration due to measurement errors of joint velocity. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by simulations on a 5-link robot manipulators with two degrees of freedom.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.54-67
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• 2003

In this paper, a novel estimation technique for a robust adaptive control scheme is presented for a class of uncertain nonlinear systems with a general set of uncertainty. For a class of introduced more extended semi-strict feedback forms which generalize the systems studied in recent years, a novel estimation technique is proposed to estimate the states of the fully nonlinear unmodeled dynamics without stringent conditions. With the introduction of powerful functions, the estimation error can be tuned to a desired small region around the origin via the estimator parameters. In addition, with some effective functions, a modified adaptive backstepping for dynamic uncertainties is presented to drive the output to an arbitrarily small region around the origin by an appropriate choice of the design parameters. With our proposed schemes, we can remove or relax the assumptions of the existing results.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1577-1583
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• 2015

In this research, a combined adaptive-robust current controller is developed for non-minimum-phase DC-DC converters in a wide range of operations. In the proposed nonlinear controller, load resistance, input voltage and zero interval of the inductor current are estimated using developed adaptation rules and knowing the operating mode of the converter for the closed-loop control is not required; hence, a single controller can be employed for a wide load and line changes in discontinuous and continuous conduction operations. Using the TMS320F2810 digital signal processor, the experimental response of the proposed controller is presented in different operating points of the buck/boost converter. During transition between different modes of the converter, the developed controller has a better dynamic response compared with previously reported adaptive nonlinear approach. Moreover, output voltage steady-state error is zero in different conditions.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.886-891
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• 1987

In this paper, we present a effective method to control robotic systems by an iterative learning algorithm. This method is based on the concepts of the learning control law which is introduced in this paper, that is, avoidance of using derivative of system state and ignorance of high frequency influence in system performance. By means of the betterment of performance due to the improvement of estimated unknown information, the learning control algorithm compels the system to gradually approach in desired trajectory, and eventually the tracking error asymptotically converges upon zero. In order to verify its utility, one degree of freedom of manipulator has been used in the experiments and the results illustrate this control scheme is very effective.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1492-1495
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• 2005

This paper presents a new linear-matrix-inequality-based intelligent digital redesign (LMI-based IDR) technique to match the states of the analog and the digital T-S fuzzy control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the affine control scheme is employed to increase the degree of freedom; 2) the fuzzy-model-based periodic control is employed; and the control input is changed n times during one sampling period; 3) The proposed IDR technique is based on the approximately discretized version of the T-S fuzzy system; but its discretization error vanishes as n approaches the infinity. 4) some sufficient conditions involved in the state matching and the stability of the closed-loop discrete-time system can be formulated in the LMIs format.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1393-1405
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• 2017

It is well known that duty-cycling control by dynamically adjusting the polling interval according to the traffic loads can effectively achieve power saving in wireless sensor networks. Thus, there has been a significant research effort in developing polling interval adaptation schemes. Especially, Dynamic Low Power Listening (DLPL) scheme is one of the most widely adopted open-looping polling interval adaptation techniques in wireless sensor networks. In DLPL scheme, if consecutive idle (busy) samplings reach a given fixed threshold, the polling interval is increased (decreased). However, due to the trial-and-error based approach, it may significantly deteriorate the system performance depending on given threshold parameters. In this paper, we propose a novel DLPL scheme, called SDL (Sequential hypothesis testing based Dynamic LPL), which employs sequential hypothesis testing to decide whether to change the polling interval conforming to various traffic conditions. Simulation results show that SDL achieves substantial power saving over state-of-the-art DLPL schemes.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.411-414
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• 1989

In this paper, design of the regulator and model following is studied controller on servomechanism for discrete time system. The design of the servomechanism controller is studied on the method of mode1 following controller for the output of the process to follow the output of its model. Furthermore, a common approach to eliminate disturbance and steady-state error between the outputs of the process and its model is to introduce an integrator into the control loop itself. They are eliminated when we incorporate the integrator into the closed loop system.