• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.735-742
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• 2010

In this paper, we propose adaptive algorithms for interference cancellation in RF repeaters with multiple transmit and receive antennas. When multiple antennas are used in a repeater, the imperfect isolation between transmit and receive antennas causes the feedback interference which is modeled as multi-input multi-output (MIMO) channel. To remove the feedback interference, we derive the least mean square (LMS) algorithm and the recursive least squares (RLS) algorithm for interference cancellation based on adaptive signal processing techniques. Through computer simulations for the proposed algorithms, we analyze the convergence characteristics and compare the steady-state performance for interference cancellation.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.269-277
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• 2008

This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

• Journal of Ocean Engineering and Technology
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• v.22 no.3
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• pp.34-40
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• 2008

his study discusses the design of an automatic berthing control algorithm for ships with a haw thruster and a stern thruster, as well as a rudder. A nonlinear mathematical model for the law speed maneuvering of ships was used to design a MIMO (multi-input multi-output) nonlinear control algorithm. The algorithm consists of two parts, the forward velocity control and heading angle control. The control algorithm was designed based on the longitudinal and yaw dynamic models of ships. The desired heading angle was obtained by the so-called "Line of Sight" method. An optimal control force allocation method forthe rudder and the thrusters is suggested. The nonlinear control algorithm was tested by numerical simulations using MATLAB, and showed good tracking performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6269-6273
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• 2015

Performance of the Alamouti algorithm based M-ary $2{\times}N$ OSTBC(Orthogonal Space Time Block Coded) MIMO(Multi Input Multi Output) system has been simulated varying two main parameters - the number of constellation(M), and the number of receiving antennas(N). Computer simulation has also been carried out using Matlab software for performance comparison between $2{\times}N$ MIMO and MRC(Maximal Ratio Combining) diversity antenna system to evaluate the degree of enhancement achieved through the use of Alamouti $2{\times}N$ MIMO. Under 10 dB EbNo QPSK scenario, $2{\times}1$ MIMO brought 4.2 dB BER improvement over single antenna system and $2{\times}2$ MIMO resulted in 7.4 dB BER improvement over $1{\times}2$ MRC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1828-1832
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• 1991

We study the observer design problem for nonautonomous discrete-time nonlinear systems. We investigate the structure of nonautonomous discrete-time systems which are state equivalent to the nonlinear observer form and characterize their class. Necessary and sufficient conditions for the existence of an input independent (local) diffeomorphism axe derived which transforms multi-input, multi-output nonlinear systems into the nonlinear observer form.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.1-6
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• 1993

This report proposes a novel method of identification of continuous time-delay systems from sampled input-output data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of th sampling period. Then an identification method combining the common linear least squares(LS) method or the instrumental variable(IV) method with the genetic algorithm(GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output systems where the time-delays in the individual input channels may differ each other. Simulation resutls show that our method yields consistent estimates even in the presence of high measurement noises.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.619-621
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• 2005

This paper proposes apractical design method for ship-to-ship missiles' autopilot. When the pre-designed analogue autopilot is implemented in digital way, theygenerally suffer from severe performance degradation and instability problem even for a sufficiently small sampling time. Also, aerodynamic uncertainties can affect the overall stability and this happens more severely when the nonlinear autopilot is digitally implemented. In order to realize a practical autopilot, two main issues, digital implementation problem and compensation for the aerodynamic uncertainties, are considered in this paper. MIMO (multi-input multi-output) nonlinear autopilot is presented first and the input and output of the missile are discretized for implementation. In this step, the discretization effect is compensated by designing an additional control input. Finally, we design a parameter adaptation law to compensate the control performance. Stability analysis and 6-DOF (degree-of-freedom) simulations are presented to verify the proposed adaptive autopilot.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.965-974
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• 2003

In this paper we propose an incremental classification of multi-class data set by LS-SVM. By encoding the output variable in the training data set appropriately, we obtain a new specific output vectors for the training data sets. Then, online LS-SVM is applied on each newly encoded output vectors. Proposed method will enable the computation cost to be reduced and the training to be performed incrementally. With the incremental formulation of an inverse matrix, the current information and new input data are used for building another new inverse matrix for the estimation of the optimal bias and lagrange multipliers. Computational difficulties of large scale matrix inversion can be avoided. Performance of proposed method are shown via numerical studies and compared with artificial neural network.

• 전기의세계
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• v.28 no.12
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• pp.33-40
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• 1979

This mininzation of the multi-output switching function becomes a difficult task when the input varibles and the number of functions increase. This paper describes the optimal selection of prime inplicats for the multi-output switching function by using the Inter-section Table. This procedure is applicable to both manual and computhe programmed realization without complesith. The algorithm is implemented by a computer program in the standard FORTRAN iv language.