• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1157-1163
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• 1992

The development of adaptive control algorithms for possibly nonminimum phase systems has been hampered by singularities that may arise in the control law. To solve this problem, one securing convergence of the estimates to their true values by inducing persistency of excitation in the plant signals using direct adaptive control method and indirect adaptive control method, and another in which the estimates are adequately modified to meet the controllability requirements using indirect adaptive control method, without persistency of excitation. This paper presents an adaptive scheme that achieves regulation without persistent excitation condition using direct adaptive control method and reduces estimation algorithms with direct estimation of controller parameters without estimation of plant parameters.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.226-249
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• 2016

The symbiotic organisms search (SOS) algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.97-107
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• 2011

This paper describes efficient flight control algorithms for building a reconfigurable ad-hoc wireless sensor networks between nodes on the ground and airborne nodes mounted on autonomous vehicles to increase the operational range of an aerial robot or the communication connectivity. Two autonomous flight control algorithms based on adaptive gradient climbing approach are developed to steer the aerial vehicles to reach optimal locations for the maximum communication throughputs in the airborne sensor networks. The first autonomous vehicle control algorithm is presented for seeking the source of a scalar signal by directly using the extremum-seeking based forward surge control approach with no position information of the aerial vehicle. The second flight control algorithm is developed with the angular rate command by integrating an adaptive gradient climbing technique which uses an on-line gradient estimator to identify the derivative of a performance cost function. They incorporate the network performance into the feedback path to mitigate interference and noise. A communication propagation model is used to predict the link quality of the communication connectivity between distributed nodes. Simulation study is conducted to evaluate the effectiveness of the proposed reconfigurable airborne wireless networking control algorithms.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.245-250
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• 2009

In communications and signal processing area, a number of least mean square adaptive algorithms have been used because of simplicity and robustness. However the LMS algorithm is known to have slow and non-uniform convergence. Various variable step size LMS adaptive algorithms have been introduced and researched to speed up the convergence rate. A variable step size LMS algorithm using the error difference for updating the step size is proposed. Compared with other algorithms, simulation results show that the proposed LMS algorithm has a fast convergence. The theoretical performance of the proposed algorithm is also analyzed for the steady state.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.32-43
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• 1994

This paper presents new QRD-based recursive least squares algorithms for bilinear lattice filter. Bilinear recursive least square lattice algorithms are derived by using the QR decomposition for minimization covariance matrix of predication error by applying Givens rotation to the bilinear recursive least squares lattics algorithms. The proposed algorithms are applied to the bilinear system identification to evaluate the performance of algoithms. Computer simulations show that the convergence properties of the proposed algorithms are superior to that of the algorithms proposed by Baik when signal includes the measurement noise.

• ETRI Journal
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• v.4 no.3
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• pp.18-29
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• 1982

In a block adaptive filtering procedure, the filter coefficients are adjusted once per each output block while maintaining performance comparable to that of widely used LMS adaptive filtering in which the filter coefficients are adjusted once per each output data sample. An efficient implementation of block adaptive filter is possible by means of discrete transform technique which has cyclic convolution property and fast algorithms. In this paper, the block adaptive filtering using Fermat Number Transform (FNT) is investigated to exploit the computational efficiency and less quantization effect on the performance compared with finite precision FFT realization. And this has been verified by computer simulation for several applications including adaptive channel equalizer and system identification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3647-3653
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• 2012

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.3
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• pp.259-269
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• 1991

In this paper, power line harmonic noise which is the most serious problem in the secondary power distribution line is eliminated and analyzed using adaptive noise cancellers with two adaptive algorithms, LMS and individual tap LMS(ITLMS) algorithm. To testify the improvement of data transmission characteristics made by the adaptive filter with two adaptive algorithms, BER was measured in DS spread spectrum communication system including the noise canceller.