• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4872-4891
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• 2015

Orthogonal frequency division multiplexing (OFDM) signals suffer from the problem of high peak-to-average power ratio (PAPR), which complicates the design of analog front-end of the system. Companding is a well-known PAPR reduction technique that involves transforming signal amplitudes using a deterministic function. OFDM signal amplitude, on average, is Rayleigh distributed but the distribution can vary significantly from symbol to symbol, especially when constellation size increases. In this paper, a new adaptive companding scheme is proposed along with its design methodology aiming at optimizing the compander performance by accommodating this variation in its design. This is achieved by designing compander parameters separately for statistically dissimilar symbols in OFDM waveform and making the compander select from these parameters, during run-time, according to the features of input symbols.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1763-1770
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• 2000

A finite element interface system for the design of optimal spot welding locations has been developed. In order to find out the optimal locations of spot welding points, iterative finite element an alyses are necessary, and thus automatic generation of finite element model for the structures with spot welded pointsis required. In this interface system, quadrilateral shell elements are automatically generated for finite element analysis of spot welded structured, which employs a domain decomposition methodand adaptive mesh(h-method).

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.236-236
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• 2000

Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.25-28
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• 1987

Design procedure of adaptive controller with variable load condition is present and applied to velocity control of small, permanent magnet DC servo motor. The state feedback control scheme is adopted and Recursive Least Squares algorithm is used for parameter estimation. In order to reduce the time consuming. In the procedure of adaptation-gain tuning of state feedback controller, approximate curve fitting technique is applied to the relations between load condition and poles of the system, load condition and feedback gains. With this method, fast adaptation can be accomplished. It is shown that this procedure can be applied not only to variable load condition but also to variation of other system constants, for example variation of resistance and inductance etc.. Simulation results is present for both cases - variable inertia load, variable motor resistance to verify performance improvements. This design procedure produces an adaptive con troller which is feasible for implementation with microprocessor by reducing calculation time.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.231-234
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• 1993

This paper deals with the design of an adaptive controller using neural network. We present RBFMLP Neural Network which consists of serial-connected two networks - Radial Basis Function Network and Multi Layer Perceptron, and then design a controller based on proposed networks with the adaptive control system structure, The plant and parameters of the controller are identified by the neural networks. We use the dynamic backpropagation algorithm for the learning of networks. Simulations represent the superiorities of the proposed network and the controller.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.561-581
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• 2017

Bayesian statistics can play a key role in the design and analysis of clinical trials and this has been demonstrated for medical device trials. By 1995 Bayesian statistics had been well developed and the revolution in computing powers and Markov chain Monte Carlo development made calculation of posterior distributions within computational reach. The Food and Drug Administration (FDA) initiative of Bayesian statistics in medical device clinical trials, which began almost 20 years ago, is reviewed in detail along with some of the key decisions that were made along the way. Both Bayesian hierarchical modeling using data from previous studies and Bayesian adaptive designs, usually with a non-informative prior, are discussed. The leveraging of prior study data has been accomplished through Bayesian hierarchical modeling. An enormous advantage of Bayesian adaptive designs is achieved when it is accompanied by modeling of the primary endpoint to produce the predictive posterior distribution. Simulations are crucial to providing the operating characteristics of the Bayesian design, especially for a complex adaptive design. The 2010 FDA Bayesian guidance for medical device trials addressed both approaches as well as exchangeability, Type I error, and sample size. Treatment response adaptive randomization using the famous extracorporeal membrane oxygenation example is discussed. An interesting real example of a Bayesian analysis using a failed trial with an interesting subgroup as prior information is presented. The implications of the likelihood principle are considered. A recent exciting area using Bayesian hierarchical modeling has been the pediatric extrapolation using adult data in clinical trials. Historical control information from previous trials is an underused area that lends itself easily to Bayesian methods. The future including recent trends, decision theoretic trials, Bayesian benefit-risk, virtual patients, and the appalling lack of penetration of Bayesian clinical trials in the medical literature are discussed.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.73-81
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• 2007

To improve the capability of instantaneous torque control, a design method of an MRAC-based adaptive current controller for a PMSM servo motor is proposed. In the synchronous frame current controller, a new control inputs can be obtained through the decoupling compensation. Using this, a desired controller bandwidth can be assigned However, the control performance may be degraded due to disturbances caused by the parameter variations or dead time of the switch. To improve these drawbacks, an adaptive current controller is proposed and the design method is obtained using the hyperstability theory. The asymptotic stability is proved and the effectiveness is verified through simulations and experiments using DSP TMS320C31.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1596-1600
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• 2000

We propose a novel adaptive feed forward controller (AFC) design method for rejecting the effect of micro actuator resonance in the design of dual-stage actuator servo systems for disk drives. Microactuator's resonance is one of important issues in dual-stage actuator servo, which varies up to ${\pm}10%$ per product and even during operation. We derive an adaptive algorithm for the proposed AFC design, which turns out to be identical to the delayed-x LMS algorithm which is a special form of the filtered-x LMS algorithm. In the algorithm, coefficients of the AFC are adapted by the residuals of constrained structure defined in such a way that the coefficients become time invariant. Contrary to the conventional AFC, it considers the phase delay of closed-loop transfer function at resonance frequency for system stability. We also apply an adaptive algorithm with frequency tracking capability. The frequency tracking algorithm is induced by the orthogonality of AFC coefficients. Computer simulations are carried out to demonstrate effect of the proposed AFCs.