• ETRI Journal
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• v.41 no.4
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• pp.426-436
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• 2019

In time division duplex (TDD)-based multiuser massive multiple input multiple output (MIMO) systems, the uplink channel is estimated and the results are used in downlink for signal detection. Owing to noisy uplink channel estimation, the downlink channel should also be estimated for accurate signal detection. Therefore, recently, a blind method was developed, which assumes the use of a linear high-power amplifier (HPA) in the base station (BS). In this study, we extend this method to a scenario with a nonlinear HPA in the BS, where the Bussgang decomposition is used for HPA modeling. In the proposed method, the average power of the received signal for each user is a function of channel gain, large-scale fading, and nonlinear distortion variance. Therefore, the channel gain is estimated, which is required for signal detection. The performance of the proposed method is analyzed theoretically. The simulation results show superior performance of the proposed method compared to that of the other methods in the literature.

• Advances in aircraft and spacecraft science
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• v.8 no.4
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• pp.273-287
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• 2021

Model-based, data-driven and physics-based approaches represent the state-of-the-art techniques to estimate the aircraft flow angles, angle-of-attack and angle-of-sideslip, in avionics. Thanks to sensor fusion techniques, a synthetic sensor is able to provide estimation of flow angles without any dedicated physical sensors. The work deals with a physics-based scheme derived from flight mechanic theory that leads to a nonlinear flow angle model. Even though several solvers can be adopted, nonlinear models can be replaced with less accurate but straightforward ones in practical applications. The present work proposes a linearisation to obtain the flow angles' closed form solution that is verified using a flight simulator. The main objective of the paper, in fact, is to analyse the estimation degradation using the proposed closed form solutions with respect to the nonlinear scheme. Moreover, flight conditions, where the proposed closed form solutions are not applicable, are identified.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.37.2-37
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• 2001

This paper addresses the robust adaptive output feedback tracking for nonlinear systems under disturbances whose bounds are unknown. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The State estimation is solved using K-filters, together with the construction of a bound of an error in the state estimation due to the perturbation of the disturbance. Tuning functions are used to estimate unknown system parameters without overparametrization. The proposed control algorithm ensures that the out put tracking error converges to a residual set which can be arbitrarily small, while maintaining the boundedness of all other variables. A simulation shows the effectiveness of the proposed approach

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.75-86
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• 1999

An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.96-102
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• 1999

Sensorless speed estimation in induction motor systems is one of the most control engineers. Based on the estimated speed the vector control has been applied to the high precision torque control however most speed estimation methods use adaptive scheme so that it takes long time to estimate the speed. Thus the adaptive estimation scheme is not effective to the induction motor which requires short sampling time. In this paper a new linearized equation of induction motor system is proposed and a sensorless speed estimation algorithm based on observation techniques is developed. First the nonlinear induction motor equation is linearized at an equilibrium point. Second a proportional integral(PI) observer is applied to estimate the speed state in the induction motor system. Finally simulation results will assure the effectiveness of the new linearized equation and the sensorless estimation algorithm by using PI observer in the nonlinear induction motor system.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.153-162
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• 1998

It is needless to say that the nonlinear hemodynamic variables estimation is a very important study for the artificial heart. Even though it is important, there have not been satisfactory results which can be applied to the real world situations, In this paper, the problem of hemodynamic variables estimation for the moving-actuator type total artificial heart(MA-TAH) was studed. Multidimensional linear interpolation(MDI)scheme was used for the estimation. Proposed method was verified by in vitro test and showed good performance.

• Structural Engineering and Mechanics
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• v.32 no.3
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• pp.383-398
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• 2009

Applying nonlinear statistical analysis methods in estimating the performance of structures in earthquakes is strongly considered these days. This is due to the methods' simplicity, timely lower cost and reliable estimation in seismic responses in comparison with time-history nonlinear dynamic analysis. Among nonlinear methods, simplified to be incorporated in the future guidelines, Modal Pushover Analysis, known by the abbreviated name of MPA, simply models nonlinear behavior of structures; and presents a very proper estimation of nonlinear dynamic analysis using lateral load pattern appropriate to the mass. Mostly, two kinds of connecting joints, 'hinge' and 'rigid', are carried out in different type of steel structures. However, it should be highly considered that nominal hinge joints usually experience some percentages of fixity and nominal rigid connections do not employ totally rigid. Therefore, concerning the importance of these structures and the significant flexibility effect of connections on force distribution and elements deformation, these connections can be considered as semi-rigid with various percentages of fixity. Since it seems, the application and implementation of MPA method has not been studied on moment-resistant steel frames with semi rigid connections, this research focuses on this topic and issue. In this regard several rigid and semi-rigid steel bending frames with different percentages of fixity are selected. The structural design is performed based on weak beam and strong column. Followed by that, the MPA method is used as an approximated method and Nonlinear Response History Analysis (NL-RHA) as the exact one. Studying the performance of semi-rigid frames in height shows that MPA technique offers reasonably reliable results in these frames. The methods accuracy seems to decrease, when the number of stories increases and does decrease in correlation with the semi-rigidity percentages. This generally implies that the method can be used as a proper device in seismic estimation of different types of low and mid-rise buildings with semi-rigid connections.

• Smart Structures and Systems
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• v.22 no.3
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• pp.315-326
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• 2018

This paper presents a novel time-domain method for the identification of plastic rotations and stiffness parameters of single-bay frames with nonlinear plastic hinges. Each plastic hinge is modelled as a pseudo-semi-rigid connection with nonlinear hysteretic moment-curvature characteristics at an element end. Through the comparison of the identified end rotations of members that are connected together, the plastic rotation that furnishes information of the locations and plasticity degrees of plastic hinges can be identified. The force consideration of the frame members may be used to relate the stiffness parameters to the elastic rotations and the excitation. The damped-least-squares method and damped-and-weighted-least-squares method are adopted to estimate the stiffness parameters of frames. A noise-removal strategy employing a de-noising technique based on wavelet packets with a smoothing process is used to filter out the noise for the parameter estimation. The numerical examples show that the proposed method can identify the plastic rotations and the stiffness parameters using measurements with reasonable level of noise. The unknown excitation can also be estimated with acceptable accuracy. The advantages and disadvantages of both parameter estimation methods are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.807-810
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• 2015

In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.