• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1280-1286
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• 2004

A lot of industrial chemical processes contain certain input nonlinearities even though they are controlled by several linear controllers. Here we investigate a sequential loop closing identification method for MIMO Hammerstein nonlinear processes with diagonal nonlinearities. The proposed method separates the identification of the nonlinear static function from that of the linear subsystem by using a relay feedback test and a triangular type signal test. From 2 n activations for n n MIMO nonlinear processes, we sequentially identify the whole range of the nonlinear static function as well as the transfer function matrix of the linear subsystem.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.19-27
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• 2003

It is well known that one can easily design a high-gain adaptive output feedback control for a class of nonlinear systems which satisfy a certain condition called output feedback exponential passivity (OFEP). The designed high-gain adaptive controller has simple structure and high robustness with regard to bounded disturbances and unknown order of the controlled system. However, from the viewpoint of practical application, it is important to consider a robust control scheme for controlled systems for which some of the assumptions of output feedback stabilization are not valid. In this paper, we design a robust high-gain adaptive output feedback control for the OFEP nonlinear systems with uncertain nonlinearities and/or disturbances. The effectiveness of the proposed method is shown by numerical simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.581-586
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• 2003

This paper presents control designs using neural networks (NN) for a XY positioning table. The proposed neurocontroller is composed of an outer PD tracking loop for stabilization of the fast flexible-mode dynamics and an NN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NN weights, so that the NN compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded weight estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The proposed neuro-controller is implemented and tested on an IBM PC-based XY positioning table, and is applicable to many precision XY tables. The algorithm, simulation, and experimental results are described. The experimental results are shown to be superior to those of conventional control.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.16-25
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• 1994

The major reason that reduces the performance of satellite communication channels is known as the nonlinearities of high power amplifiers(HPA's) which are usually modeled by memoryless nonlinear systems, in the channels. This paper proposes a nonlinear adaptive predistorter,which predistorts the input symbols such that the symbol passing through the nonlinear HPA preserves the desired constellation, and derives the region of convergence for the predistorter. The predistorter has capability of coping adaptively with any time-varying environment such as changes of operating points if HPA since the coefficients of the predistorter which has a form of truncated Tayler series are obtained by recursive optimization procedure utilizing QAM data sequence directely. Simulation results show that the proposed one with 16 QAM input has better performance than the conventional fixed predistorter with the same input.

• Journal of KSNVE
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• v.4 no.3
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• pp.307-318
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• 1994

Existence of any nonlinearity in responses of a nonlinear system is tested using a kurtosis or a fourth moment which has been widely used to characterize signal patterns. By inputting a harmonic signal to a system and investigating the distortions of an output signal from a harmonic pattern, which are due to violations of proportionality between the input and the output, it is judged whether the output is generated from a nonlinear system or not. Through applying the method presented in this work to simulation studies on detections of nonlinearities of a single degree of freedom system, in which three kinds of nonlinearities are treated as restoring force terms, feasibilities of the method are shown and the range of both frequency and input amplitude, in which the system generates nonlinear responses, is determined.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.72-81
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• 2000

In this paper, we design an adaptive neuro-fuzzy inference system(ANFIS) precompensator for load frequency control of 2-area power systems. While proportional integral derivative (PID) controllers are used in power systems, they may have some problems because of high nonlinearities of the power systems. So, a neuro-fuzzy-based precompensation scheme is incorporated with a convectional PID controller to obtain robustness to the nonlinearities. The proposed precompensation technique can be easily implemented by adding a precompensator to an existing PID controller. The applied neruo-fuzzy inference system precompensator uses a hybrid learning algorithm. This algorithm is to use both a gradient descent method to optimize the premise parameters and a least squares method to solve for the consequent parameters. Simulation results show that the proposed control technique is superior to a conventional Ziegler-Nichols PID controller in dynamic responses about load disturbances.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.10
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• pp.808-815
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• 2002

The nonlinear characteristics for hinge of a deployable missile control fin are investigated experimentally. The nonlinearity is caused by a worn or loose hinge and manufacturing tolerance and cannot be eliminated completely. The structural nonlinearity has an effect on the static and dynamic characteristics of the control fin. Therefore, it is necessary to establish the accurate nonlinear model for the hinge of the control fin. In the present study the existence of nonlinearities in the hinge is confirmed from the frequency response experiments such as tip random excitation and base sine sweep. Using the system identification method. especially, ″Force-state Mapping Technique″, the types of nonlinearities are identified and the nonlinear hinge model of the control fin is established.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.261-265
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• 2014

This paper studies the problem of the sampled-data control for Lur'e system with nonlinearities. The nonlinearities are expressed as convex combinations of sector and slope bounds. It is assumed that the sampling periods are arbitrarily varying but bounded. By constructing a new augmented Lyapunov-Krasovskii functional which have an augmented quadratic form with states as well as the nonlinear function, the stabilizing sampled-data controller gains are obtained by solving a set of linear matrix inequalities. The effectiveness of the developed method is demonstrated by numerical simulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.278-285
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• 1999

This paper is concerned with the development of useful engineering techniques to detect and anlayse nonlinearities in mechanical systems. The methods developed are based on the concepts of higher order spectra. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment(skewness) of a quadratic phase coupling(QPC) can be analyzed by bicoherence function. Finally, the application of these techiques to data from actual mechanical systems will be performed insecond report.

• Journal of the Korean Mathematical Society
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• v.57 no.6
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• pp.1551-1571
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• 2020

This paper is concerned with the following Kirchhoff-Schrödinger-Poisson system $$\begin{cases} -(a+b{\displaystyle\smashmargin{2}\int\nolimits_{\mathbb{R}^3}}{\mid}{\nabla}u{\mid}^2dx){\Delta}u+V(x)u+{\mu}{\phi}u={\lambda}f(x){\mid}u{\mid}^{p-2}u+g(x){\mid}u{\mid}^{p-2}u,&{\text{ in }}{\mathbb{R}}^3,\\-{\Delta}{\phi}={\mu}{\mid}u{\mid}^2,&{\text{ in }}{\mathbb{R}}^3, \end{cases}$$ where a > 0, b, µ ≥ 0, p ∈ (1, 2), q ∈ [4, 6) and λ > 0 is a parameter. Under some suitable assumptions on V (x), f(x) and g(x), we prove that the above system has at least two different nontrivial solutions via the Ekeland's variational principle and the Mountain Pass Theorem in critical point theory. Some recent results from the literature are improved and extended.