• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.271-274
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• 1998

This paper describes a new method for separation of the Volterra kernels which are identified by use of M-sequence. One of the authors has proposed a method for identification of Volterra kernels of nonlinear systems using M-sequence and correlation technique. When M-sequence are applied to a nonlinear systems, the cross-correlation function between the input and the output of the nonlinear systems includes cross-sections of high-order Volterra kernels. However, if various order Volterra kernels exixt on the obtained cross-correlation function, it is difficult to separate the Volterra kernels. In this paper, the authors show that the magnitude of Volterra kernels is maginified by the amplitude of M-sequence according to the order of Volterra kernels. By use of this property, each order Volterra kernels is obtained by solving linear equations. Simulations are carried out for some nonlinear systems. The results show that Volterra kernels can be separated in each order successfully by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2283-2291
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• 2010

The shrinking generator which is one of clock-controlled generator is a very simple generator with good cryptographic properties. A nonlinear sequence generator based on two 90/150 maximum length cellular automata can generate pseudorandom sequences at each cell of cellular automata whose characteristic polynomials are same. The nonlinear sequence generated by cellular automata has a larger period and a higher linear complexity than shrunken sequence generated by LFSRs. In this paper we analyze shrunken-interleaved sequence based on 90/150 maximum length cellular automata. We show that the sequence generated by nonlinear sequence generator based on cellular automata belongs to the class of interleaved sequence. And we give an effective algorithm for reconstructing unknown bits of output sequence based on intercepted keystream bits.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.161-164
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• 1996

The authors have recently proposed a new method for identifying Volterra kernels of nonlinear control systems by use of M-sequence and correlation technique. A specially chosen M-sequence is added to the nonlinear system to be identified, and the crosscorrelation function between the input and output is calculated. Then every crosssection of Volterra kernels up to 3rd order appears at a specified delay time point in the crosscorrelation. This method is applied to a saturation-type nonlinear feedback control system of mechanical-electrical servo system having torque saturation nonlinearity. Simulation experiments show that we can obtain Volterra kernels of saturation-type nonlinear system, and a good agreement is observed between the observed output and the calculated one from the measured Volterra kernels.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.150-154
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• 1993

A new method is proposed for obtaining Volterra kernals of a nonlinear system by use of a nonlinear systems by use of pseudorandom M-sequences and correlation technique. M-sequence is applied to a nonlinear technique. M-sequence is applied to a nonlinear system and the crosscorrelation function between the input and the output displays not only the linear impulse response of the linear part of the system, but also crosssections of the Volterra kernals of nonlinear system. Simulations are carried out for up to 3rd order Volterra kernal, and the results show a good agreement with the theoretical considerations.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.7-12
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• 1994

This paper describes an outline of pseudorandom M-sequence and its applications to measurement and control engineering. At first, generation and properties of M-sequence is briefly described and then its applications to delay time measurement, information transmission by use of M-array, two dimensional positioning, fault detection of logical circuit, fault detection of RAM, linear and nonlinear system identification.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.221-224
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• 2005

The authors have recently developed a method for identification of Volterra kernels of nonlinear systems by using M-sequence and correlation technique. In this paper, we apply the proposed method to identification of a robot manipulator which has two degrees of freedom. From the results of the experiment, the nonlinear characteristics of the robot manipulator can be identified by the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.597-600
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• 1997

In this paper, the authors propose a new method for linearizing a nonlinear dynamical system by use of polynomial compensation. In this method, an M-sequence is applied to the nonlinear system and the crosscorrelation function between the input and the output gives us every crosssections of Volterra kernels of the nonlinear system up to 3rd order. We construct a polynomial compensation function from comparison between lst order Volterra kernel and high order kernels. The polynomial compensation function is, in this case, of third order whose coefficients are variable depending on the amplitude of the input signal. Once we can get compensation function of nonlinear system, we can construct a linearization scheme of the nonlinear system. That is. the effect of second and third order Volterra kernels are subtracted from the output, thus we obtain a sort of linearized output. The authors applied this method to a saturation-type nonlinear system by simulation, and the results show good agreement with the theoretical considerations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.149-152
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• 1996

In this paper, the authors propose a new method for linearizing a nonlinear dynamical system by use of Volterra kernel of the nonlinear system. The authors have recently obtained a new method for measuring Volterra kernels of nonlinear control systems by use of a pseudo-random M-sequence and correlation technique. In this method, an M-sequence is applied to the nonlinear system and the crosscorrelation function between the input and the output gives us every crosssection of Volterra kernels up to 3rd order. Once we can get Volterra kernels of nonlinear system, we can construct a linearization method of the nonlinear system. Simulation results show good agreement between the observed results and the theoretical considerations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.470-470
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• 2000

This paper describes a new method of identifcation of backlash nonlinear systems by use of M-sequence correlation method. In this method, we can obtain not only Volterra kernels of up to 3rd order of the nonlinear system, but also the width of the backlash element from observing the crosscorrelation between the input and the output. Here strictly speaking, a multi-valued nonlinear system such as backlash element can not be expressed by Volterra kernel representation mathematically. But in practice, we encounter many cases where it is difficult to treat them mathematically but they can be controlled from experience. So we here dare to suppose that backlash nonlinear system can be approximated by Volterra kernel representation. Simulations are carried out on a nonlinear system consisting of linear part plus backlash element. And Volterra kernels are measured. The output calculated from the observed Volterra kernels is in good agreement wi th the actual output. And we show that we can obtain the width of backlash element, which is one of the most important parameters, by observing the maximum value of crosscorrelation function between the input M-sequence and the output.