This paper describes an application of an improved optimal regulator technique developed on the basis of original optimal regulator theory to synthesis of speed control system of static Scherbius induction motor system. Theoretical results are compared with the experimental results. As the processing time required to execute the employed control algorithm in a microprocessor employed as a controller of the control system is not short enough compared with the fast transient motion of the induction motor, input delay time due to the processing time is taken into account when designing the control system. In order to improve the steady state characteristics of the designed control system, integral action is introduced in the designed control system, which results in zero steady state error, unlike the original optimal regulator system. The sampling period is chosen to be 20ms which is very short compared with the mechanical time constant and is one-fifth of the electrical time constant of the controlled object. Experiments are carried out using 8-bits microprocessor connected a high speed arithmetic element in order to make floating calculations in the microprocessor system very fast and to avoid overflows in the calculations in the microprocessor system. Feedback gains obtained theoretically by means of optimal regulator technique are used in the simulation study and in the experimental study as well. The steady state error of the control system of the experimental setup is recognized to zero in spite of step change with reasonable magnitude in the desired signal and the generator type load. The transient response, however, is not improved because the control input variable corresponding to controlling angle of the cycloconverter is restricted to with in some values in order to avoid the commutation failure of the cycloconverter used in the induction motor system. That is, the magnitude of the control input variable at the transient state cannot be allowed to grow up very large value to make the system response fast. This is inevitable situation in the present controlled object. The experimental results are compared with the simulation results, and fairy close agreement is obtained which confirms the effectiveness of the improved optimal regulator technique and the exactness of the experiments.

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This paper deals with the problem of constructing a minimal-order state observer for Roesser-type two-dimensional systems. Sufficient conditions are derived for the existence of the observer and the design procedure is presented. It is shown that if a full-order observer can be constructed for a given two-dimensional system, the minimal-order observer can also be constructed. Finally an example shows that by the method presented in this paper, we can design a minimal-order observer for a two-dimensional system for which no state observer exists by the method of Hinamoto et al.

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In this paper, a method is presented for modeling a class of nonlinear systems which involves time-varying parameters. The system model proposed here is a type of nonlinear difference equation, where unknown parameters are assumed to be linearly involved in the system model.
The principal line of attack is to assume that the nonlinear time-varying function in the system can be expanded into the M known functions with unknown constant coefficients.
First, the estimation process of unknown parameters is given by using the maximum likelihood principle. Secondly, consistency properties and asymptotic normality conditions of the estimator are shown. Finally, two numerical examples are shown in order to demonstrate asymptotic properties of the estimator derived here.

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Recently, intense interest has been shown towards recursive algorithms for parametric identification of systems derived from Model Reference Adaptive Systems (MRAS identifiers) which assure global asymptotical convergence of solutions. We apply an MRAS identifier to one-day-ahead load forecasting. Based on actual data from Kyushu Electric Power Company and weather stations in Kyushu throughout 1981, the accuracy of the proposed load forecasting is found to be very high, the standard deviation of the error of the forecast being under 4%. There exists two important keys to the forecasting success of the MRAS identifier; the suitable construction of a load model and the proper use of an MRAS identifier.
According to properties of load curves, we construct 24 load models using hourly measurements of weather conditions during a 24 hour period. We then find the best load models, whose input signals are measurements of the daily variation of the discomfort indices and whose output signals are daily load changes.
Since an inadequate MRAS identifier causes poor identification of the load models, the selection of a good MRAS identifier is an important task. We select an MRAS identifier whose steady state gain is regulated by the two indices λ and μ. By using proper values of λ and μ, the MRAS identifier accurately identify the load models. Based on actual data, the pertinent values of λ and μ are found to be within the interval from 0.78 to 0.98.

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Recently, a large number of design methods for model reference adaptive control system (MRACS) have been proposed by researchers of stability theorems. MRACS is today one of the most feasible approaches for practical implementation of adaptive control systems. However, there have been few papers which deal with MRACS for bilinear systems.
In this paper, a design method of discrete MRACS for single-input single-output bilinear systems with time-delay is proposed based on Lyapunov's stability theorem. It is shown that the proposed adaptive algorithms guarantee the convergency of the plant's output to the reference sequence through a simple procedure. For the adaptive algorithms proposed here, only available input-output data of the plant are used, using no anticipative value of the plant output and information on unknown plant parameters. Finally, the validity of the proposed adaptive algorithms is illustrated by numerical examples.

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Proposed in this paper is a design method for a model reference adaptive control system (MRACS) using continuous-time control law and discrete-time adaptive law. Such a MRACS is called a hybrid one and has the following attractive properties. The convergence speed is faster than that of a MRACS using continuous-time adaptive law. It is free from the problem on unstable zeros caused by a zero-order hold device, which is essential to a MRACS using discrete-time control law. For a hybrid MRACS, sampling scheme plays an important role to ensure the asymptotic stability of the system. In the proposed method, the periodic sampling scheme is employed in conjunction with the discussion on selection of sampling period guaranteeing the asymptotic stability, where the concept of dimensional invariance is introduced. Representation of continuous-time systems and basic structure of MRACS's that are suitable for the hybrid design are also shown. The superiority of the proposed method is demonstrated by a simple numerical example.

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This paper presents a stable multivariable MRACS (Model Reference Adaptive Control System) including an estimator for unknown coefficients of polynomials which are the nondiagonal elements of the interactor matrix of the plant. It is shown that the degrees of the polynomials are bounded by the plant's degree and that there exists an identification model which retaines the left-lower triangles structure of the interactor matrix. The former relates the number of the coefficients to be estimated and the latter plays a key role on the stability proof. Thereafter, the adaptive control system is designed on the assumption of knowing degrees of diagonal elements of the interactor matrix. It is a most general extention of MRACS from the scalar system to the multivariable system in the sence that it requires the minimal restriction on the plant's transfer function and the minimal information on the plant's interactor matrix. The global stability of the total control system is proved through modification of the established method by Goodwin et al.. Some numerical examples are also presented to show the effectiveness of the proposed adaptive control in comparison with the ordinary adaptive control in which the interactor matrix should be completely known a priori.

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This paper describes the computer-aided image processing of a moiré pattern of vortices behind cylinders in steady flow.
Moiré topography has been paid attention as an effective way to visualize fluid phenomena, because three dimensional objects are recognized by this method.
But, in general, moiré fringes on fluid phenomena include many noises and the contrast of the image is weak because of the faint reflection of light on the surface of fluid.
Besides, when the moiré fringes are overlaped or tore off, it is necessary to modify these fringes.
For these reasons, it is difficult to get necessary informations in the moiré fringes on fluid phenomena by applying the usual image processing algorithm.
In order to solve these problems, we have developed a new algorithm for the computeraided automatic image processing of the moiré pattern.
This algorithm consists of a filter part and an analysis part.
In the filter part, the image contrast is emphasized, the noises are excluded, and the lack of fringes is corrected.
In the analysis part, the center lines of fringes and the center points of vortices are picked out and the fringe numbers are determined.
In this paper, we explain the principle of this algorithm and show the results of its application to some moiré patterns of vortices behind cylinders in steady flow.

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The purpose of this paper is to present a new method for determining the particle size distribution from angulary scattered light intensity pattern. By the present method arbitrarily shaped particle size distribution can be obtained.
This method is a constrained inversion method of equation (1) under the following conditions: (1) n(D) is smooth and (2) n(D) is non-negative.
logI(θ)=log[∫i(D, θ)n(D)dD] (1)
I(θ): scattered light intensity pattern.
n(D): particle size distribution
i(D, θ): Mie scattering function Equation (1) is approximated by linear equations (I=G·n). The least square solution of its equations is obtained using Lagrange's method of indeterminate coefficients and KuhnTucker's theorem. In Lagrange's method Lagrangian multiplier γ must be selected. It is shown that geometrical mean value of G*G's eigenvalues is suitable for Lagrangian multiplier γ.
Numerical experiments are performed to verify the effectiveness of constraint conditions and the validity of γ selection. Several particle size distributions are inverted from measured light intensity patterns scattering by Polystyrene particles whose diameters are known to verify the applicability of the present method.

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The cross-correlation of m-sequences which have the same period but different characteristic polynomials is shown theoretically.
When the order N of a primitive element α in GF(2ⁿ) is nonprime, it is represented by N=sq(s, q, integer). Therefore an irreducible polynomial of degree n of exponent q with a root α^s must exist. If each root of the two different primitive polynomials is denoted as α^a, α^b, the primitive polynomials can be classified into a set of primitive polynomials in such a way that sa, sb modulo N belong to the same coset. This means that the two m-sequences are classified into the same class if they become the same sequence under the sampling of s bits.
By the use of characteristic m-sequences it is shown that the cross-correlation between the different m-sequences generated by primitive polynomials of the same class becomes large when the delay is an integral multiple of q. This is due to the fact that the cross-correlation sequence contains the non-maximum length sequences generated by its irreducible polynomial.
The cross-correlation values in case of s=3 are analyzed and obtained explicitly. The cross-correlation values actually obtained agree well with the theoretical ones.

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A new principle of on-line crook measurement for long size rolling stock while running is devised, instead of customary off line static measurement. Rolled steel beams and plates aretransferred on roller tables generally accompanied with the motion of traverse and rotation. Therefore, the following three measuring methodes are described. (1) For the case of both traverse and rotation are negligible, and the transfer can be regarded as parallel movement: The camber of the rolling stock can be expressed by processing the sampling measurement data of the rolling stock edge displacement at the fixed point beside the transfer table, with a costant interval of the transfer movement. (2) For the case accompanied with traverse, yet rotation is negligible: Traverse effect is eliminated by sampling measuerment of the stock edge displacement at the fixed two points with a constant interval length beside the transfer table. The camber is calculated by the fundamental camber equation. (3) For the case accompanied with both traverse and rotation: To eliminate the both effects, the method is introduced by sampling measurement of the edge displacement at the fixed three points with a constant length of intervals beside the transfer table. The camber is also calculated by the equation.
This principle was applied to on-line crook measurement of steel beam just after rolled. The practical system was developed through the various analysis and experiments. The beam edge dispacement was measured by three detectors of photo-diode arrays. To compensate the vertical crook, ITV deflection detectors were also used. Digital filter processing was introduced to eliminate the short pitch noise of the detecting signal by the mini-computer, which was also used for camber calculation with the measured data. On-line test results of the developed system satisfied fully the aimed accuracy. This on-line crook measurement system may be generally applicable also to various long size stock other than steel beam.

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