The purpose of this paper is to present the correct theory of the annular viscometer for gases. The measuring principle of this viscometer has been obtained from the Navier-Stokes equation for a steady flow of a viscous compressible fluid in cylindrical coordinates system. To find approximate solution, it is assumed that the mass velocity profile ρv is a function of the distance from the axis of the annular tube. The limit of the value as the mass flowrate ρQ approaches zero gives the true value η of viscosity.

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The influence of insertion and strength of each extensor on patellofemoral disorders was fully investigated through a 2-dimensional mathematical model analysis in combination with experimental design theory. In the model, the patellofemoral sections have been expressed by the spline functions. Each muscle of quadriceps has been represented by string pulled by respective force, and fascias and tendon by springs. Nonlinear equations have been composed, then solved by numerical iteration procedure. A series of simulations have been repeated to obtain the following results. The strength of most extensors has influence on the increase in lateral contact force but not patellar dislocation. The patellar tendon's insertion has significant influence on both patellar dislocation and lateral contact force. The quadriceps' insertion on the femur has no influence on patellar dislocation. The insertion of each extensor on the patella has strong effect on patellar dislocation but not on contact force.

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Microscopic LDV is made to explore the flow velocity in an extremely small area. Though it has a good spatial resolution, Doppler signals obtained from it have fewer wavenumbers in one burst signal than normal LDV. Therefore, duration time of one signal is very short. Furthermore measurements on such as lymph flow, not enough S/N ratio is expected because of scattered lights from tissues or vessel walls. So, traditional signal processing method like Burst Spectrum Analyzer (BSA) which is based on an extremely fast hardwared FFT processor is unsuited for these signals under low S/N ratio.
This paper describes a problem in case of processing signals obtained from microscopic LDV using conventional BSA through basic simulation. From this simulation, we made a correction coefficient which correspond to Doppler signals and applied it to spectrum of Doppler signals. Moreover, because of their short duration time, spectrum broadening occurs when such signals are analyzed using FFT. By taking account of this characteristic and improving the conventional BSA in two ways, we propose a new signal processing method to distinguish the spectrum of Doppler signal from that of noise. Furthermore, we carried out a fundamental experiment to examine their effectiveness on such signals.

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This paper analyzes a linear time-invariant two-channel decentralized control system with a 2×2 proper plant. A necessary and sufficient condition is given for the plant to be strongly stabilizable by such decentralized dynamic out put feedback, directly depending on the characteristics of the plant.

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This paper considers the problem of unit interpolation with rational analytic bounded functions. Lower bounds of the degree and norm of the units which interpolate given data are derived, using the Nevanlinna-Pick matrix and the non-Euclidian distance. These results explain why stable controllers tend to have large degree/norm in the strong stabilization problem.

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The authors propose an approach of optimal design for simultaneous optimization of structure and control systems. The dynamic characteristics of the regulator system is optimized against given disturbances. The present report considers two kinds of disturbances applied to the structural system. One is a white noise disturbance and the other is a harmonic wave disturbance. In case of a white noise disturbance, optimization is achieved by modifying the performance indexes with respect to both the state variables and the control inputs based on the time history response. When a harmonic wave disturbance is applied, the gains, the poles and the zero-points of the transfer functions are modified to avoid the phenomenon of instability at the frequency of the disturbance. Modification is performed by the sensitivity analysis in which the sensitivities with respect to both structural and control parameters are used simultaneously. The proposed method is applied to a multi-degrees of freedom system model. In case of a white noise disturbance, decrease of both the performance indexes of the state variables and the control inputs is realized by modifying both the structural and the control parameters simultaneously. The characteristics on frequency domain are also improved.

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Pisarenko's method is an approach to estimate the frequencies of sinusoidal signals corrupted by a white noise. Because this method provides theoretically an unbiased estimation independent on the signal-to-noise ratio, many researchers have improved Pisarenko's method and developed efficient fast algorithms for it.
In this paper, we first present a procedure for the analytic signal transform, which has zero phase property using the fast Fourier transform. It can generate N analytic signals from N measurement data, so it is suitable for spectral analysis with finite data. Secondly, we show that we could get a good frequency estimation by using Pisarenko's method with the analytic signals. Furthermore, we drive three procedures which use effectively and averagely the decimated analytic signals by two and the remainder signals in the decimation. We compare the three procedures by computer simulations and, as a result, insist that the procedure with autocorrelation function averaging is the best of the three.
This method gives much more accurate frequency estimation than the conventional Pisarenko method. Also, we could perform a real-time processing with the proposed method if we use several efficient algorithms developed recently.

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Many control system design algorithms assume knowledge of the parameters of the signal process model. In practice rarely is there a priori knowledge of these parameters, and so there exists the need to identify a signal model first. In such a case an autoregressive moving-average (ARMA) model is frequently used.
Durbin's method is an ARMA parameter estimation procedure, which provides good estimation with moderate computations. In this paper it is shown that the Durbin's method is not suitable for identifying the parameters of signals that possess lowpass and broadband power spectrum. Thus an alternative procedure is driven which could identify parameters of complex-coefficient ARMA model satisfying only the positive frequency characteristic of the unknown system. This procedure contains an efficient high-order AR model estimation algorithm, which is also proposed in this paper, and requires half the model order compared with the conventional Durbin's method. This algorithm can provide better estimation than the Durbin's one, upon finite precision arithmetic and with less computational burden. Computer simulations confirm those properties of the proposed procedure.

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In general, in multivariable adaptive control, direct method involves much more parameters to be adjusted than indirect method. It is often the case, however, that some of controller parameters are constant or even of zero value because of the intrinsic feature of the plant structure. That is, the number of unknown controller parameters may be considerably reduced by utilizing effectively a priori knowledge on the plant structure.
In this paper, adaptive control of water levels of a two-tank system is considered. By analyzing the system, some of controller parameters could be set to zeros, which in turn enable us to decrease the amount of computation required in each step. Another emphasis is put on the way of dealing with noises contained in output signals. It is confirmed that these noises cause oscillatory plant input signals with high frequency and large amplitude which do harm to input equipments. The noise problem could be overcome by adjusting the poles of observer as well as zeros of interactor.
These two ideas concerning with utilizing a priori knowledge of plant structure and with overcoming the noise problem are very universal and may be applied to many other plants.

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In many chemical reaction processes, the reaction rate depends on the temperature and this relation may be expressed by Arrhenius equation. So this paper discusses the identification for the nonlinear system with Arrhenius temperature dependence. Firstly, we hypothesize the system models on basis of the physical and chemical process, various hypotheses and approximation. Secondly, the parameters of each model are estimated by the maximum likelihood method and we calculate a posteriori probabilities for each model by the Bayesian theorem and discriminate as the optimal model whose probability is maximum.
Furthermore, it is shown from the digital simulation that the nonlinear processes with the Arrhenius temperature dependence may be identified by this method, and we apply this method to the real chemical process and obtain adequate results.

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An adaptive law and a learning method are proposed and evaluated through simulation study on controlling a PVC (Poly-Vinyl Chloride) reactor process which has highly nonlinear and time varing characteristics.
In identification of the process parameters, there are some cases where persistently excited condition is not satisfied because of constant input-output signal. As a result, the identification is not correct and the control performance degrade. On the one hand, there are some requirements Whether any methods can have learning function which the more process operation repeat, the more control effect improve.
First, in order to cope with the constant input-output signal, the proposed adaptive law prepared the forgetting factor based on restricting the trace value of adaptive gain matrix. It is obtained that the proposed adaptive law is superior to a constant trace algorithm and a variable adaptive gain algorithm.
Next, to compensate the time delay included in estimated parameters, we compose the learning method using estimated parameters in last operation. It is demonstrated that the control effect of proposed learning method attains improvements in the early temperature heating stage whenever process operation repeat by computer simulation.

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A ‘coil sensor glove’ has been proposed as a human interface device in order to operate artificial fingers of a robot hand by human fingers. Five angle sensors were attached to the glove to detect joint angles of human fingers. As an angle sensor, a pair of chip coils which were fixed on rubber was used to obtain the angle electromagnetically. The angle was found to be exactly detected without hystereses and time delay. Artificial fingers and its operation system have been developed for a tele-existence robot. The artificial fingers modeled after an index finger and a thumb were designed so that the mechanism and the structure are similar to those of human fingers. The coil sensor glove was proven available to control the movement of the artificial fingers almost in real time.

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A neural network designed to minimize an energy function is shown to be effective in nonlinear estimation. The problem treated in this paper is to estimate states of Markov jump processes from noisy observations. The estimation is accomplished by minimizing an energy function, which bears both information about the measured data and a priori information about the process. The energy function takes the minimum at the point corresponding to a sub-optimal state estimate, which is the optimal estimate under the hypothesis about jumps with maximum a posteriori probability. Though the energy function is not differentiable and has extremely many local minima, it is shown that the network attains the minimum by a continuous modification of the energy function. It is also shown that the network is applicable not only to batch processing, but also to recursive processing using a sliding window. Finally, the method is extended to the estimation of processes which have jumps in velocity.

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Active sensing plays an important role in autonomous robot systems. This paper presents an automatic planning method of light source placement for an active photometric stereo system. Since photometric stereo systems normally use multiple light sources fixed to the environment, they cannot avoid shadows caused by surrounding objects. One remedy for this problem is to use a movable light source and to adapt its placement actively to the task environment. Candidate positions of a light source to avoid shadows are obtained initially based on a 3-dimensional model of the environment and image processing on a sphere assumed to be around the target objects. Then possible combinations are compared based on a criterion taking into accout of reliability and detectability of the measurement. We introduce a singular value analysis of the coefficient matrix to evaluate the reliability of the solution. As for the detectability criterion, size of a region which corresponds to a set of detectable surface normal vectors is evaluated on a Gaussian sphere. Experimental results, using a light source affixed to a manipulator, demonstrate usefulness of the sensor setup planning.

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This paper presents a sequential filtering algorithm for the white Gaussian plus colored observation noise. The filter uses the information of the crosscovariance function between the signal and the observed value, and that of the autocovariance function of the signal plus colored noise process.

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The paper proposes a method to decrease the number of basis functions to estimate the anomaly function in order to make the fault detection for a linear discrete dynamic system much easier.

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A design method for constructing nonlinear adaptive control systems independent of the degree of the controlled processes is proposed in this paper. It is shown that no knowlege on the degree of the process is needed.

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This paper describes deployment test method using tracking control system. Configuration of the test facility is suggested and its validity is confirmed by using a deployable antenna reflector which is scheduled to be mounted on Engineering Test Satellite VI (ETS-VI).

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