We've developed a new method, as an extension of the existing one, for surface profile measuring.
The system of this method consists of a computer and more than three distance sensors arranged in a row at regular intervals on the sensors head.
As the head shifts one sensors' span, the distance values to the surface are acquired simultaneously by each sensor.
After completing data collection of all measuring points, these data are processed by the computer using least squares method to obtain the surface profile.
We'll show that our method can suppress an accumulative influence of random errors with increasing the number of sensors, and can make it easy to carry out fine zero adjustment, and so, leads to high accuracy.
In the last part, we'll give proof of the existence of the solutions, and also, make it clear how the influence of the head's fluctuations during its traverse motion are cancelled, and the meaning of selecting two base points to solve the simultaneous equations.

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A new clustering method to be used for multi-spectral images is proposed. This method consists of division and merging. The division uses a segmentation technique, in which a multi-spectral image is divided into spatially uniform areas. The division rule is based on the (spatial) Mahalanobis distance between coefficient vectors of a local regression model fitted to the neighboring areas of the image. As this distance is a chi-square statistic, a statistical test is employed to evaluate the significance of the distance, and the threshold for the test is theoretically derived.
The merging uses a clustering technique, in which the divided ares are merged into clusters. The merging rule is based on the (spectral) Mahalanobis distance between mean vectors of the multi-spectral data in divided areas. As this spectral distance also follows the chi-square statistics, the same statistical test is used. A threshold is determined for the test.
In this paper, we describe the principle and the procedures of the test. The superiority of this method to a pixel-by-pixel method with respect to the accuracy and the processing speed is confirmed quantitatively by numerical simulations.

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This paper describes a structural analysis of the piezoresistive semicon ductor high pressure sensors for pressures from 0 to 35MPa range using the finite element method. The analysis reveals that a peak stress appeares in the thick wall part of the silicon diaphragm surface due to local flexibility. Here the local flexibility means elastic deformation of solid part of silicon diaphragm, which is considered to determine the best position of piezoresistive elements in order to produce the largest output voltage. The pressure sensor assembly has oil filled pressure reception part and includes a thin metal seal diaphragm to protect the piezoresistive elements from contamination due to the measuring fluid. A unique metal flow seal technique by using plastic flow characteristics of soft metal is developed to fasten the metal seal diaphragm airtightly to the case. By minimizing the error due to volume change of filled oil, an appropriate dimension of the metal seal diaphragm is designed and prototype sensors are fabricated according to this design. These sensors have the following characteristics: The nonlinearity is less than 0.2% of the full scale in the pressure range of 0 to 35MPa. Total errors, which include zero point change and span change, are less than ±1% in the temperature range of -40∼125°C. No change in these characteristics is observed even when a 150% load is applied repeatedly 10⁶ times to the sensors.

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Previously, we proposed a method to determine simultaneously the true temperature and the emissivity of a plane object. It uses a non-linear emissivity modification brought by the multiple-reflection occuring when a half mirror is put closely and parallel to the object. It is assumed that the distance between the object and the half mirror is negligibly small in comparison with the size of them.
In the previous method, an estimation error is caused by incomplete multiple-reflection of radiation between the half-mirror and the object which takes place when the condition is not satisfied.
In this paper, the modified emissivity is modeled as a function of the ratio of the distance to the radius of a circular object and scattering property of its surface. This model is empirically found to be applicable when the ratio is less than ∼0.6.
The original method is refined and the error is corrected by an algorithm based on the model. Its validity is confirmed by the experiment.

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A most straightforward method for constructing process control systems should be to pair input and output variables of the process and to make up a set of single feedback control loops. Even if each of the loops is designed to work well, however, the overall system may be unsatisfactory because of the inherent interaction in a controlled process. It is therefore important to grasp the interaction among single feedback loops. Although most of the conventional interaction measures are useful to pair input and output variables of the open-loop system, they do not necessarily estimate the interaction in the closed-loop system constructed by pairing the variables.
This paper proposes a measure to estimate the degree of interaction in a closed-loop system and shows its applications to analysis and design problems. The proposed interaction measure is defined as the total amount of control energy which is consumed to overcome the influence of a unit impulse disturbance applied at a point connecting a single feedback loop to the others. The measure is closely related to the stability of a closed-loop system. A series of examinations verified that the measure provides a basis for estimating the interaction in a closed-loop system.

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We consider the controlled discrete event system formulated by Golaszewski and Ramadge, which is a generalization of Ramadge and Wonham's model, and specifications are assumed to be described by predicates on the state set. A predicate P is said to be control-invariant iff there exists a state feedback by which the controlled process remains in a set of states satisfying P. Such a feedback is called a control-alternative. In general, there are more than one control-alternatives for a control-invariant predicate, and the maximal and minimal elements in the set of control-alternatives, which is called maximally and minimally permissive feedbacks respectively, do not always exist uniquely.
This paper proves the necessary and sufficient conditions for the unique existence of maximally and minimally permissive feedbacks by introducing concepts of weak interaction and weak closedness. Since all the reachable states in a controlled system satisfy the given predicate if the initial state does, we introduce maximally and minimally permissive practical feedbacks, and discuss their unique existence. Finally, we deal with the case that the set of control patterns is a lattice, and several properties are shown.

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In practical control problems, it is often desirable to make plant output follow some reference output without overshoot. A few papers have reported the design methods which guarantees no overshoot for known plants. In this paper, a design of model reference adaptive control systems with no overshoot is proposed for linear discrete-time plants. In this design, a bounded region called parameter region, in which unknown plant parameters exist, is assumed to be known. An algorithm to reduce the parameter region is also given and used in the design. The usefulness of the proposed method is confirmed by experiments using a DC servo motor system.

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Robustness of discreate-time model reference adaptive control systems with respect to the mismatch between plant delay and model delay is studied. It is shown that the mismatch of delay is estimated as an approximation error of control signal and that the error is in the high-frequency range. Parameter adjustment with a low-pass filter makes the control system robust against the mismatch of delay.

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This paper concerns sliding mode control of a discrete system, and gives a design method. The sliding mode control has been designed for a continuous system, but it is realized by a digital control system. So there has existed a gap between the design and realized control system. This paper treats the sliding mode control for a discrete system, where the sampling interval of the digital control is considered.

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A new algorithm of recursive parameter estimation is proposed. The algorithm is based on the recursive least squares method and employs a vector-type variable forgetting factor, each element of which corresponds to one unknown parameter. The convergence of the algorithm is proved under deterministic circumstances. The application of the UD factorization is also studied.
The proposed algorithm is advantageous over the conventional one in such a situation when the plant includes more than one time-varying unknown parameters and their rates of change are different. This fact is confirmed by a numerical simulation, by an experiment using a pilot plant of a heat exchanger, and through the application to a heating furnace of a continuous annealing line.

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The main part of this paper is devoted to the systematic description of a best linear discriminant function (BLD). The geometrical relationship between a linear function and a multidimentional normal distribution is considered first to obtain the effctive index for calculating the total misclassification rate of a linear discriminant function. Then, the Pareto optimality is shown as the necessary condition for the BLD, which in turn enables the mathematical formulation of the BLD derivation as the optimization problem with one variable.
In the remained part, we propose the simple algorithm for obtaining the BLD which satisfies the minimax criterion. Convergence of the algorithm is proved.

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By an analogy with Kripke model in modal logic, the possibility measure Π and the necessity measure N in possibility theory are interpreted as follows. The possibility measure Π is constructed by the minimum operator adopted as a conjunctive operator and the necessity measure N is constructed by Dienes implication adopted as an implicational operator.
In this paper, a necessity measure constructed by Gödel implication and some measures related to it are proposed in addition to the usual possibility measure Π and the usual necessity measure N. The necessity measure constructed by Gödel implication is needed for unifying the views of fuzzy decision making and fuzzy mathematical programming. The properties of these measures and relations among them are investigated. Since a necessity measure constructed by Gödel implication does not have the duality with respect to Π, it is called a pseudo-necessity measure Γ. Gödel implication does not satisfy the law of contraposition, whereas Dienes implication satisfies. Thus, the contraposition of Gödel implication generates another implication. The necessity measure constructed by this implication is not a dual measure of Π either, and is called a pseudo-necessity measure L. Furthermore, pseudo-possibility measures ∧ and V, which are dual measures of Γ and L respectively, can also be defined. As the result of investigation on the properties of these measures, it is clarified that Γ and L are the similar measures to N, and ∧ and V are the similar measures to Π. Comparing with the variations of the values of Γ_A(B) and L_A(B), the variation of the value of N_A(B) around 0.5 is more gradual, and likewise comparing with the variations of the values of ∧_A(B)and V_A(B), the variation of the value of Π_A(B) around 0.5 is also more gradual. Γ_A with respect to a fuzzy set A≠0 and L_A with respect to a fuzzy set A such that supx μ_A(x)=1 satisfy the axioms of necessity measure, and ∧_A with respect to a fuzzy set A≠0 and V_A with respect to a fuzzy set A such that supx μ_A(x)=1 satisfy the axioms of possibility measure. Namely, the existence of measures which satisfy the axioms of possibility measure or necessity measure except for Π_A and N_A with respect to a fuzzy set A such that supx μ_A(x)=1 is revealed.

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This paper discusses a general and systematic computational scheme of the inverse dynamics of closed link mechanisms. The scheme works even for multi-loop closed link mechanisms. It is derived by using d'Alembert's principle and obtained without computing the Lagrange multipliers. To account for the constraints, only the Jacobian matrix of the passive joint angles in terms of actuated ones is required. Given a non-redundant actuator system, this allows a unique representation of the constraints even for a complicated multi-loop closed link mechanisms. The scheme is computationally efficient because the computation concerning the Lagrange multipliers is not required. The inverse dynamics of closed link mechanisms that contain redundant actuators and their redundancy optimization are also discussed. Closed link mechanisms with redundant actuators are underdeterminate in computing inverse dynamics. For a redundant actuation system that contains N_r redundant actuators, the passive joint angles are represented by N_r+1 independent ways as functions of actuated joints. Using their Jacobian matrices, the actuational redundancy of closed link mechanism is parameterized by an N_r-dimensional arbitrary vector in a linear equation. For the case with one redundant actuator, the computational algorithm to minimize the joint torque taking account of their limits is presented. Numerical examples are also given to show the computational efficiency of inverse dynamics computation and the possibility of closed link manipulators with actuational redundancy.

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This paper describes vector control for induction servomotor system based on optimal preview control theory. The relation between responses and preview steps of the preview control system is examined by simulation and analytical method.

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A practical and relatively simple method of identifying L-N-L type nonlinear systems is presented. A simulated L-N-L system is identified to illustrate the validity of the algorithm.

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We study the pole assignment problem of distributed parameter systems generated by analytic semigroups. Introducing unbounded feedback operators, we can solve the problem under a weaker restriction on the separation of the open loop poles and the closed loop ones.

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In this paper, we describe a design method of pre-compensator which includes preview action for desired signal. This pre-compensator is designed to improve the tracking performance of the discrete-time servosystem which has unstable zeros.

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