A feasible method is presented for estimating an unknown coefficient which depends on the state of a distributed system. The system is modeled by a class of nonlinear partial differential equations of parabolic type. Noisy observation data are assumed to be acquired through an arbitrary number of sensors allocated in the spatial domain. First, the asymptotic behavior of the solution to the state equation is discussed. Secondly, use is made of the maximum likelihood approach to obtain the optimal estimate of the unknown parameter. The consistency property of the optimal estimate obtained here are also shown. Finally, results of digital simulation experiments are demonstrated for the purpose of supporting the theoretical aspects.

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In general, it is very difficult to control motion of mechanical manipulators when their hand grips an unknown object. The reason is that the dynamic characteristics for manipulators vary according to the payload of the object. In this case, mass, center of mass, and inertia tensor of the end link become unknown parameters, while other system parameters do not change.
This paper presents a new approach to trajectory control by using adaptive controller. Only unknown parameters are identified by an on-line recursive algorithm based on the least squares error criterion, though this method requires angular acceleration observation. The controller is calculated on-line, using an accurate dynamic model with estimated values for unknown parameters. Simulation results for a six degrees of freedom manipulator show that trajectory errors become very small in spite of the fact that the least square estimate is biased when observation noise of joint angular acceleration exists. The effectiveness of the proposed control method was verified by experimental results obtained for a two degrees of freedom manipulator.

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In this paper we study linear time-invariant multivariable systems including both feedforward and feedback compensators. Firstly, a condition for the system to be an internally stable robust tracking system is obtained. Secondly, the class of attainable transfer matrices from reference signal to plant output in internally stable robust tracking systems are clarified. Finally, based on these results, we propose a synthesis procedure of robust tracking systems with desirable transient responses, in which sensitivity and stability margin can be taken into consideration at the same time.

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A control method in which a controlled variable follows a periodic reference input accurately has been proposed. It is applied to the power supply to a proton synchrotron.
However, the method developed so far has been applicable only to single variable systems. In this paper, we discuss its extension to a multivariable case. That is, the controlled variables of a multivariable system are designed to follow a set of periodic references which have the same period but different patterns each other.
In this extension, stabilization of the multivariable system becomes important. In this paper, strategy of stabilization is newly proposed in the frequency domain just like a single variable case.
The obtained design method is reasonable in the sense that it contains the one for a single variable system as a special case. It has the following merits:
(1) Only frequency response of a controlled system is used for the design process.
(2) Graphical method.
(3) It does not limit the application to decoupled multivariable systems.

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Recently, a large number of design method for model reference adaptive control system (MRACS) have been proposed by researchers of stability theorem. MRACS is today one of the most feasible approaches for practical implementation of adaptive control.
It seems most general and practically important in adaptive control to consider systems with time varying parameters. However, the greter part of design methods presuppose that systems are linear and unknown parameters are constant or slowly varying. Few papers have so far dealt with a design method and stability of the MRACS for timevarying systems.
In this paper, a design method for discrete MRACS for a class of linear time varying systems is proposed based on Lyapunov's stability theorem. The time varying systems investigated here have unknown time varying parameters which are described by polynomial or exponetial function of time. The key to ensure the stability of the MRACS is new parameter adaptive algorithms. It is shown that the proposed adaptive algorithms guarantee the convergence of the plant output to the reference sequence though the plant parameter variation are fairly rapid. For the adaptive algorithms proposed here, only available input-output date of the plant are used, using no anticipative value of the plant output. Finally, the validity of the proposed adaptive algorithms is illustrated by numerical examples.

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Events as those of technological innovation and change in political situations are unquantifiable and the structure of interactions among events is usually hardly identified. A dynamic cross impact method has been developed, which can envisage most likely multi-dimentional dynamic scenarios of those events. A ‘dynamic’ scenario here implies combination of events occuring as a time sequence. The static cross impact method, originally developed by Duperrin and Godet and modified by the authors constitutes an essential part of mathematical tools for the method.
The steps for construction of dynamic scenarios of the events are in the following. 1) Estimation of the first order probabilities, including conditional ones, of occurence of events by those who are expertised in the events concerned, 2) conversion of estimated probabilities into a set of first and second order probabilities by employing a two dimensional Markovian model, 3) modification of estimated low order probabilities by use of quadratic programming so as to have them satisfy necessary conditions as a probability set, and 4) derivation of most likely scenario(s) as a chain of reachable static scenarios.
Application of this method to the forecast of nuclear power technology demonstrates validity and, usefulness of this method.

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One of the important problems in system structure's analysis is how to modify strongly connected systems to partial ordering structures that satisfy transitivity. This paper presents an effective method for the above partial order structuring problem. The problem is first formulated into a 0-1 linear programming problem with m constraints and n variables, where m and n are the number of cycles and edges, respectively, in the strongly connected system. To solve the 0-1 linear programming problem, we develop a solution algorithm based on the concept of relaxation strategy. This method has an excellent ability on calculation time. Consequently, this method can be easily applied to the large-scale strongly connected system which has a large number of components and cycles. The effectiveness of the method is demonstrated by applying this to two real problems; a ranking problem based on pairwise comparison and a simulation problem of a sulfuric acid plant.

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For measuring concentration of electrolytic solution resonance method has been applied by using a Q meter. The method is such a way that measuring Q variation continuously of the printed coil dipped into pure water in a cell while solution is transfered and diffused into pure water through control plate and cellophane transferring membrane. Coucentration decided by Q variation curves are obtainable for different concentration and for different components of solution.
The concentration has been set between the range of 0.05∼0.5N for the solution under test at this time. It is found that concentration and components are presumable from the measured curves of a solution with unknown parameter through the experiment with the test frequency at 8MHz. In order to identify the specific parameters of each measured curve, the following two methods were taken for identifying solution under test.
1) Decide parameters by non-linear regression analysis method while approximate measured curves by complemented error function.
2) Compare measured and reference curves overlupped on computer graphic display.
The fundamental data is obtained for the identification of unknown solution with the data analysis mentioned above.

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A new method is proposed for describing human body forms. Human bodies have been measured mainly by Martin's anthropometrical method and body forms have been represented by Martin's measures or indices derived from them. But these cannot reconstruct the original body forms although they describe some features of the human body. The proposed method not only overcomes this defect but enables body forms to be processed as patterns and to be analysed quantitatively.
In this paper body form is defined as shape of silhouette curves and some other well-defined curves on a human body projected on a vertical plane. Body form is represented by sequences of nodes on these body curves. The nodes are extracted from the body curves through a curve dividing algorithm so that linear interpolating splines passing through them can reconstruct the original body curves within a certain error. In this sense the obtained node sequences can be said to describe the body form.
The node extracting procedure was applied to the fifteen body curves defined on the front and side views of 347 Japanese women aged 5 to 54 years. Generally the body form of young grils could be represented with a smaller number of nodes than that of older women. Based on the results 173 node locations were determined that can describe body forms of 99% or more women. It was shown that body forms can be reconstructed with remarkable accuracy by interpolating the above 173 nodes using parabolic splines developed by the authors instead of inear splines. It was also shown that an average body form can be drawn by arithmetically averaging the coordinates of the corresponding nodes among body curves.

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A method is proposed to recover three-dimensional structure and motion of a moving rigid object. It is assumed that one can observe velocity fields generated at temporally discrete intervals by orthographic projection of a set of points belonging to one object whose rotational velocity component is constant.
From the condition of rigidity, an instantaneous rigidity condition is derived which states that the relative position vector between any two points is orthogonal to the corresponding relative velocity vector.
From the condition of constant rotational velocity component, each of the projected relative velocity vectors depicts a similar elliptical trajectory, the direction of whose longer axis is one and the same.
Then one can determine the equations of the ellipses by observing only two points in three views or three points in two views. The solution is obtained from a set of linear equations. The determined length of the longer axis enables one to determine the relative velocity and then the instantaneous rigidity condition is used to obtain the relative position. The special cases where the rotational axis is either perpendicular to or parallel with the image plane are discussed.
The above results are discussed in relation to the relevant psychophysical observations as well as the other theoretical studies.

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In this paper, a new type controller based on a Petry-Net like control language named C-net is proposed. By using C-net, control specifications can be easily described as a directed graph according to a time chart representing work station's actions. Complicated control specifications of work stations can be easily comprehended and changed.
C-net can be directly executed by a microprocessor based controller named SCR (Station Controller). A C-net interpreter executes a defined C-net by interpreting it cyclically (this cycle is called an execution cycle). In real time controll systems, a response time of the controller is an essential factor. An efficient execution schema of C-net interpretation called a limitted scanning method is also presented. In order to evaluate the efficiency of this schema, a performance evaluating model is built. Through the analysis of this model, the expression for calculating a response time of SCR is formulated, and this theoretical response time shows good coincidence with measured response time. By using the presented method SCR can excute the C-net model within 15 msec/execution cycle (on HMCS 68000), which describes control specifications of 10 machine tools-work station, where one of actions avaragely finishes every half a second. (This execution time doesn't depend on a scale of a C-net model.)
SCR has been successfully applied to several applications. A parts assembly station which consists of one industrial robot and six machine tools is dercribed as a example. In this application, initial software development man-hour was reduced about 50% compared with relay radder diagram method. Besides, maintainances as trouble shooting and changing of control specifications have been achieved easily.

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Vegetable factory is an industrial vegetable production system which can supply steady amount of vegetables independent of natural environmental conditions. The system, in which environmental conditions for growing vegetables are completely controlled using artificial lights, is called “completely controlled vegetable factory”. Compared with that, solar- type system is expected to have the advantage of economy and of saving energy by adding solar irradiation. In case of solar-type vegetable factory, however, there is a difficulty that varying solar irradiation effects much on the inside environmental conditions (illuminance, air temperature, and so on). So, environmental cotrol method plays a very important part to suffice both demands of yearlong steady production and of improvement of economy.
In order to perform economically optimum environmental control in solar-type vegetable factory, optimum criteria for inside environmental control are proposed as below.
1) P≥P₀
2) E→MAX.
where P: production
P₀: constant value of production (lower limit)
E index of economy
Production P is a function of inside environmental conditions and index E depends on both inside and outside environmental conditions. 1) is the criterion to ensure certain amount of product. 2) is the criterion for economy, and possible indices of E are, for example, the inverse of productive cost (C), cost performance (P/C), and profit (described as a form of aP-bC, where a and b are constants).
To make sure of the efficiency of the optimum environmental control method based on the above criteria, several cases of simulated controls are executed. The main results are as follows.
1) The economic efficiency of the proposed control methods are clarified, i. e. the comparison with no control and with constant-temperture control shows that our control methods work quite adaptively on outside environmental conditions and sufficiently achieve both demands of steady production and of improvement of economy.
2) In control on cloudy days, economy weighs more than production, differed from that on clear days. And in winter, production cost is lower on the average than in summer.
3) The value of P_o effects much on the control of inside environmental conditions.
And in case that profit is used as E, the estimate of the profit has also much influence on the inside conditions.

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