Recently, many space-borne imaging sensors have been available. As satellites have various height and various spectral bands, we can use many types of data, for example, to analyze the change of the earth's environment. These image data have their own geometrical property, and therefore, they have relative disparity among them. The disparity makes it difficult for us to apply multitemporal and/or multisensor methods for efficient analysis of the environment. In change detection processing, for example, the disparity between multitemporal images causes apparent change. The disparity between stereo pair images also gives us topological information such as terrain height. It has been indispensable to register remotely sensed images with high accuracy. There have been a lot of methods reported for the image registration.
In the most of the former methods, we needed to choose a coordinate transfer function and to select manually many pairs of control point. Accuracy of the registration wholly depends on the coordinate transfer function and the accuracy with which control point pairs were selected. Manual selection of the point pairs is very time consuming and it often causes decrease in accuracy due to mis-selection. Efficient and accurate algorithm has been acquired.
In this paper, we propose an automated registration method ARTSIM (Automated Registration meThod for Satellite IMages). ARTSIM automatically generates as many pairs of control point as possible on the images to be registered. A spatial correlation technique is used to remove the mis-selection of control point pair. In order to avoid the error due to using inadequate coordinate transfer function, we adopt a piecewise registration where images are divided into many triangles so that their vertices are the control points generated, then piecewise Affine transformation is applied to each triangle pair. For achieving high level automation, ARTSIM compensates relative rotation and shift between the images from rough information about their initial disparity.
Here, we describe the principle and the procedures of ARTSIM. The validity of the method is confirmed by numerical simulation. Application results of ARTSIM to actual remotely sensed images are also shown.

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It has already been shown that the stable inverse system can be constructed by using 2-delay input control. However, the control inputs may be often changed very largely between the sample points. The big change of inputs between the sample points causes ripples in the responses and is not desirable.
The purpose of this paper is to make as small as possible the input change between the sample points. The 2-delay input controller which constructs the inverse system contains free parameters involved in the general solutions of Diophantine equation. We will first show the existence of an inverse system that makes the input change during a sampling period settle down to zero in finite time for a specified class of desired inputs. This controller is also given by solving the Diophantine equation and thus contains some free parameters. Secondly, we propose the controller minimizing the input changes before settling down to zero. The summation of squared input changes is introduced as a cost function and the controller is obtained simply by minimizing the cost function.

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This paper presents a new model reference adaptive control system (MRACS) for Hammerstein systems, in which each system consists of a memoryless nonlinearity followed by a linear time invariant system. Such kind of systems is particularly simple, but can describe a class of nonlinear systems including nonlinear actuator. Although existing adaptive control schemes for Hammerstein systems have been developed in discrete-time case, we present the MRACS for continuous-time systems because many actual systems are continuous ones. First, we derive an adaptive control law by using only the input and output variables of the plant, which corresponds to MRACS for linear systems when the plant is linear. Second, we clarify that regularity of the signals in the closed loop is ensured when the relative degree of the plant is determined by the transfer function from the highest power of the input to the output. It is well known that regularity of the closed loop signals plays an important role to prove the stability of the system. By using the regularity conditions, we show that boundedness of all signals in the proposed control system and convergence of the output error are guaranteed in the case. Finally, the effectiveness of the proposed scheme is illustrated through numerical simulations.

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An extension of the Riccati difference equation is introduced. The standard equation is combined with Landau's scheme for adaptive control so as to have a robust convergence property such that a time-invariant stabilizing feedback gain is given even for time-varying systems. The global convergence to the stabilizing solution is proved by constructing a Lyapunov function within the range of time-invariant systems. This relation is an extension of the well-known convergence property of the Riccati difference equation.

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This paper presents a Neuro-Based Adaptive Control (NBAC) for torque control of a flexible beam with structural uncertainties. In the NBAC scheme, a neural network is connected in parallel with a linearized plant model, so that the neural network can be expected to identify the uncertainties included in the controlled plant. At the same time, the neural network works as an adaptive controller that can compensate effects of the unknown part of the plant. In this paper, the NBAC is applied to a torque control of a flexible beam that includes linear and nonlinear structural uncertainties caused by a contact force, a frictional force, shape and material of the beam, and so on. The comparison of the experimental results under the NBAC and other control methods illustrates the effectiveness and applicability of the NBAC.

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In the order allocation to in-stock slabs problem, it is necessary to optimize both the selection thick and flat pieces of steel plate, that is called in-stock slabs, for each orders and the order arrangement in hot rolling plates. The optimum solution in this problem is to produce as many high priority orders as possible while using the slabs as efficiently as possible, i.e. reducing waste material as much as possible.
We have approached this in-stock allocation problem as a combinatorial optimization problem and have successfully applied a combinatorial optimization method known as the genetic algorithms (GA) to achieve an optimal allocation and arrangement. We present the GA based system in this paper.
As the in-stock allocation problem became more complicated (number of constraints included, number of orders, number of slabs, etc.) the calculation time began to exceed the allocated production planning time. In this system we divided the problem into sub problems while maintaining solution quality. By allocating the given calculation time among the small problems we were able to obtain a good solution in a feasible calculation time.
In general, it is difficult to solve the problem which includes a vast of array of solution constraints and restrictions using GA. The order allocation problem has many these constraints such as order/slab material composition restriction, machine dictated order arrangement constraints and so on. In the proposed system, by introducing a new coding and decoding method which considers these constraints, it is possible to enable the application of GA.
Furthermore, in this problem it is necessary to satisfy the two objectives of order priority and yield rate. By the construction of the evaluation function and the tuning of the weighting coefficients we were able to develop a system which satisfies two objectives.

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This paper deals with a warehousing problem in three dimensional space, by taking account of safety, availability of the capacity, and easiness for taking boxes out. This problem is a complicated combinatorial optimization problem with three-dimensional constraints. The objective is to get the most favorite arrangement of boxes in a warahouse. An important constraint is that the area of the base of the upper box is always smaller than that of the lower box. In the problem formulation, this constraint is treated explicitly, but the other constraints are included in the objective as the respective penalty functions. The genetic algorithm (GA) is applied to solving the problem. For searching for a solution efficiently, several procedures such as the individual description, the decoding rule, crossover and mutation are proposed for this problem. Particularly, a new idea of “column” is introduced in this paper. The column is an array of boxes arranged in the vertical direction, which is applied to converting the genotype into the phenotype without getting an infeasible solution of the problem. Numerical results are shown to investigate the effectiveness of these procedures.

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Automatic machine which seems to be represented by transfer machines takes charge of manufacturing process and its automation is important for realization of automation of whole manufacturing system. Manufacturing process of automatic machines is generally sequential control and Programmable Controller (PC) is put to controlling use. During automatic driving, automatic machines frequently carries out a special so-called “return action” which is a kind of controlled action with reverse sequence according to its normal sequence. It is difficult to represent “return action” by Sequential Function Chart (SFC) which is widely used for the normal sequential control. Some representing techniques are already suggested, but a practical case is not appeared for the simplicity of SFC expression to be ruined.
The authors suggested Total-SFC (T-SFC) as an expansion of SFC expression. In T-SFC, sequential control part is represented in usual SFC while non-sequential control part is represented in Random Function Chart (RFC) and Interlock Tables. The change over from sequential control to reverse sequential control of “return action” is non-sequential control and reverse sequential control itself is sequential control. In this paper, the general definition is given for “return action” having such characteristics. An approach by T-SFC is taken and the effectiveness of the representation is shown. That realization is possible by exemplifying in an example of transfer machine and the advantage is described.

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This paper described contour control of flexible manipulators by use of modified taught data method. To circumvent an oscillation of the robot arm movement in high speed operation, the arm should be regarded as flexible and be controlled appropriately. The modified taught data method was proved to be an appropriate tool for this purpose through theoretical and experimental considerations.

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This paper describes the outline of the serpent type wave maker and generated oblique wave and gives the directional resolution of the oblique regular wave in the serpent type wave maker.

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