This paper presents an efficient method for acquisition of generalized action-decision knowledge based on gaze control for virtual mobile robot. The relationships between actions and gaze control are acquired by genetic algorithm in the form of if-then rules. The extracted generalized knowledge from the acquired rules accelerate acquisition of new action-decision rules under unknown environment. The virtual mobile robot equipped with range sensors traveling from a start point to goal area is simulated. The extracted generalized knowledge from rules under some environments operated well to accelerate the learning of robot under unknown environment. The result can be interpreted as skill transition under various environments realized by means of generalization of acquired knowledge.

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We show that a logical error is contained in some epidemiologic papers which intend to verify the hypothesis that there is an association between magnetic fields of power lines and childhood leukemia: for instance, the Swedish paper by Feychting and Ahlbom in 1993 showed us leukemia association related to calculated magnetic fields in one-family houses but apartment ones, from the results obtained from the stratified analyses according to type of building; this was contradictory to their premise that exposure assessment was claculated magnetic fields irrespective of type of building. However, the authors described in conlusion that their hypothesis could be verified. Nevertheless it needed to be supplemented by some data, as was customary in epidemiologic analysis, not to miss any possible causes of cancer. Our views are as follows: related engineers would be hard to accept the procedure, which needs the supplementary data, because it is employed at the auther (s)'s will for the scheduled verification of the hypothesis; it would be natural to suppose that the hypothesis could not be verified.

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We propose a method to estimate pose of a three-dimensional object from two dimensional image based on a parametric eigen space method. In this method we use a Gaussian blurred edge image as the input image instead of the original image itself. There we compress the input images using K-L transformation, and show better pose estimation can be achieved than the method which use the original images as its inputs. The method has better efficiency especially in the cases of with occlusion, position shift and intensity changes of the objects.

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We propose a new design method for the model predictive control system based on a dual parametrization, that is, a class of all plants stabilized by a basic controller. The objective is to design the model predictive control system which guarantees the stability of the control system for a perturbed plant and to enhance the tracking performance with the basic controller. The design procedure consists of two steps. First, we design the basic integral controller for the nominal plant and consider the dual parametrization and Youla parametrization its extension to the dual case. Next, we carry out the model predictive control by tuning the free parameter of the Youla parametrization. A numerical example is given to illustrate the effectiveness of the proposed method by comparing with MAC (Model Algorithmic Control).

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In this paper, a decoupling control for a non-minimum phase system is considered from a limiting form of linear optimal regulator problems point of view, and an explicit relationship between the limiting properties and a decoupling control is shown. Moreover, using an appropriate performance index, this paper deals with the new method on the decoupling control to keep out the effect of the natural poles by pole-zero cancellation. The properties of stability and sensitivity are improved by this method. This paper also gives numerical examples to illustrate effectiveness on decoupling control with a limiting form.

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The purpose of this paper is to construct a disparity _??_ection method based on the spatial characteristic of simple cells in the visual cortex and to evaluate its availabilities for the stereopsis. The receptive fields of simple cells are approximated by two-dimensional spatial filters described with Gabor function. This filter is referred to as Gabor filter, which selectively responds of to stimulus patterns with specific spatial frequency and phase.
The principle of the disparity detection is as follows. When input images are given, a pair of the Gabor filters which have a certain phase difference show the maximum output among the filters. The phase difference between the right and left Gabor filters is approximately proportional to the disparity.
The disparity is calculated in the following three steps. First, the left and the right images are spatially filtered with a Gabor filter and the value of phase differences is calculated at each pixel. Second, the phase differences are calculated at several spatial frequencies of Gabor filter. Finally, a unique disparity at each pixel is obtained from a weighted sum of these phase differences, and spatial profile of the disparities in adjacent pixels is made smooth.

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This paper presents VLSI architecture for FIR filter with very high throughput keeping small latency. In this architecture, a block implementation with characteristic of multirate system is applied, so that very high sampling rate becomes possible while processing speed of PE's is held constant. Moreover, by using distributed arithmetic, of which processing time depends on only word length and data of input and output are given serially, latency can be minimized and number of signal pins can be reduced to 2L for block length L. Next, we reveal a new method of lower power dissipation, by considering not only the properties of function Φ but also impulse response of even symmetry and odd symmetry. As a result we show that a 32-tap FIR digital filter can be realized with very high sampling rate of 95.2MHz and the small latency of 315ns, by using 0.6μm CMOS technology. In this case, the processor is implemented with relatively low power of 5.41 W.

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This paper presents a homotopy approach to identification of ARMAX systems. The idea is to construct a homotopy connection of the identification based on ARMAX model with the one based on ARX model. LS (least squares) estimate of ARX model, which guarantee to be global minimum of the loss function, is mapped to the estimate of ARMAX model. By tracking paths of LS estimate gradually transformed into the estimate of ARMAX model, it is shown to have very good convergence properties in estimation. Monte Carlo simulations are carried out to demonstrate the effectiveness of the proposed approach.

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This paper presents conditions of reachability onto a switching plane for the sliding mode control of phase-shifters in multimachine power systems. Sliding mode controllers are usually synthesized so as to satisfy only the existence condition of a sliding mode. However, there is the border of an asymptotically stable region and a system state cannot reach onto a switching plane unless a state at the start of control (initial state) exists in that region. Hence, reachability is defined as an asymptotic stability of the initial state. A sufficient condition to reach onto a switching plane is given by an energy-type Lyapunov function. It is described by control parameters which are introduced to find required control gains rather than feedback gains themselves. This allows us to straightforwardly evaluate an asymptotic stability. A phase-shift control system is numerically tested in a 2-machine 1-infinite-bus power system. The simulation results show that improved control system offers faster transient stability and achieves the reachability of a switching plane.

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The generalized minimum variance control (GMVC) method was proposed by Clarke, and it was developed by Allidina taking into account of the closed-loop properties. However, these methods could not be applied to nonlinear systems. In this paper, a new design method of GMVC for nonlinear systems is proposed. This method is a kind of the hybrid controllers by using linear controllers and neural networks (NN). The GMVC law is derived for the known linear model of the controlled object, and the NN learns to compensate the modeling error. Finally, a numerical simulation example is illustrated in order to show the effectiveness of the proposed method.

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This paper presents a new design method of optimal deadbeat control system considering the time delay arising from a computation. First, dynamic characteristic of the system is expressed by the step response. The deadbeat control signal which minimizes the quadratic cost function of the control signal and errors can be easily obtained by the matrix computation using sampled data of the system's responses. Then, parameters of compensators and feedback gain of the control system are easily determined from formulated matrix by using control signal having controlling delay. Finally, the effectiveness of the proposed method is confirmed by applying it to three different control systems.

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Supervisory systems such as in power plants require complex tasks for users to communicate with each other. During a maintenance period or in case of system malfunctions, skilled staff members have to go to the actual field of the plant involved and check equipment directly, and operators in the central control room have to support for staff members. But, it is very difficult for operators to contact the appropriate staff member and encourage collaboration, because there is no way to know current location of the staff member and to contact him/her directly.
In addition, supervisory system users need to use several different styles of communication which depend on the phase of the users tasks. For example, an operator may get collaboration between staff members by personal intervention as well as need the help of other operators to do difficult task . Also, they have to switch styles of communication frequently.
We propose a new extended user interface model to overcome these problems and we propose a system based on the model. Communi-Board, which is a notice board system, provides seamless communication with dispersed staff members by two functions. One is quick contacting to dispersed staff members by chasers which indicate member locations, and the other is automatic changing of communication styles covering all situations by simple action.

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Concern for the environment has recently led to very severe regulations on fuel consumption and exhaust emissions. Especially fuel consumption has become more important index which represents technology of car makers. This paper therefor proposes a scheme to minimize rate of fuel consumption by a direct fuel injection engine used by combination with a continuously variable transmission. Target values for the engine and the transmission which minimize fuel consumption ensuring driving performance are calculated based on the nonlinear optimization method. The engine and the transmission are cooperatively controlled in order to achieve these target values.
The simulation in the acceleration test and the 10-15 mode test showed that the proposed method is effective to achieve low fuel consumption ensuring driving performance.

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The problem of adaptive control for a class of dynamical systems including delayed states is considered. In the paper, a key assumption on continuous time-delay systems is made. On the basis of this key assumption, an algorithm for direct adaptive control is proposed, and it is also shown that the closed-loop time-delay system resulting from the proposed adaptive control schemes is globally stable in the sense of uniform ultimate boundedness. Particularly, the time-varying delay is assumed only to be any bounded and continuous nonnegative function, and is independent of the proposed adaptive control schemes. Therefore, the results obtained in this paper are also applicable to dynamical systems with uncertain time-delay. Finally, a numerical example is given to demonstrate the validity of the results.

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In order to improve the response property of the closed-loop control system constructed by generalized minimum variance control (GMVC), in general, the control-weighting polynomial included in the cost function is adjusted. But, the tracking response to the reference-signal and the response property for disturbances are changed together when the control-weighting polynomial is tuned.
A method solving this problem is a two-degree-of-freedom GMVC. In this paper, we propose a two-degree-of-freedom GMVC with the reference-signal-filter. On the other hand, we propose the control system allowing the reference-signal-weighting to be a rational function in the conventional control structure. This system can set up the feedback property and the tracking performance independently.

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Electromyographic and mechanomyographic signal (EMG and MMG) reflect the electrical and mechanical activities of contracting muscle fibers, respectively. The complexity of these signals vary with increasing force exerted. The fractal analysis methods may be used to assess the complexity of the signals. The present investigation was undertaken to determine whether the surface EMG and MMG signal have the fractal characteristics and to estimate their fractal dimension. The EMG and MMG signal were recorded from the rectus femoris muscle of 12 normal subjects during submaximal isometric contractions at the intensity of 10% to 80% of maximal voluntary contraction (MVC). The fractal dimension of these signals was calculated by the resealed range analysis (R/S analysis) and the Higuchi's algorithm. The results demonstrated that both the EMG and MMG were a fractal signal. The R/S analysis seems not to estimate correctly the fractal dimension of both EMG and MMG signal. On the other hand, the fractal dimension calculated by Higuchi's algorithm changed with increasing force and ranged from 1.5 to 1.7 in the EMG and from 1.6 to 1.8 in the MMG. The relationship between the fractal dimension and %MVC in the MMG is considered to be more consistent with the physiological findings on the motor unit activation strategy compared with that in the EMG.

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This paper deals with loop-shaping characteristics on hand position control of a human operator in a human-machine control system. We consider that a human-machine control system generally can be regarded to comprise a hand position control subsystem which consists of mechanical dynamics of the operator and the machine. In this paper, we investigate this subsystem and properties of human operator on adapting his mechanical dynamics to the machine. As a result, loop-shaping characteristics of a human operator on his hand position control are discovered. The knowledge of the characteristics is quite useful for designing mechanical dynamics of the interface part of the human-machine control system.

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The problem of estimating orders and delay-time of the process in a closed-loop control system is investigated in this paper. We have proposed an estimation procedure before, but it needed additive noise to the input part. If the input is noise free, estimation becomes much more difficult because it is hard to understand property of the process instead of the controller. We propose another procedure of estimating orders and delay-time using the fact that the process output can be represented by filtered output of ARMA model. Simulation example will show usefulness of the procedure.

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