This paper proposes a method of model-based fault detection that is insensitive to the uncertainties due to unknown parameter errors whereas it is highly sensitive to the component failures. The proposed method is applied to the sensor failure detection of a smart structure control system and numerical simulation results show that the present approach is effective in suppressing disturbances due to model uncertainties and remarkably improves the detection performance.

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This paper describes about a concept of self-maintenance for self-sensing actuation system and how system identification and state estimation can be used to achieve self-maintenance. Currently, Self-sensing system that have concurrent actuation and sensing can be made by using a bridge circuit. However, hardware tuning is still needed due to the unstable nature of an imbalanced bridge circuit. This problem becomes serious in the space environment where human beings may not be available to perform the maintenance. A method of achieving self-sensing actuation without a bridge circuit is proposed. in this study, Dynamics of this proposed system can be described as the state space expression with a direct transmission component. This means that the problem of balancing the bridge circuit is equivalent to the system identification and state estimation problem. The proposed method was verified with experimental results, demonstrating that smart structures can achieve self-maintenance.

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We study state feedback control of hybrid automata with forcible events. A predicate is said to be control-invariant if there exists a state feedback controller such that the predicate remains true in the controlled system invariantly. We prove that there always exists the supremal control-invariant subpredicate of a predicate given as a specification.

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Recently, we have proposed an optimal inverse system for linear-parameter-varying max-plus-linear (LPV-MPL) system by extending the conventional inverse systems for fixed parameter MPL systems. In the design method, the linear parametrized control law is given, and the parameters are optimized by solving the linear programming successively. However, from the applicational point of view, there are many cases where the behaviour of parameters has dynamical properties and cannot be changed directly. Therefore, this paper gives the optimal inverse system for LPV-MPL with the counter k-dependent parameters in order that we could take account of the dynamical behavior of the parameters.

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Traffic control systems are typical examples of hybrid systems as both continuous and discrete variables, such as the number of cars, their speeds, traffic signals and so on are involved in the system. For the modeling of hibrid systems, there exist various approaches based on discrete event system theory, which utilizes, for example, timed automaton, Petri net and so forth. The traffic control system can be often regarded as the system controlled by a logic-based controller. In addition if the control specifications are also given by logical expressions, it may not be difficult to modify the existing logic-based controller. In this paper, the traffic control system consisting of two crossings is taken for an examaple, one of the modeling methods using modal logic is proposed, and its applicability to control is considered.

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This paper discusses the finite-time optimal control problem via sampled-data control of a class of piecewise affine (PWA) systems, where the switching action of the discrete state is determined at each sampling time according to a condition on the continuous state.

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This paper, firstly, tries to make a model of the assembly skill based on a Mixed Logical Dynamical System (MLDS) framework, which includes both physical (continuous) dynamics and logical switching. In case of assembly skill, the resulting MLDS includes nonlinear constraints unlike the standard MLDS. This implies that the MLDS based optimal control problem for assembly skill leads to Mixed Integer NonLinear Programming(MINLP). It is also well-known that finding the solution for MINLP is much harder than that for MIQP. Therefore, secondly, this paper presents some ideas find the optimal solution for assembly skill with less computational amount. Finally, some simulation results on peg-insertion task are shown to verify the usefulness of our idea.

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In this article, we consider a dynamic model of TCP/AQM(Transfer Control Protocol/Active Queue Management) networks and derive the dynamic model using linear systems with self-scheduling parameters. Here we focus on the constraints on the maximum queue length and tcp window-size, which are the network resources in TCP/AQM networks, and design a state feedback controller considering the constraints.

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Slippage of an automobile often occurs during acceleration and braking. In this paper, we propose a traction control system design method by using the model-following sliding mode control, in which we consider the friction coefficient between the road surface and the tires as an uncertainty in the controlled object. We confirmed that the control system has good performance in simulations.

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PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.

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This paper is concerned with robust stabilization and robust H_∞ control of a class of uncertain systems. The class of the systems is continuous-time systems with norm-bounded time-varying parameter uncertainties. We first show relationships between robust H_∞ control via linear output feedback and a scaled H_∞ control problem and between quadratic stabilization and a standard H_∞ control problem for uncertain systems. These implies that a quadratic stabilizing controller for uncertain systems can be designed by solving a standard H_∞ controller. Next, the results are applied to a helicopter model. The model is likely to have identification error between the original model and its linear mathematical representation. It is shown that robust controllers designed for uncertain systems work effectively.

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Tracking a target robustly by vision is very difficult for mobile robot running on irregular terrain in natural environment, because the image deformation caused by rolling and pitching of the camera, as well as relative movement between the target and the camera, affect the tracking ability greatly in this task. One approach to cope with such problems is matching the target image with many affine transformed candidate images while tracking. But when the number of candidate images get larger, such approach is not available to real-time task due to the computational cost. In this paper we propose a new Robustness Analysis for Tracking (RAT) to improve the tracking ability. RAT is the analysis based on feature of the object image, where three parameters: ‘Detectability’, ‘Robustness for Depth (RBD)’ and ‘Robustness for Rotation (RBR)’ are defined. Much more robust templates can be found by analyzing the object image using RAT before the tracking task is performed. The experimental results will be shown to verify the effectiveness of this method.

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If actuators can work stably and their output characteristics are robust with varying load and frequency, it is very easy to design and control general-purpose machines that have this kind of load varying free actuators. We have proposed the control idea to make actuator robust with varying load, named Dynamic Impedance Matching of Actuator^[1], that the output of an actuator is not influenced by load at certain range of frequency. In this paper, we look into the stability condition of this control and find the relation ship of phase constraint between Dynamic Impedance Matching of Actuator and H infinity controller that represents the robust control, also try to make H infinity controller by hiring the idea of Dynamic Impedance Matching of Actuator.

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In this article we report the experimental results and the evaluation of control and communication systems for bilateral tele-operation systems. The proposed system consists of simple mechanical parts, real-time control subsystems, tele-communication subsystems and network systems. The two mechanical systems can make communications each other via TCP/IP or UDP/IP network protocols, which has appreciable time delay (transmission delay). The proposed system overcomes the degradation caused by the time-delay with robust control theory. By using the proposed method we can construct stable bilateral tele-operation systems with simple control algorithms. We have implemented the algorithms on RT-Linux systems and made some experiments on the IP network systems of JGN (Japan Gigabit Network). As a conclusion we can obtain a robust and stable tele-operation systems against time delay up to 2 seconds and some probabilistic disturbances.

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This paper is concerned with the automatic pouring system in the casting industy, and gives special consideration to both track to a moving mold line and sloshing suppression. The system is constructed with two-degrees-of-freedom control, and is designed using a Hybrid Shape Approach. The effectiveness of the proposed system is shown through experiments in liquid container transfer.

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Three types of pulse angle modulation are considered, namely i) pulse phase modulation, ii) pulse frequency modulation and iii) pulse repetition period modulation. The frequency spectrum of each type is investigated. Then implementing these types for inverters is discussed. The details of implementing pulse frequency modulation for inverters are given and some results are shown.

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In this paper, the speed and advance angle control method is described to drive an industrial low voltage SRM (Switched Reluctance Motor) for a forklift truck. This method is based on data by the real experiment. The low voltage SRM is difficult to achieve the desired dynamic speed because the rising time of current grows longer. Fuzzy logic is a flexible and general-purposed method of implementing non-linear function and as such it is useful in control applications. Therefore, we designed a fuzzy current controller to control the velocity of SRM appropriately. And this system is used the look-up table for advance angle control. We show that the proposed controller with fuzzy logic and look-up table has good performance for the nonlinear SRM in experiments and simurations.

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This paper presents a method to control the sway of a rotary crane by using a straight transfer transformation (STT) model. The STT model is built and its parameters are geometrically derived. Considering the variation of the rope length, optimal control of a rotary crane is solved using an optimization method of Davidon-Fletcher-Powell (DFP) so that the load has no sway at the end point of the transfer. The proposed control method using the STT model is demonstrated to be effective to reduce the influence of centrifugal force through simulation and experiments.

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The center of the ground reaction forces is useful to evaluate the balance of the biped system. Here, we consider where to control it when the foot has an asymmetrical structure like humaner being. Two control laws are examined from the view point of the ankle joint output and postural stability. In order to discuss which of two should be used for biped robot control, we measure the position of the center of the ground reaction forces for human upright posture.

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The simultaneous perturbation stochastic approximation(SPSA) is an extension of Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. In SPSA, since all parameters is perturbed simultaneously, it is possible to modify parameter with only two measurements of the evaluation function regardless of the dimension of parameter. We propose a parameter identification algorithm using SPSA. Simulation result shows a feasibility of the identification proposed here.

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In this paper, a method of estimating a set of frequency response of a stable plant from interval data of step response is given where no parametric model is assumed. Step response is approximated by a piecewise linear function, to which Fourier transform is applied, and the estimation problem is reduced to a linear programming problem. The result is shown graphically by vector locus and Bode diagram.

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In this paper, we discuss the meaning of the intermediate parameters introduced by the deterministic off-line identification method ¹⁾, which is performed by using input and output data with a constant steady state output response. It is shown that the intermediate parameters are the coefficients of the polynomial that is derived by the Taylor expansion of the plant around s = 0.

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This paper is concerned with a new RLS algorithm for time-varying parameters using an internal model and a stability margin of the algorithm. This algorithm is given from a standpoint that the varying parameter changes can be approximated as a polynomial function of time with a finite degree. So the proposed algorithm involves an internal model of the function in the adaptive loop so as to consider an influence of the varying parameters. A sufficient condition for assuring stability of the proposed algorithm is given by the output strictly passive and small-gain theorem. Furthermore, the stability margin of the algorithm is shown and a simulation is down to perform the validity of the new LMS algorithm.

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In this paper, we propose two identification methods for a class of multi-input multi-output discrete-time linear parameter-varying systems. The methods are based on the subspace state space metbod (4SID). We present numerical simulations to demonstrate the efficacy of the methods.

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In the present study, the on-line measurement of the specific index reflecting the welder skill level has been experimentally studied for the purpose of human skill quantification. Three welders with different level of skill performed the TIG (tungsten inert gas arc welding) welding task of first layer on single V groove in a flat position with different welding conditions. It has been confirmed that the specific behavior of the welder with different skill level has been successfully estimated.

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Ocular information such as pupil size, eyeblink or eye gaze point can be utilized for diagnosis of cerebral function disorders. There are a lot of methods of measuring ocular information, but accuracy and simplicity are required to be applied for diagnosis of cerebral function disorders. In this paper, the relationship between ocular information and cerebral function disorders is described first, followed by the review of methods of measuring ocular information. And system configuration of Eye-Sensing HMD which can not only provide three-dimensional images but also measure ocular information is described. Then measurement system to measure ocular information by using Eye-Sensing HMD and its experimental study for diagnosing cerebral function disorders are described.

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The Parasitic Humanoid (PH) is a wearable robot for modeling nonverbal human behavior. This anthropomorphic robot senses the behavior of the wearer and has the internal models to learn the process of human sensory motor integration thereafter it begins to predict the next behavior of the wearer using the learned models. When the reliability of the prediction is sufficient, the PH outputs the errors from the actual behavior as a request for motion to the wearer. Through symbiotic interaction, the internal model and the process of human sensory motor integration approximate each other asymptotically.

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The investigation of the human characteristic on visual and auditory reaction time is very important for making high-reality virtual environment and safe uses of multimedia machines. Up to now, human visual and auditory mechanisms have been investigated as two separate systems. In this study, we pay attention to human characteristics of the visual and auditory calculation processing, and the reaction time and electroencepha-logram (EEG) are measured. Based on the measurement results and the results in our previous functional magnetic resonance imaging (fMRI) study, the authors discuss the difference between the visual and the auditory information processing.

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In this paper, we have studied crossover for graph-based programs. Graph crossover is unsatisfactory on several counts to divide and combine graphs unlike with string or tree crossover, because relatively large number of random factors should be inevitable to operate crossover. In this paper, we have compared the performance of several crossover operators for Genetic Network Programming experimentally. The experimental results show the advantages and drawbacks of each method.

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Many evolutionary computation methods have been studied. Recently, a new method called Genetic Network Programming(GNP), which is based on Genetic Algorithm and Genetic Programming has been proposed. GNP has a network structure and can search for solutions effectively. GNP has been mainly applied to dynamic problems. In this paper, GNP is extended to generating programs in the static environment.

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In this paper, we propose a new method for shape recognition of a pillar-like object using 1-D ultrasonic sensor array and GA. The proposed system consists of an ultrasonic transmitter, an ultrasonic sensor array, a signal processing unit, and a recognition unit. In the signal processing unit, the peak positions and their values, and the positions of the inflection points and their values. of ultrasonic waves that are outputted from the sensor array unit are acquired. These valnes and positions are inputted into the recognition unit, which consists of the GA, for object identification. We designed and built a prototype system, and we tested this system by attempting to identify six objects, each of which was a cylinder or a rectangular prism. The experimental results showed near-perfect object identification.

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A purpose of this research is to propose a scene recognition method for real-time visual servoing of a manipulator, which has robustness for lighting environments. We have verified the robustness of the proposed method against lighting conditions variations and the effectiveness of the method for real-time recognition using fish catching experiment by visual servoing of a hand-eye robot.

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We propose a method to acquire machine intelligence to utilize unknown dynamics, which is designated as “motion intelligence”. The motion intelligence is defined as an ability that the machine can find by itself a way using its own but unknown dynamics. We confirmed that the 1-link mobile manipulator could find the effective swinging of link that makes it travel.

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In this paper, an unique method is proposed in order to solve the optimal problems where it takes a long time to calculate the objective function. Recently, various methods for a lot of optimal problems have been developed using advanced technologies. LeSurf (Learning with Surface Fitting), presented in this paper, aims to obtain the global optimum in less searching steps than the conventional methods.

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A method for verifying operationality of artifacts is proposed focusing on interaction between artifacts and operator. We have already proposed a model for representing artifacts in which the close interactions among “states and operations”, “designer’s intention” and “physical phenomena” are represented. The interaction results in a network representation of state transitions and operations. We will discuss the way to apply the graph operations on this network for verifying artifacts.

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The real option approach draws much attention toward an optimal investment problem under uncertainty. This paper shows that the optimal investment rule obtained by the method is strongly dependent on the process employed as the model of price fluctuations. The mean reverting process would be more reasonable than the geometric Brownian motion when considering the characteristics of the price fluctuation.

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Group buying is seen as an effective form of electronic commerce and a promising field for applying agent technologies. When buyers cooperate with each other, a seller can discount the price of a good. In existing group buying sites, each buyer’s preference may not be reflected effectively. Furthermore, when there are several identical goods in the same category, buyers are often distributed into several different coalitions. Each buyer cannot expect much discount. We propose a decision support system for group buying based on buyers’ preferences. In our system, each buyer’s preference is reflected effectively by integrating member preferences by using AHP.

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In this paper, a new method for combinatorial optimization problems by means of multi-agent system is proposed. In our method, a lot of agents explore in the solution space, locally and globally, for finding an optimal solution. A part of experimental results is also shown in order to demonstrate the effectiveness of our method.

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The discretized maps of gradient models with Euler’s method generate chaos, which can be used for global optimization by applying the chaotic annealing. In this paper, we apply this approach to solve the traveling salesman problem. We formulate it as continuous optimization problems with particular constraints, and newly derive gradient projection dynamics whose discretized maps generate chaos on a simplex.

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With 3-D vision measuring, camera calibration is necessary to calculate parameters accurately. In this paper, we present an algorithm for camera calibration using perspective ratio of a grid type frame with different line widths. It can easily estimate camera calibration parameters such as focal length, scale factor, pose, orientations, and distance. But, radial lens distortion is not modeled. The advantage of this algorithm is that it can estimate the distance of the object. To validate proposed method, we set experiments with a frame on rotator at a distance of 1.2[m] from camera and rotate the frame from -60 to 60 degrees. We have investigated the distance error affected by scale factor or different line widths and experimentally found an average scale factor that includes the least distance error with each image. The average scale factor tends to fluctuate with small variation and makes distance error decrease. Compared with classical methods that use stereo camera or two or three orthogonal planes, the proposed method is easy to use and flexible. It advances camera calibration one more step from static environments to real world such as autonomous land vehicle use

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Automatic acquisition of object using model’s appearances from an environment is proposed in this paper. Robots directly interact with a defined environment in order to extract an object shape from its scene. The robot extracts targeted object’s appearances creating eigenspace and stores it into the memory server (or intelligent data carrier). Eigenspace is constructed successfully every times when a new object appears, and various appearances accumulated gradually. A closed sequence of appearances is generated from its accumulated shapes, which is used for recognition of object. Experimental results of object’s accumulation and recognition show the effectiveness of the proposed method

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We developed a silicon retina system, and applied it to target tracking in natural scenes. In this system, a silicon retina which is capable of smoothing and contrast enhancement on input images is used to detect edges of the object in real time. Experimental results have shown that this system can track the target in real time.

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This paper presents a new incremental map building and self-positioning method for an unmanned conveyance car in a closed area such as in the factory storehouse. To navigate the conveyance car, accurate map is required. The proposed method is based on the detection of straight line segment measured by laser rangefinder. The proposed method was validated by experiments.

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Automonous Ground Vehicle (AGV) is one of the key technologies utilized in the Intelligent Transport Systems (ITS), a sophisticated road traffic information system in many countries. Especially, the robust and real-time lane detection under outdoor environment is prerequisite key technology for AGV. In order to apply outdoor AGV, we employ the omni-directional camera.

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The intelligence for harvesting machine of tropical fruits requires the ability of image analysis on natural background, which more complicate than image analysis on unique color background that is used for grading fruits and vegetables. In some case, we can easily distinguish fruit areas in natural background image by color. However, finally, we have to use shape analysis for identification and getting exactly boundary positions. This research intends to detect position of fruits by its shape and used Elliptic Fourier Descriptors to describe the typical shape. Then, we deform the typical shape in the spatial frequency domain by scaling, rotating, and phase shifting and match with the interesting image to get the maximum likelihood. However, the matching process to determine all likelihood takes a long time because we have to inverse Fourier series and deform the parameters as many as possible to get enough accurate result. To optimize these problems, we use FFT for inverting the typical shape and the Genetic algorithm for searching the most likelihood because this problem is a problem depending on natural environment. Using Genetic algorithm, which is a random search algorithm, is suitable and can decrease position-searching time.

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Energy cost of greenhouses is the major concern in greenhouse management during winter time. Greenhouse energy consumption per day can be reduced by lowering the greenhouse temperature since energy consumption is approximately the liner function of different between inside and outside air temperature of greenhouse. However, Lower greenhouse temperature requires longer growth period. Total energy consumption is the product of these two factors, and is not simply calculated. A greenhouse energy consumption was constructed and was estimated using the developed model in this project.

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This paper describes operations and performance of an automated quality verification syetem for agricultural products and its main features. The system utilizes improved engineering designs and image-processing techniques and to convey and grade products. Basically are two inspection stages of the system can be identified; external fruit inspection and internal fruit inspection stage. Surface inspection is accomplished through processing of color CCD images while internal inspection is by special sensors for sugar and acid contents. X-ray sensor is incorporated to detect biological defects.

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In this study the both mercury free lamp and conventional lamp was used for growing lettuce, which means the R/FR environment was changed for one plant growth interval between R/FR>3.0 and R/FR<1.0. From the experiment, the growth speed was faster and the leaf shape and leaf area was larger than growing the lettuce under single lamp.

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In this study, we make a proposal on the way of controlling plant shape and height. Plant growth can be controlled by changing lighting condition. In order to change lighting condition, we adopted the method to use a covering material that absorbs specific wavelength radiation. The plants grown under covering materials differ from that under natural radiation.

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In this paper, we study a scheduling problem with resource constraints using the Petri nets based on the transitive matrix P-invariant. This work focused on the analysis of a cyclic schedule for the determination of the optimal cycle time and minimization of Work In Process (WIP for short). Especially, this paper deals with product FMS cyclic scheduling problem with each other products using the transitive matrix. And TPN slice are applied to analyze this FMS model. We can divide original system into subsystem using the transitive matrix and permutated these sub-nets for analyzing the optimal scheduling.

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