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We perform modal analysis of nonlinear swing dynamics of multimachine power systems based on the so-called Koopman operator. Modes derived through spectral analysis of the Koopman operator, called Koopman modes, provide a nonlinear extension of linear oscillatory modes and a novel technique for identification of coherent generators using finite-time data of swing dynamics.

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Local variational method is a technique to approximate intractable posterior distributions in Bayesian learning. In this study, we derive several inequalities regarding information divergences between the approximating posterior distribution and the true Bayesian posterior distribution. We also propose an efficient method to evaluate an upper bound of the marginal likelihood in the application to the kernel logistic regression model.

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A nonparametric statistical method called the empirical likelihood (EL) is applied to estimation problems with side information. Since EL is formulated as the KL-divergence minimization, a variant called the exponential tilting (ET) is also discussed that employs the divergence of the opposite direction. Theoretical analyses of the methods show that they are almost the same in the asymptotic performance but different in an algorithmic difficulty. Some numerical experiments confirm the above analyses.

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Most car navigation systems are aiming at the optimal route. In this research, Q value-based Dynamic Programming with Boltzmann distribution is used to distribute the cars and provide the global optimal routes according to the real-time traffic volumes. The purpose of this approach is to alleviate traffic congestions.

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In this paper we study the direct derivation method of optimal preview compensator dynamics for linear discrete-time systems. We derive the pair of preview compensator dynamics and Riccati difference equation by calculating the first variation of the performance index under the dynamics constraint.

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In this paper we propose a time multi hierarchical construction method of noncausal compensators considering multi objective of noncausal (preview) tracking control systems and performance evaluation. In this paper we assume sufficient real time processing for time multi hierarchical constructed noncausal compensation and introduce some compensator dynamics on multi time flow constructed virtually.

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The research on fuzzy control is various and performed. Fuzzy control is used for the control methods, such as automatic conveyance vehicles, such as a line trace robot and a factory, in many cases. It is verified whether fuzzy control is applicable to an object with a fast running speed like line trace car. In this research, the simplified reasoning method is used for the steering angle and the motor control of the line trace car. We tried to make smoothly controller without carrying out a zigzag run. About line tracer system, the car calculates a steering angle from the value of the sensor read during the run. Then, the line trace car calculates a motor output from the outputted steering angle.

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We will propose a nonlinear MPC using step input constraints and a cotinuation method.

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Load increase of server is inevitable problem considering trend of cloud computing in allover the computer field. Therefore, the grid computing has been expected rapidly, and new task about efficient use of surplus resource has been focused. This paper presents optimization of multigrid scheduling with respect to improvement of efficient resource use.

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The grid computing has advantage in sharing of many computer resource, but tends to be vulnerable in security. Then we propose security model of grid computing which can prevent information leakage, which is concerned by direct connection of each computer, using proxy server between client and server in grid environment executing job scheduling.

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This paper aims performance evaluation of data replication using speculative lock. The speculative lock is a method in which transaction processing is executed by temporarily neglecting conflict with write lock in the concurrency control, and abort conflicted transaction by detecting conflict at time of checkpoint. This paper considers experimental results of the performance evaluation.

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Evolutionary multiobjective optimization (EMO) has been one of the most active research areas in the field of evolutionary computation for the last decade. In this paper, first we overview a number of representative EMO algorithms. Next we explain the common framework of well-known and frequently used EMO algorithms such as NSGA-II and SPEA. Then we discuss hot issues in the EMO community. Finally we explain how EMO algorithms can be applied to multiobjective knowledge extraction. As an example, we show experimental results of EMO algorithms for multiobjective design of fuzzy rule-based classifiers where a number of non-dominated classifiers are obtained by a single run of an EMO algorithm.

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Recent expectations of what computational neuroscience contributes to the development of robotic technologies are remarkable. In dynamic environments, robots are required to work as an online and on-demand system, like humans do. However a simple conjunction of neural network models merely provides a pre-ordered circuit to control the robot, and then such a constructive approach casts doubt on the strength of the reality of brain-based robots. Nowadays, neuroscientists know the limitation of the traditional analytic science and start to explore a kind of the synthetic approach as the integration of past knowledge that have been investigated analytically. In this study, we discuss on the direction to the synthetic approach through the neuro-robotics.

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We approached the control mechanism of human quiet standing from conducting a novel psychophysical task paradigm. In our experiments, a subject was asked to control the inverted pendulum using their own electromyograms of the lower leg muscles.

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We propose the self evolving graph network as the method in which the environmental model is dynamically and real-time built. In our proposal method, node and path represent a symbolic memory of local environment and relationships between memories respectively. In this presentation, the validation result for availability of this method is shown.

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This paper describes the linguistic processing of robots. It is based on three stochastic computations: symbolization of motion, association between motion symbols and words, representation of word concatenation. This framework makes it possible for robots to interpret motions as sentences and generate motions from sentences.

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This lecture focuses on modeling and control design problems for internal combustion engines. First, in-cylinder engine model is introduced which describes the behavior of the dynamics of individual cylinders, and so-called mean-value model, which is much convenience for control design, is explained with demonstration of experimental validation. Then, several control design problems such as speed control and the cold-starting control will be introduced with the demonstration of experimental results.

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