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Volume 52, Issue 9
Displaying 1-7 of 7 articles from this issue
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Paper
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Kota YAMAMOTO, Shigeru YAMAMOTO2016 Volume 52 Issue 9 Pages 459-466
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSIn this paper, we propose an identification method to obtain a cellular automaton model based on l1-norm optimization. The cellular automaton model describes the transition of the discrete state on the discretized space in the discrete-time. The states of the cellular automaton change according to the transient rule which can be expressed by max and/or min operators. It is generally known that there are multiple expressions to describe the transient rule of the cellular automaton, however the simple expression is desirable to analyze the system to use the model. To obtain the simpler model from the multiple candidates, we cast the identification problem into an l1-norm optimization problem. We verify the effectiveness of the proposed method by two examples.View full abstractDownload PDF (396K) -
Hideo MUROI, Shuichi ADACHI2016 Volume 52 Issue 9 Pages 467-473
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSIn this paper, we consider an identification input design problem for multi-input single-output (MISO) systems described by transfer functions which have common poles, based on the deterministic identifiability condition. First, we derive an identifiability condition for the system using cyclic shifted M-sequences. The derived condition is similar to the condition for the system described by finite impulse response in previous work. However the derived condition achieves the shorter shift length and the shorter input length than the condition of previous one in many cases. Finally, we confirm the derived condition through a simple example.View full abstractDownload PDF (613K) -
Kei SENDA, RitsuSamuel OTSUBO, Yurika TANI2016 Volume 52 Issue 9 Pages 474-480
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSIn a general reinforcement learning problem, a learning policy for an estimated plant is applied to a real plant. However, if the difference between the two plants is large, the learning policy is not effective. Therefore, a learning policy for a variation plant set, including elements made by adding variations to the estimated plant, is obtained. However, the number of elements of the set is infinite. To solve this problem, we discretize the infinite plant set by using the relationships between the structures of the plants. The policy that is proper for all the elements of the finite set obtained by the discrete approximations is also proper for all the elements of the original infinite plant set. Using the relationships between the structures of plants and policy, the properness of policy, which is the solution of the relaxation problem for the finite plant set, is revealed. The effectiveness of the proposed method is demonstrated by numerical examples.View full abstractDownload PDF (584K) -
— Estimation of Road Noise in Car Cabin —Yoshiro TAKAMATSU, Noriaki FUJIKI, Yoshitaka DEGUCHI, Taketoshi KAWABE2016 Volume 52 Issue 9 Pages 481-489
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSReduction of noise in a car cabin due to road irregularities has been a subject of research for many years. For reducing such a noise, we proposed H2-based active structural acoustic control method that used road noise estimation models and we verified its feasibility on a test bench. In this paper, we propose road noise estimation method in driving condition. The structure of road noise estimation, the method to select accelerometer number and location, and system identification method are proposed. In order to avoid multicollinearity among acceleration signals, principal component analysis over frequency domain is used for non-parametric modelling. The estimation performance and robustness was verified by using driving experimental data.View full abstractDownload PDF (3857K) -
Mitsuyuki SAITO, Hiroto KIRITA, Takahiro ICHIMOTO, Yasuhide KOBAYASHI, ...2016 Volume 52 Issue 9 Pages 490-497
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSState feedback control assumes that all of the state power can be observed. However, all of the state power cannot be observed in fact. As a solution in such a case, output feedback control of performing feedback control directly without using an observer from the output of the system detected by the sensor is proposed. Considering an actual system, various noises mix in the observation process by a sensor, and when controlling, it is thought that it has a certain influence. However, about the proposed output feedback control, observation noise is not included in the system. In this paper, we consider a robustness of a certain kind over the observation noise of output feedback control, and we show a means by which a upper bound of the power spectral density of observation noise evaluates the influence of the observation noise which is known.View full abstractDownload PDF (1261K) -
Takashi IRITA, Takumi SHINOHARA, Toru NAMERIKAWA2016 Volume 52 Issue 9 Pages 498-506
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSIn this paper, we study detection problem of replay attacks on smart grid. A smart grid is operated as if it is a Cyber-Physical System with solid links between its calculation and its material constituents, hence ensuring cyber security has been an important role. The goal of this paper is to detect replay attack that is one of cyber attacks on the sensors of a control system. We propose a detecting method adding intentional noise to not only sensors as code signal but also input. Replay attack can immediately be reflected by using fault diagnosis matrices that are composed of the estimator and observed values even if code signal is decrypted. Finally, we show simulation results to analyze effectiveness of the proposed method.View full abstractDownload PDF (1173K) -
Masahiro YASUDA, Tatsuya IBUKI, Hiroshi SUZUKI, Mitsuji SAMPEI2016 Volume 52 Issue 9 Pages 507-515
Published: 2016
Released on J-STAGE: September 29, 2016
JOURNAL FREE ACCESSThis paper proposes a novel pose (position and attitude) control law for hexrotors composed of six rotors. Since hexrotors have the potential to control full 6 degrees of freedom, we can apply two major kinds of control methods to them. One is a linear control scheme for a linearly approximated hexrotor model, which can make a hexrotor tilt when it moves in the horizontal direction. The other is a feedback linearization method which enables us to control 6 degrees of freedom of it individually. For these methods, the former can often be suitable for large translational movement and the latter to control the pose precisely. However, there exists no research on combination of both controllers. In view of this fact, this paper proposes a novel continuous switching control method using a weighting function. Here, the weighting function is built by dynamic manipulability based on given hexrotor structure. Concretely speaking, the two kinds of controllers continuously switch based on the relation between dynamic manipulability and pose errors for desired values. Furthermore, we give stability analysis and demonstrate the validity of the present method via simulation.View full abstractDownload PDF (2485K)
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