Abstract
〈Vol.6 No.5(2013.9)〉
Titles
[Contributed Papers]
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■ Model Predictive Control for Ecological Vehicle Synchronized Driving
Considering Varying Aerodynamic Drag and Road Shape Information
Kyushu University・Anan KAKU,The University of Tokyo・M.A.S. KAMAL,
Kyushu University・Masakazu MUKAI and Taketoshi KAWAB
This paper presents an ecological vehicle synchronized driving control
system that aims at reducing overall fuel consumption of the vehicles in
a group. A centralized system for controlling the vehicles in a group has
been developed using the model predictive control method considering vehicle-aerodynamics
and the resistance due to road slopes. The ecological synchronized driving
system is simulated on a typical road with up-down slopes for high speed
driving. Its fuel saving performance is compared with a conventional vehicle
following system. Computer simulation results reveal a significant improvement
in fuel economy using the proposed ecological synchronized driving control
system.
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■ Periodic Time-Varying Model-Based Predictive Control of Air-Fuel Rratio
in Gasoline Engines under Individual fuel Injection
Sophia University・Yinhua LIU and Tielong SHEN
The air-fuel ratio is a key performance of engines. In multi-cylinder internal-combustion
(IC) engines, imbalance in fuel paths between cylinders exists, which demands
for modifying fuel injection of individual cylinders. This paper applies
the model predictive control strategy to air-fuel ratio control through
modifying the fuel injection command for individual cylinders. The control
scale is with BDC scale where BDC is the event that the piston reaches
the bottom dead center. Experimental results show that the air-fuel ratio
can be controlled to the objective value even when unknown disturbance
on fuel injectors exists.
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■ Evaluation of the Communication Load of a Real-Time Fieldbus Using Concepts
of Periodical Communication
Waseda University・Yoshitsugu MORIOKA and Yoshiharu AMANO
To implement and design an application of a real time fieldbus segment,
engineers are obliged to estimate the communication load factor of the
communication to secure the operation. According to the recent increase
of the node number per segment, communication load management becomes a
real issue. This paper gives the definition of the communication load and
the procedure to estimate and measure the communication load of a real
time fieldbus: FOUNDATIONTM fieldbus and thus establish the theoretical
and experimental base of the guidance to keep the periodi-cal/stationary
communication load less than 70%
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■ Passivity-Based Visual Feedback Pose Regulation Integrating a Target
Motion Model in Three Dimensions
Tokyo Institute of Technology・Tatsuya IBUKI,Takeshi HATANAKA and Masayuki
FUJITA
This paper investigates passivity-based visual feedback pose regulation
whose goal is to control a vision camera pose so that it reaches a desirable
configuration relative to a moving target object. For this purpose, we
present a novel visual feedback estimation/control structure including
a vision-based observer called visual motion observer under the assumption
that a pattern of the target motion is available for control. We first
focus on the evolution of the orientation part and the resulting estimation/control
error system is proved to be passive from the observer/control input to
the estimation/control error output. Accordingly, we also prove that the
control objective is achieved by just closing the loop based on passivity.
Then, we prove convergence of the remaining position part of the error
system. We moreover extend the present velocity input to force/torque input
taking account of camera robot dynamics. Finally, the e ectiveness of the
present estimation/control structure is demonstrated through simulation.
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■ Velocity-robust Gait Analysis for Human Identification through Constrained
Learning of Stochastic Switched Auto-Regressive Model
Nagoya University・Dapeng ZHANG,Shinkichi INAGAKI and Tatsuya SUZUKI
Gait recognition is a promising non-intrusive biometric method. A robust
and compact gait model is desirable in many security applications from
public facilities to personal devices. Shape cues are chosen in most current
researches except a few adopting dynamical features exclusively. And most
of these systems are velocity-dependent. In order to explore more features
of gait and to fit the varying environments of different applications,
a new gait recognition model which synthesizes dynamic model and statistical
one is designed. A kind of dynamical features, angular variables with respect
to ankle joint, are adopted as the model’s input. The proposed model has
a circular structure consisted of 2 pairs of correlated states. A constrained
learning algorithm is proposed under the model’s special structure configured
according to a 2-link virtual passive walking model which plays an important
role both in the initialization and in the updating step. By evaluating
the recognition rates of different models, the velocity-robust characteristics
of the new model and its low computational load compared with conventional
HMM are verified.
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■ Simple Representation of the Critical Chain Project Management Framework
in a Max-Plus Linear Form
Hosei University・Hiroyuki GOTO,
Nagaoka University of Technology・ Nguyen THI NGOC TRUC and Hirotaka TAKAHASHI
This paper derives simple formulas in max-plus algebra to make a robust
schedule for a project with atypical processes, based on the critical chain
project management framework. The derived form is classified as state-space
representation in control theory terminology, consisting only of simple
algebraic operations. Two types of time buffers can be easily applied to
achieve robustness.
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■ Fictitious Reference Iterative Tuning to Modified IMC for Unstable Plants
Kanazawa University・Hien THI NGUYEN.,Osamu KANEKO and Shigeru YAMAMOTO
This paper proposes a data-driven controller parameter tuning of the modified
internal model control (IMC),which was proposed by Yamada in 1999, for
unstable plants. Here the authors apply fictitious reference iterative
tuning (FRIT) to the parameterized modified IMC with only one-shot experimental
data. The proposed approach enables us to simultaneously obtain the optimal
controller for a desired performance and an appropriate model of the actual
plant, and it is applicable for unstable plants in both of the minimum
phase and the non-minimum phase cases.
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■ Reliable Decentralized Failure Diagnosis of Discrete Event Systems
Osaka University・Shuhei NAKATA and Shigemasa TAKAI
In most existing works on decentralized diagnosis of discrete event systems,
it is implicitly assumed that diagnosis decisions of all local diagnosers
are available to detect the failure. However, it may be possible that some
local diagnosis decisions are not available due to some causes. Letting
n be the number of local diagnosers, the notion of (n; k)-reliable codiagnosability
guarantees that any occurrence of the failure can be detected by using
arbitrary more than or equal to k local diagnosis decisions within a uniformly
bounded number of steps. In other words, even if at most n . k local diagnosis
decisions are not available, the failure can be detected by using the remaining
diagnosis decisions. In this paper, a method for verifying (n; k)-reliable
codiagnosability for any k is presented. Then, the delay bound within which
any occurrence of the failure can be detected by using arbitrary more than
or equal to k local diagnosis decisions is computed.
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■ H∞ Filter-Based SLAM with the Observation on an a priori Known Landmark
Keio University・Yoshihiro OKAWA and Toru NAMERIKAWA
The authors consider the simultaneous localization and mapping (SLAM) problem
with an H∞ filter and with an observation of a landmark that is known
a priori. With this observation, the system satisfies observability, and
the estimated error is suppressed and the determinant of its covariance
matrix becomes small compared with that of the original H∞ filter. As
a result, our proposed method avoids finite escape time, the divergence
of the error covariance matrix that occurs in the estimation when using
the original H∞ filter. We prove the convergence of the error covariance
matrix. In addition, with simulations and experimental results, we confirm
that finite escape time is avoided, that the derived theorems for the convergence
are correct, and that we can accurately estimate the state of the robot
and the environment.
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