Abstract
〈Vol.4 No.6(2011.12)〉
Titles
[Contributed Papers]
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■ Solving Bilevel Programming Problems Using a Neural Network Approach
and Its Application to Power System Environment
Waseda University・Shamshul Bahar YAAKOB,Junzo WATADA
In this paper, a hybrid neural network approach to solve mixed integer
quadratic bilevel programming problems is proposed. Bilevel programming
problems arise when one optimization problem, the upper problem, is constrained
by another optimization, the lower problem. The mixed integer quadratic
bilevel programming problem is transformed into a double-layered neural
network. The combination of a genetic algorithm (GA) and a meta-controlled
Boltzmann machine (BM) enables us to formulate a hybrid neural network
approach to solving bilevel programming problems. The GA is used to generate
the feasible partial solutions of the upper level and to provide the parameters
for the lower level. The meta-controlled BM is employed to cope with the
lower level problem. The lower level solution is transmitted to the upper
level. This procedure enables us to obtain the whole upper level solution.
The iterative processes can converge on the complete solution of this problem
to generate an optimal one. The proposed method leads the mixed integer
quadratic bilevel programming problem to a global optimal solution. Finally,
a numerical example is used to illustrate the application of the method
in a power system environment, which shows that the algorithm is feasible
and advantageous.
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■ New Results of Energy-Based Swing-up Control for a Rotational Pendulum
Okayama Prefectural University・Seiji TANAKA,Xin XIN,TaigaYAMASAKI
In this paper, we revisit the energy-based swing-up control problem for
a rotational pendulum. Different from the existing energy-based control
solution, first, we present a necessary and sufficient condition such that
the control law has no singularities for all states of the rotational pendulum.
Next, we carry out a global motion analysis of the pendulum, and we remove
the previous required constraint on the initial state of the pendulum and
the control parameters for preventing the pendulum getting stuck at the
downward equilibrium point by revealing that the point is a saddle. Specifically,
we show that the Jacobian matrix evaluated at the point has two and two
eigenvalues in the open left- and right-half planes, respectively. We prove
that the pendulum will eventually be swung up into the basin of attraction
of any (locally) stabilizing controller for all initial conditions with
the exception of a set of Lebesgue measure zero. Finally, we validate the
presented theoretical results via numerical simulation. Our simulation
results show that the swing-up control can be achieved quickly under the
improved conditions on the control parameters.
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■ Online Signature Verification System for Kaisyo Script Based on Structured
Learning and Segmentation of HMM
Nagoya University・Dapeng ZHANG,Shinkichi INAGAKI,Tatsuya SUZUKI,and Naoki KANADA
This paper presents a new Hidden Markov Model (HMM) for the online signature
verification of oriental characters such as Japanese and Chinese. These
oriental characters usually consist of many individual strokes such as
dots and straight lines. Taking into account of this characteristic, a
new HMM is proposed, which is composed of many sub-models each of which
corresponds to an individual stroke. In addition, the ‘pen-up’ state
which represents the movement between strokes is explicitly introduced.
Then, a parameter re-estimation scheme for this special class of HMM is
derived exploiting the structure of the proposed HMM. Thanks to the structured
learning mechanism, the
proposed HMM not only can drastically reduce the computational time necessary
for the learning process but also shows higher recognition performance
for the rejection of the skilled forgery. Finally, the usefulness of the
proposed scheme is demonstrated by comparing it with conventional models.
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■ Hybrid Speaker Recognition Using Universal Acoustic Model
Keio University・Jun NISHIMURA and Tadahiro KURODA
We propose a novel speaker recognition approach using a speaker-independent
universal acoustic model (UAM) for sensornet applications. In sensornet
applications such as “Business Microscope”, interactions among knowledge
workers in an organization can be visualized by sensing face-to-face communication
using wearable sensor nodes. In conventional studies, speakers are detected
by comparing energy of input speech signals among the nodes. However, there
are often synchronization errors among the nodes which degrade the speaker
recognition performance. By focusing on property of the speaker’s acoustic
channel, UAMcan provide robustness against the synchronization error. The
overall speaker recognition accuracy is improved by combining UAM with
the energy-based approach. For 0.1 s speech inputs and 4 subjects, speaker
recognition accuracy of 94% is achieved at the synchronization error less
than 100ms.
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■ Sampled-Data Consensus Control for Nonlinear Multi-Agent Systems of
Strict-Feedback Form with Application to Marine Systems
Shizuoka University・Hitoshi KATAYAMA
Sampled-data consensus control for nonlinear multi-agent systems of strict-feedback
form is considered. By using a change of state variables and an input transformation,
the discrete-time double-integrator dynamics is derived from the Euler
approximate model of each agent and discrete-time consensus control laws
are designed. Then by applying the nonlinear sampled-data control theory,
it is shown that the designed control laws achieve sampled-data consensus
for
nonlinear multi-agent systems in the continuous-time semiglobally practically
uniformly asymptotically stable (SPUAS) sense. As an application of the
proposed design method, sampled-data consensus control for fully-actuated
ships is considered.
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■ Performance Bounds for Optimal Control of Polynomial Systems: A Convex
Optimization Approach
Toyota Technological Institute・Tanagorn JENNAWASIN,,
Michihiro KAWANISHI and Tatsuo NARIKIYO
This paper is concerned with an approach for a nonlinear optimal control of polynomial systems. The
Hamilton-Jacobi-Bellman (HJB) equation is relaxed into HJB inequalities.
Both an upper bound and a lower bound on the cost function, as well as
a suboptimal controller, can be computed from solutions of the resulting
inequalities. Solving the HJB inequalities can be cast as state-dependent
matrix inequalities (SDMIs), whose derivation is based on representation
of the given polynomial system in a linear-like form. The resulting SDMI
for the upper-bound computation is nonconvex in the decision variables,
and hence an iterative procedure is proposed to deal with the non-convexity.
On the other hand, the resulting SDMI for the lower-bound computation can
be written as a state-dependent linear matrix inequality, which is a convex
optimization problem solvable by existing numerical tools. Numerical examples
are provided to illustrate the proposed approach.
▲ ■ Configuration Consensus of Two Underactuated Planar Rigid Bodies
Tokyo Institute of Technology・Maclaurin HUTAGALUNG,Tomohisa HAYAKAWA
and Kobe University・Takateru URAKUBO
A consensus control framework for configuration of two underactuated planar
rigid bodies is developed. Specifically, we propose a series of control
laws that achieve asymptotic consensus between the underactuated planar
rigid bodies that possess small-time local controllability. The results
are predicated on the characterizations of the approximate solution and
the inversion algorithm for underactuated systems. Finally, we present
a numerical example to show the utility of the proposed approach.
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■ MIMO PID Controller Design Based on Integral-Type Optimal Servomechanism
and Its Extension to Model-Following-Type
National Defense Academy・Hiroyuki KONDO and Yoshimasa OCHI
This paper presents a design method of an MIMO integral preceded by proportional-derivative
(I-PD) controller based on an integral-type optimal servomechanism. The
proposed method consists of two steps. First, a given plant is represented
in a specific state-space form, and then an integral-type optimal servo
controller is designed. Although the resultant controller does not always
become a typical I-PD one, when the order of a given MIMO plant is equal
to or less than twice the number of the outputs, the resultant control
law is equivalent to an I-PD one. Moreover, the proposed I-PD
controller design can be extended to a model-following type by adding a
reference model and a feedforward compensator for a desirable output response.
Controller design examples and numerical simulation studies are carried
out in order to demonstrate that the proposed design method has sufficient
effectiveness.
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■ Electroencephalographic Denoising and Classification by Using Power
Spectrum Density Based Independent Component Analysis and Common Spatial
Pattern
Keio University・Abbas ORAND,Junichi USHIBA,
Fujita Health University・YutakaTOMITA,and Keio University・Satoshi HONDA
With the participation of 12 volunteers, the off-line application of independent
component analysis for automatic artefacts removal based on power spectral
density is investigated. By using the “range” values of the power spectra
of the independent components within the frequency range of 2 to 8 Hz along
with the integral values of the independent components in the range of
8 to 30 Hz, artificial independent components are automatically marked
and removed. The artefact-free electroencephalographic signal is further
classified using the method of common spatial pattern. It is found that
the modification of the conventional common spatial pattern can result
in a higher imagery task classification.
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■ On Predictive Control for Systems with Information Structured Constraints
Keio University・Toru NAMERIKAWA,
Tokyo Institute of Technology・Takeshi HATANAKA and Masayuki FUJITA
In this paper, we investigate a predictive control problem with information
structured constraints motivated by control of micro grid. A system with
information structures is defined as a system in which each subsystem collects
spatio-temporally different information. For the system, we consider a
predictive control law and the finite time constrained optimization problem
to be solved online is reduced to a deterministic convex programming problem.
Then, we reduce a control problem for a simple micro grid system to the
framework and the effectiveness of the proposed control and estimation
law is demonstrated through a numerical simulation.
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