研究会 (2017 年 10 月 30 日)
SICE 九州支部 制御理論と応用に関する研究会, 協和ダイナミクス設計論研究会 共催
日時: 10/30(月) 14:40～17:30
場所: 九州工業大学飯塚キャンパス セミナー室W406
講演1: Nonlinear observers robust to measurement disturbance in the ISS sense
(Prof. Hyungbo Shim, Seoul National University, South Korea; 14:40～15:40)
(シム ヒュングボ, ソウル大学, 韓国)
講演2: Robust Pareto suboptimal strategy for uncertain markov jump linear
stochastic systems with multiple decision makers
(Prof. Hiroaki Mukaidani, Hiroshima University, Japan; 15:50～16:40)
(向谷 博明, 広島大学)
講演3: Analyzing and tuning sublevel sets of Lyapunov functions for
interconnected iISS systems
(Prof. Hiroshi Ito, Kyushu Institute of Technology, Japan; 16:50～17:30)
(伊藤 博, 九州工業大学)
懇親会: 飯塚市内(当日案内) 18:00-
問合わせ先: 伊藤博 http://palm.ces.kyutech.ac.jp/~hiroshi
We begin with an analysis of nonlinear observers in terms of passivity.
By suitably defining input and output of the estimation error dynamics,
designing observer injection gain can be viewed as making the error
dynamics passive. This finding in turn leads to another interpretation
of reduced-order observer since the error dynamics of reduced-order
observere is nothing but the zero-dynamics of full-order error dynamics.
Then, we note that passivity property naturally leads to some
robustness, which is, in the case of observer, against measurement
disturbance. We will talk about recent results on nonlinear observers
robust to measurement disturbance in the ISS (input-to-state stability)
Speaker's biographcal sketch:
Hyungbo Shim received the B.S., M.S., and Ph.D. degrees from Seoul
National University, Korea, and held the post-doc position at University
of California, Santa Barbara till 2001. He joined Hanyang University,
Seoul, Korea, in 2002. Since 2003, he has been with Seoul National
University, Korea. He served as associate editor for Automatica, IEEE
Trans. on Automatic Control, Int. Journal of Robust and Nonlinear
Control, and European Journal of Control, and as editor for Int. Journal
of Control, Automation, and Systems. He was the Program Chair of
ICCAS 2014 and Vice-program Chair of IFAC World Congress 2008. His
research interes includes stability analysis of nonlinear systems,
observer design, disturbance observer technique, secure control systems,
In this study, a robust Pareto suboptimal strategy for
uncertain Markov jump linear stochastic systems (UMJLSSs) with
multiple decision makers is investigated. A guaranteed cost-control
principle is employed to obtain the conditions given using
a stochastic algebraic Riccati inequality (SARI), such that the
closed-loop stochastic system is exponentially mean square stable (EMSS),
having a cost bound. The minimization problem of the cost bound is
formulated, and the necessary conditions, which are obtained via the
set of cross-coupled stochastic Riccati equations (CCSAREs), are derived
with the help of the Karush-Kuhn-Tucker (KKT) conditions.
Finally, a numerical example is solved to demonstrate the effectiveness
and usefulness of the proposed strategy.
This talk forces on feedback interconnection of two nonlinear systems.
The component systems are assumed to be integral input-to-state
stability (iISS). iISS allows the state of a system to be unbounded even
for bounded external input, while in contrast, input-to-state stability
(ISS) guarantees the state to be bounded. The concept of iISS captures
inevitable dynamics arising from saturation and bilinearity.
Interestingly, the state going far away can be pulled back by connecting
an ISS system to it if the stability of the ISS system is strong enough.
A small-gain condition allows one to check if this mechanism kicks in.
The small-gain condition is merely a test. Constructing a Lyapunov
function of the feedback and investigating its sublevel sets can provide
one with useful information of system behavior, One may conjecture that
the magnitude of the state increases very large temporarily when
stability margins are small. The aim of this talk is to discuss this
conjecture and correct it. As expected, sublevel sets of a previously
available Lyapunov function is flattened extremely when stability
margins are small. It is, however, demonstrated that it is not
necessary, and a new Lyapunov function producing surprisingly better
sublevel sets is proposed.
Last modified: Tue March 10 12:11:55 JST 2015