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

(飯塚市川津680-4)

http://www.kyutech.ac.jp/information/map/iizuka.html

キャンパスマップの建物8番の4F。エレベータ降りて右裏側。

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-

参加者: 未定

(以上敬称略)

問合わせ先: 伊藤博 http://palm.ces.kyutech.ac.jp/~hiroshi

概要 1. 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) sense. 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, and synchronization. 2. 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. 3. 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