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Conference Program of WCICA 2012

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<strong>Conference</strong> <strong>Program</strong> <strong>WCICA</strong> <strong>2012</strong><br />

On Definition and Construction <strong>of</strong> Lyapunov Functions for Boolean Networks,<br />

pp.1247–1252<br />

Wang, Yuzhen<br />

Li, Haitao<br />

Shandong Univ.<br />

Shandong U<br />

This paper investigates how to define and construct a Lyapunov function<br />

for Boolean networks, and presents a number <strong>of</strong> new results based<br />

on the semi-tensor product <strong>of</strong> matrices. A proper form <strong>of</strong> pseudo-<br />

Boolean functions is found, and the concept <strong>of</strong> (strict-)Lyapunov functions<br />

is thus given. It is shown that a pseudo-Boolean function in<br />

the proper form can play the role <strong>of</strong> Lyapunov functions for Boolean<br />

networks, based on which some Lyapunov-based stability results are<br />

obtained. Then, we study how to construct a Lyapunov function for<br />

Boolean networks, and propose a definition-based method. The study<br />

<strong>of</strong> illustrative examples shows that the new results/method presented in<br />

this paper work very well.<br />

◮ FrA08-2 13:50–14:10<br />

Finding all controllers for disturbance decoupling <strong>of</strong> Boolean control networks,<br />

pp.1344–1349<br />

Yang, Meng<br />

Chu, Tianguang<br />

Peking Univ.<br />

Peking Univ.<br />

We investigate a type <strong>of</strong> disturbance decoupling problem (DDP) <strong>of</strong><br />

Boolean control networks. Using semi-tensor product <strong>of</strong> matrices, the<br />

dynamics <strong>of</strong> Boolean control network is expressed in its algebraic form.<br />

All the necessary arguments <strong>of</strong> the functions <strong>of</strong> outputs are called<br />

output-friendly coordinates. In order to estimate the solvability <strong>of</strong> D-<br />

DP, we give a necessary and sufficient condition <strong>of</strong> the output-friendly<br />

coordinates being always in a known invariant subspace. Then it is<br />

computationally feasible to construct all the valid feedback control matrices.<br />

The logical function <strong>of</strong> each controller can be recovered from the<br />

obtained feedback control matrix. We further discuss the constraints <strong>of</strong><br />

the selection <strong>of</strong> the invariant subspace. Examples are provided to show<br />

the effectiveness <strong>of</strong> the proposed method.<br />

◮ FrA08-3 14:10–14:30<br />

New algorithm for finding fixed points and cycles <strong>of</strong> Boolean network,<br />

pp.2691–2694<br />

Suo, Jinghui<br />

Sun, Jitao<br />

Tongji Univ.<br />

Tongji Univ.<br />

Boolean networks have been successfully used in modeling biological<br />

systems. The fixed points, cycles and transient states that lead to them<br />

play an essential role to describe the structure <strong>of</strong> Boolean networks.<br />

In this paper we propose an algorithm to get all the fixed points and<br />

cycles <strong>of</strong> Boolean network by using the results <strong>of</strong> semi-tensor product<br />

and permutation. At last, an example is given to illustrate the efficiency<br />

<strong>of</strong> the obtained results.<br />

◮ FrA08-4 14:30–14:50<br />

Matrix Approach to Simulation and Bisimulation Analysis <strong>of</strong> Finite Automata,<br />

pp.2716–2721<br />

Xu, Xiangru<br />

Hong, Yiguang<br />

Lin, Hai<br />

Acad. <strong>of</strong> Mathematics & Sys. Sci., CAS<br />

Chinese Acad. <strong>of</strong> Sci.<br />

Univ. <strong>of</strong> Notre Dame<br />

In this paper, the simulation and bisimulation relations <strong>of</strong> finite automata<br />

are investigated using matrix-based method. To solve the problem,<br />

composition operations <strong>of</strong> automata are studied first and then the algorithms<br />

and criteria are provided to check the simulation and bisimulation<br />

relations <strong>of</strong> two automata. An illustrative example is also provided.<br />

◮ FrA08-5 14:50–15:10<br />

Approximation <strong>of</strong> Boolean Networks, pp.2280–2285<br />

Cheng, Daizhan<br />

Zhao, Yun-Bo<br />

Zhao, Yin<br />

Chinese Acad. <strong>of</strong> Sci.<br />

Univ. <strong>of</strong> Glasgow<br />

Acad. <strong>of</strong> mathematics & Sys. Sci., CAS<br />

The problem <strong>of</strong> approximation to large-scale Boolean networks is considered.<br />

First, we assume a large-scale Boolean network is aggregated<br />

into several sub-networks. Using the outputs(or inputs) <strong>of</strong> each<br />

sub-network as new state variables, a new simplified time-varying network<br />

is obtained. Then a time-invariant Boolean network is used to<br />

approximate each subsystem. Observed data are used to find the best<br />

approximating dynamic models. Finally, the aggregation method is investigated.<br />

FrA09 13:30–15:30 Room 311A<br />

Invited Session: Coordination <strong>of</strong> Multi-Agent Systems and Networked<br />

Systems With Constraints and Uncertainties<br />

Chair: Chen, Zengqiang<br />

Co-Chair: Cheng, Long<br />

Nankai Univ.<br />

Inst. <strong>of</strong> Automation, Chinese Acad. <strong>of</strong> Sci.<br />

◮ FrA09-1 13:30–13:50<br />

Discarded Consensus <strong>of</strong> Multi-Agent Systems with State Constraint,<br />

pp.3460–3464<br />

Liu, Zhongxin<br />

Chen, Zengqiang<br />

NanKai Univ.<br />

Nankai Univ.<br />

This work addresses the consensus problem <strong>of</strong> multi-agent systems<br />

(MAS) with state constraint, while very few researchers consider such<br />

constraint in their study <strong>of</strong> consensus. A simple distributed algorithm<br />

named discarded consensus algorithm is proposed for weighted directed<br />

multi-agent systems. The proposed method can ensure the MAS<br />

reaching consensus while keeping the state estimate <strong>of</strong> each agent<br />

within its own constraint if the digraph is strongly connected and the<br />

initial state <strong>of</strong> each agent is within its constraint. Network <strong>of</strong> agents with<br />

both fixed and switching communication topologies are investigated in<br />

this paper. The convergence <strong>of</strong> the presented algorithms is analyzed<br />

theoretically and numerical simulations are provided to demonstrate the<br />

effectiveness <strong>of</strong> the theoretic results.<br />

◮ FrA09-2 13:50–14:10<br />

Control Design for Flexible Hierarchical Formation <strong>of</strong> Multiple Robots,<br />

pp.3595–3600<br />

Tang, Yutao<br />

Hong, Yiguang<br />

Chinese Acad. <strong>of</strong> Sci.<br />

Chinese Acad. <strong>of</strong> Sci.<br />

In this paper, we consider flexible formation and related control design<br />

<strong>of</strong> multi-robot systems. A hierarchical structure is provided for flexible<br />

formation <strong>of</strong> unicycle robots. With the virtual hierarchy defined in light<br />

<strong>of</strong> interconnection graphs, the formation and related parameters can be<br />

changed in different levels <strong>of</strong> the whole structure. The formation control<br />

design is given from a leader-following viewpoint. Stability analysis is<br />

also provided after that.<br />

◮ FrA09-3 14:10–14:30<br />

Performance Analysis for Multi-Agent Coordination With Partial Measurable<br />

States Over Digital Networks, pp.863–868<br />

Li, Tao<br />

Acad. <strong>of</strong> Mathematics & Sys. Sci., Chinese Acad.<br />

<strong>of</strong> Sci.<br />

Xie, Lihua<br />

Nanyang Technological Univ.<br />

In this paper, we consider the performance <strong>of</strong> a class <strong>of</strong> distributed<br />

coordination algorithms <strong>of</strong> discrete-time second-order multi-agent systems<br />

with partially measurable states and a limited communication data<br />

rate. The distributed coordinated control law is based on an encodingdecoding<br />

scheme which integrates the state observation with encoding/decoding.<br />

The convergence time, the selection <strong>of</strong> controller parameters<br />

and the performance limit are discussed. We give upper bounds<br />

<strong>of</strong> the convergence time in terms <strong>of</strong> precision, control and network parameters.<br />

We develop a linear approximation <strong>of</strong> the spectral radius <strong>of</strong><br />

the closed-loop matrix with respect to the control gains and the algebraic<br />

connectivity <strong>of</strong> the communication graph, by which we show that for a<br />

connected network, 2-bit quantizers suffice for the exponential asymptotic<br />

synchronization <strong>of</strong> the states <strong>of</strong> the agents. Furthermore, it is<br />

shown that as the number <strong>of</strong> agents increases, the asymptotic convergence<br />

rate can be approximated as a function <strong>of</strong> the number <strong>of</strong> agents,<br />

the number <strong>of</strong> quantization levels (communication data rate) and the<br />

ratio <strong>of</strong> the algebraic connectivity to the spectral radius <strong>of</strong> the Laplacian<br />

matrix <strong>of</strong> the communication graph.<br />

◮ FrA09-4 14:30–14:50<br />

A Sampled-Data Based Average Consensus Protocol for Double-<br />

Integrator Multi-Agent Systems with Switching Topologies and Commu-<br />

98

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