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Diagnosis on a sliding window for partially observable Petri nets

Amira Chouchane, Philippe Declerck (2022)

Kybernetika

In this paper, we propose an algebraic approach to investigate the diagnosis of partially observable labeled Petri nets based on state estimation on a sliding window of a predefined length h . Given an observation, the resulting diagnosis state can be computed while solving integer linear programming problems with a reduced subset of basis markings. The proposed approach consists in exploiting a subset of h observations at each estimation step, which provides a partial diagnosis relevant to the current...

Distributed accelerated Nash equilibrium learning for two-subnetwork zero-sum game with bilinear coupling

Xianlin Zeng, Lihua Dou, Jinqiang Cui (2023)

Kybernetika

This paper proposes a distributed accelerated first-order continuous-time algorithm for O ( 1 / t 2 ) convergence to Nash equilibria in a class of two-subnetwork zero-sum games with bilinear couplings. First-order methods, which only use subgradients of functions, are frequently used in distributed/parallel algorithms for solving large-scale and big-data problems due to their simple structures. However, in the worst cases, first-order methods for two-subnetwork zero-sum games often have an asymptotic or O ( 1 / t ) convergence....

Distributed classification learning based on nonlinear vector support machines for switching networks

Yinghui Wang, Peng Lin, Huashu Qin (2017)

Kybernetika

In this paper, we discuss the distributed design for binary classification based on the nonlinear support vector machine in a time-varying multi-agent network when the training data sets are distributedly located and unavailable to all agents. In particular, the aim is to find a global large margin classifier and then enable each agent to classify any new input data into one of the two labels in the binary classification without sharing its all local data with other agents. We formulate the support...

Distributed consensus control for discrete-time linear multi-agent systems with reduced-order observer

Wenhai Chen, Lixin Gao, Xiaole Xu, Bingbing Xu (2015)

Kybernetika

In this paper, we investigate multi-agent consensus problem with discrete-time linear dynamics under directed interaction topology. By assumption that all agents can only access the measured outputs of its neighbor agents and itself, a kind of distributed reduced-order observer-based protocols are proposed to solve the consensus problem. A multi-step algorithm is provided to construct the gain matrices involved in the protocols. By using of graph theory, modified discrete-time algebraic Riccati...

Distributed event-triggered algorithm for optimal resource allocation of multi-agent systems

Weiyong Yu, Zhenhua Deng, Hongbing Zhou, Xianlin Zeng (2017)

Kybernetika

This paper is concerned with solving the distributed resource allocation optimization problem by multi-agent systems over undirected graphs. The optimization objective function is a sum of local cost functions associated to individual agents, and the optimization variable satisfies a global network resource constraint. The local cost function and the network resource are the private data for each agent, which are not shared with others. A novel gradient-based continuous-time algorithm is proposed...

Distributed event-triggered tracking control of leader-follower multi-agent systems with communication delays

Jiangping Hu, Guanrong Chen, Han-Xiong Li (2011)

Kybernetika

As embedded microprocessors are applied widerly to multi-agent systems, control scheduling and time-delay problems arose in the case of limited energy and computational ability. It has been shown that the event-triggered actuation strategy is an effective methodology for designing distributed control of multi-agent systems with limited computational resources. In this paper, a tracking control problem of leader-follower multi-agent systems with/without communication delays is formulated and a distributed...

Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

Derui Ding, Qing-Long Han, Xiaohua Ge (2020)

Kybernetika

Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in...

Distributed output regulation for linear multi-agent systems with unknown leaders

Xinghu Wang, Haibo Ji, Chuanrui Wang (2013)

Kybernetika

In this paper, the distributed output regulation problem of linear multi-agent systems with parametric-uncertain leaders is considered. The existing distributed output regulation results with exactly known leader systems is not applicable. To solve the leader-following with unknown parameters in the leader dynamics, a distributed control law based on an adaptive internal model is proposed and the convergence can be proved.

Distributed resilient filtering of large-scale systems with channel scheduling

Lili Xu, Sunjie Zhang, Licheng Wang (2020)

Kybernetika

This paper addresses the distributed resilient filtering for discrete-time large-scale systems (LSSs) with energy constraints, where their information are collected by sensor networks with a same topology structure. As a typical model of information physics systems, LSSs have an inherent merit of modeling wide area power systems, automation processes and so forth. In this paper, two kinds of channels are employed to implement the information transmission in order to extend the service time of sensor...

Drugs in the Classroom: Using Pharmacokinetics to Introduce Biomathematical Modeling

G. A. Koch-Noble (2011)

Mathematical Modelling of Natural Phenomena

Pharmacokinetics is an excellent way to introduce biomathematical modeling at the sophomore level. Students have the opportunity to develop a mathematical model of a biological phenomenon to which they all can relate. Exploring pharmacokinetics takes students through the necessary stages of mathematical modeling: determining the goals of the model, deciphering between the biological aspects to include in the model, defining the assumptions of the model, and finally, building, analyzing, using, and...

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