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RISS 인기검색어
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- 주제어 : networked Markovian jump systems (검색결과 4 건)
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Shuai Chen,Jun Guo,Lifeng Ma 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.7
In this paper, the network-based sliding mode observer is investigated for a class of discrete nonlineartime-delay systems with stochastic communication protocol. The stochastic communication protocol is adopted toregulate the transmission order of the measurements from multiple sensor nodes, which could effectively avoid datacollisions. Under the scheduling of communication protocol, only one sensor node is allowed to get access to theshared communication network at each time step for data transmission. Moreover, the stochastic communicationprotocol is governed by a Markov chain, which converts the protocol-constrained system into a Markovian jumpsystem. It is the purpose to design a sliding mode observer such that, with the stochastic communication protocol,the trajectories of the estimation error system are driven into a band of the sliding surface and, in subsequent time,the sliding motion is mean-square asymptotically stable. By solving a minimization problem, the sufficient conditions for the desired sliding mode observer are established. Finally, an illustrative example is given to demonstratethe effectiveness of the proposed algorithm.
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박명진(Myeong-Jin Park),권오민(Oh-Min Kwon),박주현(Ju-Hyun Park),이상문(Sang-Moon Lee) 대한전기학회 2011 전기학회논문지 Vol.60 No.2
This paper proposes delay-dependent stability conditions of the fuzzy Markovian jumping Hopfield neural networks of neutral type with time-varying delays. By constructing a suitable Lyapunov-Krasovskii's (L-K) functional and utilizing Finsler's lemma, new delay-dependent stability criteria for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. A numerical example is given to illustrate the effectiveness of the proposed methods.
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Lijuan Nie,Dongyan Chen,Jun Hu 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.8
This paper is concerned with the problem of protocol-based sliding mode control for a class of uncertain discrete networked Markovian jump systems with stochastic perturbation and time-varying delays. An improved dynamic uniform quantizer for processing system output signals is proposed to mitigate communication constraints. Next, a Round-Robin protocol with zero-order holders is introduced in the communication channels from the controller to the actuators to reduce potential network congestion and collision. Then, in the output feedback case,a new sliding surface is designed based on the quantized output, and a mode-dependent sliding mode controller is constructed using protocol scheduling signals. Additionally, a sufficient condition is derived to ensure that the closed-loop system is asymptotically stable in the mean square on a specific sliding surface despite the existence of the time-varying delays. Subsequently, the reachability of the state trajectories is guaranteed, where a sufficient criterion is proposed by constructing new Lyapunov-Krasovskii functional as well as using the stability theory. Furthermore, the cone complementary linearization iteration algorithm is employed to tackle the non-convex problem during the controller design. Finally, a simulation example demonstrate the effectiveness and feasibility of the protocol-based sliding mode control method.
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Yuqian Lin,Guangming Zhuang,Jianwei Xia,Wei Sun,Junsheng Zhao 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.3
In this paper, the problem of asynchronous robust H∞ dynamic output feedback control for Markovian jump neural networks with norm-bounded parameter uncertainties and mode-dependent time-varying delays is investigated. The improved delay-dependent stochastic stability conditions and bounded real lemma are obtained by introducing the relaxation variables, which reduces the conservatism caused by boundary technology and model transformation. An improved Lyapunov-Krasovskii functional is constructed using linear matrix inequalities. On this basis, the solution of robust H∞ dynamic output feedback problem and sufficient conditions for solving the problem of asynchronous dynamic output feedback controller are given respectively. Asynchronous dynamic output feedback controller is constructed to ensure that the closed-loop mode-dependent time-varying delays Markovian jump neural networks achieve different convergence speeds. The given H∞ performance index is satisfied for the delays not bigger than a given upper bound. Numerical examples are employed to show the effectiveness and correctness of the method presented in this paper.
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