The problem of robust stabilization for a class of uncertain networked controlsystems （NCSs） with nonlinearities satisfying a given sector condition is investigated in this paper. By introducing a new model of NCSs...
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The problem of robust stabilization for a class of uncertain networked controlsystems （NCSs） with nonlinearities satisfying a given sector condition is investigated in this paper. By introducing a new model of NCSs with parameter uncertainty, network-induced delay, nonlinearity and data packet dropout in the transmission, a strict linear matrix inequality （LMI） criterion is proposed for robust stabilization of the uncertain nonlinear NCSs based on the Lyapunov stability theory. The maximum allowable transfer interval （MATI） can be derived by solving the feasibility problem of the corresponding LMI. Some numerical examples are provided to demonstrate the applicability of the proposed algorithm.
Several simulation tools are used to evaluate network performance including OMNeT++. In this paper, a case of topology control (TC) in WSNs is simulated by considering its interaction with MAC layer and routing based ...
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ISBN:
(纸本)9781424422012
Several simulation tools are used to evaluate network performance including OMNeT++. In this paper, a case of topology control (TC) in WSNs is simulated by considering its interaction with MAC layer and routing based on the SensorSimulator framework. Some ways to improve the simulation efficiency are described. Finally, the simulation results are given.
With very rich real-time data in DCS, how to turn real-time data into process-monitoring information and to present it effectively to the users, have been a difficulty of designing DCS-human interface for the process-...
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With very rich real-time data in DCS, how to turn real-time data into process-monitoring information and to present it effectively to the users, have been a difficulty of designing DCS-human interface for the process-monitoring. This paper presents an information system model for the production process monitoring using IDEF0*. By putting into several levels of monitoring demand, the paper provides a design of human-machine interface for the monitoring information, fault reasons, operation scene and incidence. With this method, DCS monitoring system was designed for the distillation process as an example, and the effectiveness of this method was illustrated.
Although numerous proposals have been made for ad hoc network routing protocols, not all of them are suitable for the wireless sensor networks in home automation (WSHA). Selecting the most appropriate routing protocol...
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Although numerous proposals have been made for ad hoc network routing protocols, not all of them are suitable for the wireless sensor networks in home automation (WSHA). Selecting the most appropriate routing protocols for WSHA requires good knowledge of its particular characteristics and requirements. In this paper, we analyze the basic characteristics and requirements of WSHA, and evaluate some popular routing protocols for their suitability to WSHA. We also provide recommendations for optimizing the protocols for the best WSHA performance.
An Online Kernel Learning based Adaptive control (OKL-AC) framework for discrete-time affine nonlinear systems is presented in this paper. A sparsity strategy is proposed to control the complexity of OKL identificatio...
An Online Kernel Learning based Adaptive control (OKL-AC) framework for discrete-time affine nonlinear systems is presented in this paper. A sparsity strategy is proposed to control the complexity of OKL identification model, meanwhile to make a trade-off between the demanded tracking precision and the complexity of the control law. The forward increasing and backward decreasing learning stages are performed, both incorporating efficient recursive updating algorithms. Owing to these advantages, the adaptive control law based on the OKL identification model is easily obtained and can be efficiently updated. Numerical simulations show that the proposed simple OKL-AC strategy has satisfactory performance, including good tracking performance and fast learning ability, in both deterministic and stochastic environments.
A novel online identification method is developed for nonlinear multi-input multi-output process modeling issue, which is based on kernel learning framework and named as online kernel learning (OKL) algorithm in this ...
A novel online identification method is developed for nonlinear multi-input multi-output process modeling issue, which is based on kernel learning framework and named as online kernel learning (OKL) algorithm in this paper. This proposed approach can adaptively control its complexity and thus acquire controlled generalization ability. The OKL algorithm performs first a forward increasing for incorporating a “new” online sample and then a backward decreasing for pruning an “old” one, both in a recursive manner. Furthermore, the prior knowledge about process can be easily integrated into the OKL scheme to improve its performance. Numerical simulations on a fed-batch penicillin fermentation process show that the proposed OKL algorithm can learn adaptively the dynamics of the process using relatively small samples, indicating the OKL is an attractive online modeling method for fermentation process.
A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into t...
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A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into this system, when feedback was available, this system could compute the control output and update the plant model with the plant output, otherwise, compute the control output based on the plant model output instead of plant output. On the condition that the plant was SISO and the error between plant and model existed, the necessary and sufficient condition for closed-loop stability of this system was derived. Simulation indicates that the range of model error within which this system is stable is easy to be derived by using this necessary and sufficient condition.
This note concerns the delay-dependent robust stability analysis for uncertain singular time-delay systems. The parameter uncertainty is assumed to be norm-bounded and possibly time-varying, while the time delay consi...
This note concerns the delay-dependent robust stability analysis for uncertain singular time-delay systems. The parameter uncertainty is assumed to be norm-bounded and possibly time-varying, while the time delay considered here is assumed to be constant but unknown. By using a new Lyapunov-krasovskii functional which splits the whole delay interval into two subintervals and defines a different energy function on each subinterval, some delay-dependent conditions are presented for the singular time-delay system to be regular, impulse free and robustly stable. The obtained delay-dependent criteria are effective and less conservative than previous ones, which are illustrated by numerical examples.
This note is concerned with the absolute stability analysis for time-delay Lurie controlsystems with nonlinearity located in an infinite sector and finite one. By using a new Lyapunov-Krasovskii functional that split...
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This note is concerned with the absolute stability analysis for time-delay Lurie controlsystems with nonlinearity located in an infinite sector and finite one. By using a new Lyapunov-Krasovskii functional that splits the whole delay interval into two subintervals and defines a different energy function on each subinterval and introducing some free-weighting matrices, some new delay-dependent robustly absolute stability criteria are presented in terms of strict linear matrix inequalities (LMIs). The obtained delay-dependent criteria are less conservative than previous ones, as are illustrated by numerical examples.
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