摘要 :
In this paper, a novel consensus algorithm is presented to handle with the leader-following consensus problem for lower-triangular nonlinear MASs (multi-agent systems) with unknown controller and measurement sensitivities under a ...
展开
In this paper, a novel consensus algorithm is presented to handle with the leader-following consensus problem for lower-triangular nonlinear MASs (multi-agent systems) with unknown controller and measurement sensitivities under a given undirected topology. As distinguished from the existing results, the proposed consensus algorithm can tolerate to a relative wide range of controller and measurement sensitivities. We present some important matrix inequalities, especially a class of matrix inequalities with multiplicative noises. Based on these results and a dual-domination gain method, the output consensus error with unknown measurement noises can be used to construct the compensator for each follower directly. Then, a new distributed output feedback control is designed to enable the MASs to reach consensus in the presence of large controller perturbations. In view of a Lyapunov function, sufficient conditions are presented to guarantee that the states of the leader and followers can achieve consensus asymptotically. In the end, the proposed consensus algorithm is tested and verified by an illustrative example.
收起
摘要 :
In this paper, the problem of adaptive output feedback stabilization is investigated for a class of nonlinear systems with sensor uncertainty in measured output and a growth rate of polynomial-of-output multiplying an unknown cons...
展开
In this paper, the problem of adaptive output feedback stabilization is investigated for a class of nonlinear systems with sensor uncertainty in measured output and a growth rate of polynomial-of-output multiplying an unknown constant in the nonlinear terms. By developing a dual-domination approach, an adaptive observer and an output feedback controller are designed to stabilize the nonlinear system by directly utilizing the measured output with uncertainty. Besides, two types of extension are made such that the proposed methods of adaptive output feedback stabilization can be applied for nonlinear systems with a large range of sensor uncertainty. Finally, numerical simulations are provided to illustrate the correctness of the theoretical results.
收起
摘要 :
Understanding the water balance, especially as it relates to the distribution of runoff components, is crucial for water resource management and coping with the impacts of climate change. However, hydrological processes are poorly...
展开
Understanding the water balance, especially as it relates to the distribution of runoff components, is crucial for water resource management and coping with the impacts of climate change. However, hydrological processes are poorly known in mountainous regions due to data scarcity and the complex dynamics of snow and glaciers. This study aims to provide a quantitative comparison of gridded precipitation products in the Tianshan Mountains, located in Central Asia and in order to further understand the mountain hydrology and distribution of runoff components in the glacierized Kaidu Basin. We found that gridded precipitation products are affected by inconsistent biases based on a spatiotemporal comparison with the nearest weather stations and should be evaluated with caution before using them as boundary conditions in hydrological modeling. Although uncertainties remain in this data-scarce basin, driven by field survey data and bias-corrected gridded data sets (ERA-Interim and APHRODITE), the water balance and distribution of runoff components can be plausibly quantified based on the distributed hydrological model (J2000). We further examined parameter sensitivity and uncertainty with respect to both simulated stream-flow and different runoff components based on an ensemble of simulations. This study demonstrated the possibility of integrating gridded products in hydrological modeling. The methodology used can be important for model applications and design in other data-scarce mountainous regions. The model-based simulation quantified the water balance and how the water resources are partitioned throughout the year in Tianshan Mountain basins, although the uncertainties present in this study result in important limitations.
收起
摘要 :
This paper addresses the problem of output feedback sampled-data stabilization for upper-triangular nonlinear systems with improved maximum allowable transmission delay. A class of hybrid systems are firstly introduced. The transm...
展开
This paper addresses the problem of output feedback sampled-data stabilization for upper-triangular nonlinear systems with improved maximum allowable transmission delay. A class of hybrid systems are firstly introduced. The transmission delay may be larger than the sampling period. Then, sufficient conditions are proposed to guarantee global exponential stability of the hybrid systems. Based on these sufficient conditions and a linear continuous-discrete observer, an output feedback control law is presented to globally exponentially stabilize the feedforward nonlinear system. The improved maximum allowable transmission delay is also given. The results are also extended to output feedback sampled-data stabilization for lower-triangular nonlinear systems. Finally, illustrative examples are used to verify the effectiveness of the proposed design methods. Copyright (c) 2016 John Wiley & Sons, Ltd.
收起
摘要 :
In this paper, we study dynamical output feedback H-infinity control for networked control systems (NCSs) based on two channel event-triggered mechanisms, which are proposed on both sides of the sensor and the controller. The outp...
展开
In this paper, we study dynamical output feedback H-infinity control for networked control systems (NCSs) based on two channel event-triggered mechanisms, which are proposed on both sides of the sensor and the controller. The output feedback H-infinity controller is constructed by taking random network-induced delays into consideration without data buffer units. The controlled plant and the output feedback controller are updated immediately by the sampled input and the sampled output, respectively. By using the approaches of time delay and interval decomposition, linear matrix inequality (LMI) based sufficient conditions are presented to guarantee that the closed-loop system satisfies H-infinity performance. Finally, we provide numerical simulations to illustrate effectiveness of the proposed method.
收起
摘要 :
In this paper, we propose a new economic dispatch model with random wind power, demand response and carbon tax. The specific feature of the demand response model is that the consumer's electricity demand is divided into two parts:...
展开
In this paper, we propose a new economic dispatch model with random wind power, demand response and carbon tax. The specific feature of the demand response model is that the consumer's electricity demand is divided into two parts: necessary part and non-essential part. The part of the consumer's participation in the demand response is the non-essential part of the electricity consumption. The optimal dispatch objective is to obtain the minimum total cost (fuel cost, random wind power cost and emission cost) and the maximum consumer's non-essential demand response benefit while satisfying some given constraints. In order to solve the optimal dispatch objective, a multi-subpopulation bat optimization algorithm (MSPBA) is proposed by using different search strategies. Finally, a case of an economic dispatch model is given to verify the feasibility and effectiveness of the established mathematical model and proposed algorithm. The economic dispatch model includes three thermal generators, two wind turbines and two consumers. The simulation results show that the proposed model can reduce the consumer's electricity demand, reduce fuel cost and reduce the impact on the environment while considering random wind energy, non-essential demand response and carbon tax. In addition, the superiority of the proposed algorithm is verified by comparing with the optimization results of CPLEX+YALMIP toolbox for MATLAB, BA, DBA and ILSSIWBA.
收起
摘要 :
This paper investigates finite-time stability and its application for solving time-varying Sylvester equation by recurrent neural network. Firstly, a new finite-time stability criterion is given and a less conservative upper bound...
展开
This paper investigates finite-time stability and its application for solving time-varying Sylvester equation by recurrent neural network. Firstly, a new finite-time stability criterion is given and a less conservative upper bound of the convergence time is also derived. Secondly, a sign-bi-power activation function with a linear term is presented for the recurrent neural network. The estimation of the upper bound of the convergence time is more less conservative. Thirdly, it is proposed a tunable activation function with three tunable positive parameters for the recurrent neural network. These parameters are not only helpful to reduce conservatism of the upper bound of the convergence time, accelerate convergence but also reduce sensitivity to additive noise. The effectiveness of our methods is shown by both theoretical analysis and numerical simulations.
收起
摘要 :
The increase of extreme climate events under a warming climate has and will continue to threaten the growth and development of maize across the North China Plain (NCP). Understanding and assessing the spatiotemporal changes of fut...
展开
The increase of extreme climate events under a warming climate has and will continue to threaten the growth and development of maize across the North China Plain (NCP). Understanding and assessing the spatiotemporal changes of future extreme climate events during the maize growth period are essential for developing adaptation strategies to reduce the risks of climate to maize productivity under future climate change. In this study, we applied statistically downscaled climate data from 20 global climate models (GCMs) and two Shared Socioeconomic Pathways (SSP245 and SSP585) for 52 stations in the NCP and investigated the future changes of 6 extreme climate indices (ECIs) during different maize growth periods that are sensitive to maize yield. The change in maize phenology under future climate scenarios was simulated by the well-validated APSIM-maize model. Moreover, we selected the independence weighted mean (IWM) method to evaluate the performance of 20 GCMs in reproducing historical changes in ECIs. The results from IWM could better reproduce historical changes of ECIs than any individual GCM and multi-model arithmetic mean. We found that the intensity and frequency of extreme high temperature indices during the maize growth period were projected to increase over the twenty-first century for both SSP245 and SSP585 across the NCP. There was no significant change in extreme precipitation index (R20). The consecutive wet days (CWD) significantly increased, while the consecutive dry days (CDD) slightly decreased over the twenty-first century. To mitigate and adapt the impacts of future extreme climate on maize growth, we found adjustment of sowing date (SD) had important effects on ECIs, especially on the extreme high temperature indices. Overall, a proper delay of SD could greatly reduce the occurrence of extreme heat stress on maize production under both scenarios. We expect these climate extreme projections will provide helpful information to optimize climate resources in the NCP to better adapt future climate change.
收起
摘要 :
In this paper, we consider two kinds of sampled-data observer design for a class of nonlinear systems. The system output is sampled and transmitted under two kinds of truncations. Firstly, we present definitions of the truncations...
展开
In this paper, we consider two kinds of sampled-data observer design for a class of nonlinear systems. The system output is sampled and transmitted under two kinds of truncations. Firstly, we present definitions of the truncations and the globally uniformly ultimately bounded observer, respectively. Then, two kinds of observers are proposed by using the delayed measurements with these two truncations, respectively. The observers are hybrid in essence. For the first kind of observers, by constructing a Lyapunov-Krasovskii functional, sufficient conditions of globally uniformly ultimately bounded of the estimation errors are derived, and the maximum allowable sampling period and the maximum delay are also given. For the second ones, sufficient conditions are also given to ensure that the estimation errors are globally uniformly ultimately bounded. Finally, an example is provided to illustrate the design methods.
收起
摘要 :
In this paper, we discuss exponential stability for nonlinear systems with sampled-databased event-triggered schemes. First, a framework is proposed to analyze exponential stability for nonlinear systems under some different trigg...
展开
In this paper, we discuss exponential stability for nonlinear systems with sampled-databased event-triggered schemes. First, a framework is proposed to analyze exponential stability for nonlinear systems under some different triggering conditions. Based on these results, output feedback exponential stabilization is investigated for a class of inherently nonlinear systems under a kind of event-triggered strategies. Finally, the rationality of the theoretical work is verified by numerical simulations.
收起
原文获取