This paper studies consensus control problems for a class of second-order multi-agent systems without relative velocity measurement. Some dynamic neighbour-based rules are adopted for the agents in the presence of ext...
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This paper studies consensus control problems for a class of second-order multi-agent systems without relative velocity measurement. Some dynamic neighbour-based rules are adopted for the agents in the presence of external disturbances. A sufficient condition is derived to make all agents achieve consensus while satisfying desired H∞ performance. Finally, numerical simulations are provided to show the effectiveness of our theoretical results.
Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. The problem becomes more complex because the acquired data series are non-linear and non-Gaussian. In this pa...
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This paper presents a controlsystem design strategy for multi-input and multi-output (MIMO) networked controlsystems with random delays. The performance index of the controlsystems is constructed by entropies of tr...
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This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
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ISBN:
(纸本)9780955529337
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
Next-day electricity prices forecasting is essential to consumers and producers. Due to the stochastic characteristics of the electricity price time series, a novel model of electricity price forecasting is presented ...
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Next-day electricity prices forecasting is essential to consumers and producers. Due to the stochastic characteristics of the electricity price time series, a novel model of electricity price forecasting is presented based on the Hidden Markov Model (HMM). The factors impacting the electricity price forecasting are discussed. The proposed approach is utilized in an electricity market, the results show the effectiveness.
In an open electricity market, generation companies (GENCO) have to optimally bid to gain more profits with incomplete information of other competing generators. In this structure, market participants must develop the...
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In an open electricity market, generation companies (GENCO) have to optimally bid to gain more profits with incomplete information of other competing generators. In this structure, market participants must develop their bids in order to maximize their profits. Building optimal bidding strategies for GENCO could need to evaluate some market parameters such as forecasting market-clearing price (MCP), non-convex production cost function and forecasting load. A new framework to build bidding strategies for GENCO in an electricity market is presented in this paper. A normal probability distribution function (PDF) is used to describe the bidding behaviors of other competing generators. Bidding strategy of a generator for each trading period in a day-ahead market is solved by a new adaptive particle swarm optimization APSO). APSO can dynamically follow the frequently changing market demand and supply in each trading interval. A numerical example serves to illustrate the essential features of the approach and the results are compared with the solutions by other PSO algorithms.
It is difficult to deal with the variable speed constant frequency (VSCF) wind turbine systems due to the stochastic characteristics and the pneumatic effects of wind. In this paper, a new pitch controller based on ge...
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ISBN:
(纸本)9781424450459;9781424450466
It is difficult to deal with the variable speed constant frequency (VSCF) wind turbine systems due to the stochastic characteristics and the pneumatic effects of wind. In this paper, a new pitch controller based on generalized predictive control theory is designed to improve the power-output quality of variable speed constant frequency wind turbines. An application to a 300MW wind turbines is given, and simulation results show that the proposed method is effective in wind speed interference suppression and constant out power.
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
In this paper, a mmlmum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for non...
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ISBN:
(纸本)9780955529337
In this paper, a mmlmum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for nonlinear NeSs via information theoretic learning approach based on stochastic gradient algorithm. A numerical example is given to illustrate the effectiveness of the proposed scheme.
In this paper, a minimum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for no...
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In this paper, a minimum entropy filter is presented for estimating states in networked controlsystems with multiple-packet transmission mechanism and non-Gaussian time-delay and noises. The filter is designed for nonlinear NCSs via information theoretic learning approach based on stochastic gradient algorithm. A numerical example is given to illustrate the effectiveness of the proposed scheme.
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