A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status ...
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Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is ...
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This paper proposes a tradeoff based interactive multiobjective evolutionary algorithm (TIEA). It can support the decision maker (DM) to guide the search towards the DM's most preferred solution by combing evoluti...
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In this paper, an improved adaptive time-varying sliding mode controller (SMC) is designed for five-phase dual-rotor permanent magnet synchronous motor (FDRPMSM). It focuses on three objectives: 1) maintaining the hig...
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This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guar...
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ISBN:
(纸本)9781509015740;9781509015733
This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guaranteed stability. A model-free algorithm of adaptive dynamic programming is employed to deal with the uncertainty of system parameters, yielding an optimal feedback controller for the system subject to a predefined cost. Then the stability of the system in time-varying uncertain situation which may undergo parameter changes or jumps is analyzed from the perspective of finite-time stability. On the basis of these results, a switching control strategy is presented to ensure the stability of the time-varying uncertain system with desired optimality properties in the long run. The effectiveness of the strategy is verified by simulations on a DC torque motor servo system.
In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stoc...
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In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stochastic equations, we give stochastic sufficient stability criteria for polytopic uncertain Itô SMJSs. As a corollary, stochastic sufficient stability criteria are given for nominal Itô SMJSs. For this two cases of Itô SMJSs, based on the obtained stochastic stability criteria, their time-independent sampled-data controllers are designed, respectively. Then, for designing a time-dependent sampled-data controller for Itô SMJSs, a parameters-dependent time-scheduled Lyapunov functional is developed. New stochastic sufficient stability criteria are obtained for polytopic uncertain Itô SMJSs and nominal Itô SMJSs. Furthermore, their time-dependent sampled-data controllers are designed, respectively. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed method.
In this paper, a simplified dynamic vehicle model is established to accurately describe the dynamics of Unmanned Ground Vehicle (UGV) in trajectory tracking, while meeting the real-Time computing requirement. And a mo...
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state estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subse...
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ISBN:
(纸本)9781509045839
state estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subsequent estimation problems are based. Among these problems are the estimation problem in the presence of packet drops and estimation problem involving event-based triggers. We study in this paper both phenomena simultaneously. In an attempt to find the Kalman-like filter, which proves the Gaussianity of the state and offers a set of update equations, our paper shows that no such filter exists. More precisely, one cannot find an event-based trigger such that under possible packet drops, the state variable remains a Gaussian variable. This conclusion can be reasonably extended to a more general setting.
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based ...
As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based on the behavior analysis. Firstly, customers' active behavior is represented by the quantity of active customer households. Based on the analysis of customer behaviors, a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo method. Then, with the inputs as the quantity of active customer households and time of photovoltaic power generation, an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical appliances. By combing the average usage time of electrical appliances, load characteristics are analyzed based on usage state of electrical appliance of distributed power customers. Finally, the simulation results verify the effectiveness of the proposed method.
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