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A Reinforcement-learning-based Bidding Strategy for Power Suppliers with limited information

Journal of Modern Power Systems and Clean Energy 2022年第4期10卷 1032-1039页

作者： Qiangang Jia Yiyan Li Zheng Yan Chengke Xu Sijie Chen Shanghai Jiao Tong University Shanghai 200240China Department of Electrical and Computer Science North Carolina State UniversityRaleigh 27695USA

The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding behaviors.Most existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding strategy.However,this assumption may not be true in reality,particularly when a power market is newly launched.To help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is proposed.This algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated game.Simulation results verify the effectiveness of the proposed learning algorithm.

关键词： Power market bidding strategy limited information repeated game continuous action reinforcement learning automata

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Real-time interactive motion control of virtual human in virtual maintenance based on limited information

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International Journal of Modeling, Simulation, and Scientific Computing 2015年第2期6卷 16-39页

作者： Xiangyang Li Zhili Zhang Feng Liang Zhao Tong Xi’an Research Institution of High Technology Xi’an People’s Republic of China

In order to provide a simple and efficient approach to perform the real-time interactive motion control of virtual human in virtual maintenance environment(VME),the motion control method of virtual human based on limited input information is proposed.With the space position tracking system with only one sensor the action sequences and motion models of virtual human,the human motions and hand actions in VME are driven by the sensor data in stages and in real time through the transmission condition control in the process of maintenance operation.And the input data and information is processed based on the method of Kalman filtering and wavelet transforming to improve the control effects.An experimental VME is also established to validate the control efficiency,and the experiment results show that the space motion control of virtual human in VME can be performed based on limited information with proposed control strategy.

关键词： Real-time interactive motion control virtual human virtual maintenance virtual maintenance environment limited information

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Stabilization for nonlinear systems via a limited capacity communication channel with data packet dropout

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控制理论与应用（英文版） 2010年第1期8卷 111-116页

作者： Lei ZHOU Guoping LU School of Science Nantong University Nantong Jiangsu 226007 China Department of Mathematics East China Normal University Shanghai 200062 China College of Electrical Engineering Nantong University Nantong Jiangsu 226019 China

This paper addresses the stabilization problem for a class of nonlinear systems. It is assumed that the controller can only receive the transmitted sequence of finite coded signals via a limited digital communication channel. Both state and output feedback coder-decoder-controller procedures are proposed. Stabilization conditions involving the size of coding alphabet, the sampling period, system state growth rate and data packet dropout rate are obtained. Finally, an example is given to illustrate the design procedures and effectiveness of the proposed results.

关键词： Stabilization Nonlinear system limited information Data packet dropout Linear matrix inequality

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