With the excessive consumption of fossil energy and the growing environmental pollution caused by its combustion, the gas turbine system (GTS) plays a key role in distributed renewable energy fields due to its versati...
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The recognition of stress responses in health, resilience, and psychopathology holds significant scientific importance. The biological information carried by the facial tissue oxygen saturation (StO2) is a useful indi...
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ISBN:
(数字)9798350386226
ISBN:
(纸本)9798350386233
The recognition of stress responses in health, resilience, and psychopathology holds significant scientific importance. The biological information carried by the facial tissue oxygen saturation (StO2) is a useful indicator for stress recognition. Although graph-based methods have achieved state-of-the-art (SOTA), there is room for improvement. This study proposes an automatic graph generation method for facial StO2, replacing manual methods and enhancing the information of graphs. To further enhance the capability of graphs’ representation, a dimensionality reduction strategy for nodes is proposed. The strategy is implemented based on an novel objective function that can increase the inter-class distance and reduce the intra-class distance. After obtaining highly representative graphs, a dual-stream network integrating GAT and GCN is designed to extract stress-related features from the graphs, ultimately achieving the SOTA recognition accuracy.
In this paper, a new reinforcement learning-based model-free adaptive control algorithm is introduced for discrete-time nonlinear multi-agent systems with unknown dynamics, while the equivalent dynamic linearization a...
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ISBN:
(数字)9798350379228
ISBN:
(纸本)9798350390780
In this paper, a new reinforcement learning-based model-free adaptive control algorithm is introduced for discrete-time nonlinear multi-agent systems with unknown dynamics, while the equivalent dynamic linearization algorithm is applied to design the optimal controller. The strategy for Q-Learning and the actor-critic neural network are specifically redesigned to achieve consensus control in multi-agent systems. The proposed reinforcement learning algorithm can adjust the dynamic linearization parameters in real-time only based on input and output data. The stability of the closed-loop system is proven by Lyapunov theorem. Furthermore, the method’s effectiveness is verified by a numerical simulation.
In this paper, event-triggered active disturbance rejection control (ADRC) is first addressed for a class of uncertain random nonlinear systems driven by bounded noise and colored noise. The event-triggered extended s...
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With the excessive consumption of fossil energy and the growing environmental pollution caused by its combustion, the gas turbine system (GTS) plays a key role in distributed renewable energy fields due to its versati...
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ISBN:
(数字)9798350353594
ISBN:
(纸本)9798350353600
With the excessive consumption of fossil energy and the growing environmental pollution caused by its combustion, the gas turbine system (GTS) plays a key role in distributed renewable energy fields due to its versatility, efficiency and controllability. This paper focuses on the adaptive constraint regulation problem for the GTS with time-varying load disturbance, thereby facilitating exact speed tracking to regulate the fuel flow for the turbine under variable load conditions. Therein, a residual transformation dynamics based on the performance function are established for triggering the preset-time residual convergence and output performance constraints. Then, an adaptive constraint controller is developed to ensure the desired regulation level of the GTS. Simulation results illustrate that the proposed strategy can mitigate the load disturbance effect and guarantee the GTS performance constraints.
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