Physics-guided neural networks (PGNN) is an effective tool that combines the benefits of data-driven modeling with the interpretability and generalization of underlying physical information. However, for a classical P...
详细信息
Physics-guided neural networks (PGNN) is an effective tool that combines the benefits of data-driven modeling with the interpretability and generalization of underlying physical information. However, for a classical PGNN, the penalization of the physics-guided part is at the output level, which leads to a conservative result as systems with highly similar state-transition functions, i.e. only slight differences in parameters, can have significantly different time-series outputs. Furthermore, the classical PGNN cost function regularizes the model estimate over the entire state space with a constant trade-of hyperparameter. In this paper, we introduce a novel model augmentation strategy for nonlinear state-space model identification based on PGNN, using a weighted function regularization (W-PGNN). The proposed approach can efficiently augment the prior physics-based state-space models based on measurement data. A new weighted regularization term is added to the cost function to penalize the difference between the state and output function of the baseline physics-based and final identified model. This ensures the estimated model follows the baseline physics model functions in regions where the data has low information content, while placing greater trust in the data when a high informativity is present. The effectiveness of the proposed strategy over the current PGNN method is demonstrated on a benchmark example.
The widespread dissemination of misinformation and propaganda has become a crucial issue in societal conversations. This study presents an innovative framework to counter propaganda within information warfare using a ...
详细信息
State observers for nonlinear systems are often designed for a canonical form of this system. However, this form may possess singular points, where the vector field is not defined or a Lipschitz condition is not fulfi...
详细信息
In this contribution we discuss the design of functional observers for polynomial systems. Our approach is based on a high gain design employing an embedded observer. The functional to be estimated is generated from t...
The effective warning of dangerous events along long-distance pipelines is critical to ensure the safety of oil and gas transportation. Distributed optical fiber sensing (DOFS) technology can assist operators to ident...
详细信息
Path planning is very necessary in an autonomous mobile robot system to ensure a planned collision- free path from the starting point to the destination point in the navigation environment In general, there are two me...
详细信息
In this research, nature inspired metaheuristic optimization algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Techniques are formulated to tune optimal combinations of PID controller parameters...
详细信息
Permanent magnet synchronous motors (PMSMs) are widely used in various fields due to their high efficiency, high power factor and small volume. In this paper, a segmented permanent magnet interior permanent magnet syn...
详细信息
High-resolution magnetic resonance imaging (MRI) is very important for doctors to judge the condition. At present, the depth learning method has been widely studied in the super-resolution reconstruction of MR images....
详细信息
In the shallow sea environment, array of small array elements may not be able to accurately locate targets due to undersampling. To address this issue, the paper proposed a method called sound field extension based on...
详细信息
暂无评论