Scene text detection is a fundamental component of optical character recognition, document intelligence, assistive technologies, multilingual content retrieval, and multimodal perception systems. However, accurately detecting text that is curved, stylized, densely packed, or small-scale in natural scenes remains challenging—limiting the reliability of text-dependent vision systems in real-world applications. In this paper, we propose a Query vector guided Multi-scale Text Detection algorithm (QMTD) that dynamically generates the initial query vectors for the transformer decoder using a query embedding initialization module. By extracting the initial query vectors from the pixel features of the input feature map, QMTD improves the model’s generalization ability. Additionally, an attention region guidance module is introduced to exploit multi-layer decoder features in the transformer to direct subsequent computational processes, which allows for the step-by-step refinement of the predicted results across multiple decoder layers, accelerating training while improving model performance. Finally, QMTD incorporates a multi-scale feature enhancement module, which uses high-resolution feature maps to improve segmentation precision and low-resolution feature maps to balance the computational time required. Evaluations on CTW1500, Total-Text, and ICDAR2015 benchmarks demonstrate that QMTD achieves competitive or state-of-the-art H-mean, converges faster than the DTTR baseline during training, and maintains robust performance across curved and multi-oriented text scenarios. These findings collectively establish QMTD as a highly effective and practical solution for robust scene text detection.

This paper addresses the stability analysis of DC distribution networks with voltage source rectifiers (VSRs) and constant power loads (CPLs). Existing stability criteria for DC networks often rely on simplified models neglecting source converter controller dynamics, limiting their applicability in practical controller design. To overcome this, a singular perturbation-based framework is proposed to derive analytical stability conditions for closed-loop DC distribution network systems. By decomposing the high-dimensional Jacobian matrix into two structured low-dimensional matrices, tractable stability criteria are established using properties of Karush-Kuhn-Tucker (KKT) matrices. Sufficient stability conditions for local stability of a VSR-based DC distribution network are derived without requiring global VSR information, while a robust stability criterion dependent solely on maximum load data is developed to handle uncertainties. These results provide explicit design guidelines to enhance robustness and reduce computational complexity in stability analysis. Simulations validate the effectiveness of the proposed approach.

With the high proportion of distributed energy resources with randomness and intermittency penetrating the distribution network, traditional centralized optimization methods face problems such as communication packet loss, frequent failures, and low reliability and are difficult to apply to large-scale DC microgrids with wide-area dispersion effectively. Therefore, distributed optimization methods have attracted widespread attention due to their superior scalability and robustness. This paper investigates a convex relaxation-based distributed control strategy for DC microgrids with constant power loads (CPLs) and MPPT-controlled distributed generations (MPPT-DGs) to achieve global optimization. First, an optimal power flow (OPF) problem model for large-scale DC microgrids under a distributed framework is established, and a convex relaxation method taking exactness into account is proposed to transform the non-convex original problem into a new convex problem with the same optimal solution. Then, the Karush–Kuhn–Tucker (KKT) condition and its equivalent consistency-based condition are derived based on convex relaxation, and a distributed global optimization control method is proposed to achieve global optimal system operation, avoiding the solution of large-scale non-linear optimization problems. Finally, simulations and numerical experiments are presented to verify the correctness of the proposed strategy.

Frequency damping control is a crucial aspect of islanded microgrids utilizing multiple virtual synchronous generators (VSGs). This paper studies the effects of line impedance mismatches and transient frequency out-of-sync leading to frequency interactive oscillation in VSGs. To address this issue, we propose a distributed interactive damping and zero-error control method that utilizes sparse communications. The objective of this method is to effectively suppress frequency oscillation by minimizing the differences in frequency dynamics among all VSGs. By implementing this approach, a low rate of change of frequency (RoCoF), accurate active power sharing, and zero frequency deviation are ensured. Through dynamic performance analysis, frequency characteristic analysis, and stability analysis based on LaSalle’s invariance principle, we demonstrate significant improvements in system stability, as well as dynamic and steady state performances. Finally, simulation and experimental results obtained under load changes, short-circuits, and communication faults validate the effectiveness of the proposed control method.

Multi-energy flow analysis is the fundamental work to study the state estimation, safety analysis, and optimal control of integrated smart energy system (ISES). However, the randomness of renewable energy can easily lead to no static equilibrium in ISES, making its static stability a huge challenge. In addition, the coupling effect between multiple energy flows makes the analysis of the static stability of ISES more complicated. In this paper, the existence of equilibrium of ISES under multi-energy flow coupling is analyzed, and the analytical sufficient conditions for the static stability of the system are given. Firstly, the power flow equation of the ISES is derived. Then, based on Brouwer's fixed-point theorem, the analytical sufficient conditions for the power flow equation of the ISES are derived. Finally, a simulation model based on Matlab/Simulink is established, and the simulation results verify the correctness and effectiveness of the proposed conclusions.

Testing, Adjusting and Balancing (TAB procedure) is an important issue of heating, ventilation, and air conditioning (HVAC) systems. This paper proposes an adaptive distributed consensus control-based air balancing (ADCC-AB) method for the HVAC systems, which aims to achieve air balancing via neighboring communication and parameter self-tuning. Comparing with the traditional air balancing methods, the proposed ADCC-AB method has the following advantages. 1.) This method only need to communicate with neighboring terminals, thus eliminating the necessity of a centralized control unit. 2.) It is mode-free method that requires no system topology and parameters and is therefore easy to apply. 3.) The proposed method can automatically adjust the control parameters to achieve system stability. The simulation results verified the performances of the proposed method.

This paper proposes a novel distributed control scheme for DC microgrids to acquire minimum generation cost and recover the global average voltage with consideration of capacity constraints. Our main focus is on constrained problems where the power of each distributed generator (DG) is restricted to lie in the feasible region. In this paper, a global load observer (GLO) is introduced that uses neighbor's data to estimate the total load across the microgird. To achieve minimizing generation cost, an alternative control strategy is proposed based on the specific characteristics of the optimum solution. When the total load which can be obtained by the GLO is less than the critical point, it generates power according to equal incremental cost rate (ICR) criteria; otherwise, it generates power maintain the maximum output point. To achieve voltage recovery, a voltage regulator is designed. The proposed controller on each DG communicates with its neighbor DGs on a sparse communication graph. The performance of the proposed scheme is validated and tested through MATLAB simulation.