Insulator defects in transmission lines can threaten the safe and stable operation of the power system. Therefore, insulator defect detection plays a crucial role in the electricity sector. Currently, You Only Look Once (YOLO) algorithm is widely used in insulator fault detection. However, insulator defect detection using YOLO still faces the double challenges of detection precision and real-time performance. Therefore, we construct a lightweight model for insulator defect detection named coordinate attention mechanism (CAM) and feature channel shuffle operation (CSO) YOLO (CACS-YOLO). By introducing the CAM and CSO in the original YOLOv8m, we improve the detection precision, and reduce the parameters of model, compared with existing insulator defect detection models. Meanwhile, in order to solve the problem of insufficient data and cope with different weather conditions, we use synthetic weather algorithms for data enhancement, and construct a Synthetic Foggy and Rainy Insulator Dataset (SFRID). The experimental results show that the mean average precision of CACS-YOLO is 96.9% and the parameters of proposed model is 27.44M. These outcomes show the high-precision and lightweight of our proposed model in insulator defect detection. The source code and dataset are available on Github.

A parameterized controller design approach is proposed to solve the problem of multi-objective control for vehicle active suspension systems by using symbolic computation. The considered model is a quarter-vehicle model of the active suspension system. The multi-objective robust control performances include the sprung mass acceleration, suspension deflection, and tire deflection. Based on dissipative Hamiltonian systems and Lyapunov function, a multi-objective. H∞ controller design approach is developed, which can avoid solving Hamilton-Jacobi-Issacs equations. Then, an algorithm of solving semi-positive definite polynomial with tuning parameters is proposed by using symbolic computation. Furthermore, a method of parameter optimization is proposed. Simulations and comparation show that the control performance is significantly improved comparing with passive controlled systems and existing other control systems for active suspension systems.

This paper focuses on the problems of globally exponential stability and stabilization with H_∞ performance for a class of interconnected Markovian jump system with mode-dependent delays in interconnection. By constructing a Lyapunov-Krasovskii functional, delay-range-dependent globally mean-square exponential stability conditions are established in terms of linear matrix inequalities. Based on the obtained conditions, state feedback control utilizing global state information and state feedback control utilizing global state information of decentralised observers are developed to render the closed-loop interconnected Markovian jump time-delay system globally exponential stable with H_∞ performance. Numerical simulation of a power system, composed of three coupled machines, is used to illustrate the effectiveness of the obtained results.