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"stability control system"
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Research and Application of Panoramic Data Visualization Platform for Stability Control Equipment Based on the Whole Life Cycle
In recent years, with the mass access of new energy such as UHV commissioning projects and photovoltaic wind, the problems in safely and stably operating regional power grid are becoming more and more prominent. Mass power grid stability control system and equipment play a significant role in this aspect. However, there are a great variety of manufacturers and models of the stability control systems and equipment, as well as configuration schemes for the operation strategy and fixed value of the primary equipment. Due to insufficient technological support, it is relatively inconvenient to manage the information and data of stability and control system on the whole process from feasibility research, initial test, factory debugging, site debugging, commissioning acceptance, protection verification, daily operation and maintenance management to the decommission of the system, thus failing to achieve the objective of classified management according to the relevant requirements, nor to modify and improve in time. Based on the management requirements and status quo of the stability and control equipment, a technical research on the panoramic data visualization platform for the stability control equipment with full life-cycle information covering the feasibility research, release, debugging, commissioning, verification, operation, decommission and so on of the equipment, which is available for the panoramic informationized and digital management of the stability control equipment, so as to realize the whole life cycle and systematic closed-loop management of the stability control system and the equipment.
Journal Article
A hierarchical lateral stability control strategy of distributed drive electric vehicles based on extended Kalman filter and integral terminal sliding mode control
This paper proposes a hierarchical control strategy to enhance the lateral stability of distributed drive electric vehicles. In the upper layer, the extended kalman filter (EKF) is employed for real-time estimation of critical vehicle states, including the sideslip angle and yaw rate. In the intermediate layer, a direct yaw-moment control (DYC) system based on integral terminal sliding mode control (ITSMC) is designed, which utilizes the deviation between the EKF-estimated states and their desired values to calculate the required additional yaw moment for stability compensation. In the lower layer, an optimal control–based torque allocation strategy is adopted to distribute the driving torque among the four in-wheel motors. Unlike many existing direct yaw moment control strategies that assume ideal state availability or suffer from control chattering and limited wheel-level realizability, this study explicitly addresses the coupled problem of state estimation uncertainty, robust yaw-moment generation, and practical torque realization under nonlinear tire dynamics. Simulation results demonstrate that the proposed EKF-based state estimation achieves high accuracy, while the ITSMC-DYC controller significantly improves lateral stability, trajectory tracking capability, and driving safety. Furthermore, hardware-in-the-loop (HIL) tests validate the effectiveness of the hierarchical control strategy under realistic scenarios, confirming its potential for practical applications.
Journal Article
Flexible hardware-in-the-loop testbed for cyber physical power system simulation
Nowadays, the power system is evolving into a complex cyber physical system with the closely merged physical system, information system, and communication network. It is critical to understand the connections between the power and cyber systems, and the potential impact of cyber vulnerability. In this study, a flexible hardware-in-the-loop (HIL) testbed is proposed for studying the cyber physical power system. By using the flexible interface, various co-simulation systems for different purposes are generated. Based on this testbed, three sample co-simulators are built as proofs. First, a HIL power and communication co-simulator with non-real-time synchronisation mechanism is introduced, and a case of false data injection attack on automation voltage control is studied. Then, a real-time power and communication HIL co-simulator is introduced, and a case considering the impact of communication bit error on the stability control system is simulated to demonstrate the performance of stability control equipment. Finally, another co-simulator for simulating the actual cyber-attack on the stability control system is introduced, and a case of a man-in-the-middle attack on the data link is simulated to demonstrate the impact of cyber-attack on the stability control system.
Journal Article
Trajectory Tracking Control of High-Speed Vehicles on Wet and Slippery Roads
Autonomous vehicle trajectory tracking control is one of the hot topics in the autonomous driving field. One of the most widely used control methods is MPC (Model Predictive Control). As the control system generally becomes more nonlinear and complex, more nonlinear system factors are added to the MPC method. However, tracking accuracy and the amount of calculation needed are both dependent on a lot of contradictions for NMPC (Nonlinear Model Predictive Control). This research proposes a control algorithm for MPC-fused PID (Proportional-Integral-Derivative) control that ensures tracking accuracy under different high-speed driving conditions on wet and slippery road surfaces. The objective of the algorithm is twofold: first, to enhance trajectory tracking accuracy, and second, to ensure real-time control and optimize the vehicle’s comfort, economy, and safety indexes. The results of the joint simulation in Carsim/MATLAB Simulink show that trajectory tracking accuracy is improved by at least 22.2% under high-speed driving conditions of a vehicle on a wet and slippery road. At the same time, the comfort, economy, and safety of the vehicle are improved by at least 9.4%, 19.8%, and 5.3%, respectively.
Journal Article
Dynamic Multi-Core Task Scheduling for Real-Time Hybrid Simulation Model in Power Grid: A Deep Reinforcement Learning-Based Method
With the increasing scale and complexity of power systems, the Security and Stability Control System (SSCS) plays a vital role in ensuring the safe operation of the grid. However, existing SSCS implementations still face many limitations in cross-regional coordination, control precision, and risk prediction. Establishing the digital simulation model is an effective way to verify the control policy of SSCS. This paper proposes a neural heuristic task scheduling method based on deep reinforcement learning (DRL) to schedule the simulation tasks. It models the task dependencies of SSCS as a directed acyclic graph (DAG) and then dynamically optimizes task priorities and resource allocation through deep reinforcement learning. The method introduces multi-head attention and heterogeneous attention mechanisms to effectively capture complex dependencies among tasks, enabling efficient multi-core task scheduling. Simulation results show that the proposed algorithm significantly outperforms traditional scheduling methods in terms of makespan, load balancing, and resource utilization. It can also adapt to dynamic changes under different task scales and multi-core environments, demonstrating strong robustness and scalability.
Journal Article
Control of Vehicle Lateral Handling Stability Considering Time-Varying Full-State Constraints
Lateral handling stability control is crucial for ensuring vehicle driving safety. To address this issue, this paper proposes a lateral handling stability control method that considers time-varying full-state constraints. By constructing a time-varying symmetric Barrier Lyapunov Function (TS-BLF), this method imposes time-varying nonlinear constraints on both the sideslip angle and yaw rate, thereby ensuring full-state constrained stability control of vehicles under complex operating conditions. Additionally, a second-order command filtering technique with an error compensation mechanism is introduced to reduce the computational complexity of control laws while mitigating filter-induced errors that may degrade system performance. To validate the effectiveness and robustness of the proposed method, the vehicle’s dynamic response is analyzed under different speeds on both dry asphalt pavement and dry gravel surfaces. The simulation results demonstrate that the proposed method effectively suppresses understeer and oversteer, enhances the dynamic stability margin under extreme operating conditions, and improves vehicle adaptability in complex environments.
Journal Article
Design of personal mobility system for assisted agricultural work with self-adjusting center of gravity
A personal mobility system with a self-adjusting center of gravity is designed to aid agricultural work. This personal mobility system can assist elderly and disabled people with mobility problems to perform simple agricultural tasks. Simulations and experiments were performed using a 2.5-times reduced model of the personal mobility system, and the feasibility and effectiveness of the proposed system were verified. With the initial position of the center of gravity of the personal mobility system as the set value, the proportional-integral-derivative control of the counterweight motion is coordinated horizontally using two corresponding motors and the center of gravity of the system is controlled within a certain range of the set value. The experimental transition time is 10.8 s and the simulated transition time is 10.4 s. The error between the two is 3.85 %. The results demonstrate that the proposed adaptive control system achieves adaptive adjustment of the center of gravity.
Journal Article
Hybrid fire testing in a non-linear environment using a proportional integral controller
Purpose
The purpose of this paper is to propose a new framework based on linear control system theory and the use of proportional (P) controller and proportional integral (PI) controller to address identified stability issues and control the time properties in hybrid fire testing.
Design/methodology/approach
The paper approaches hybrid fire testing as a control problem. It establishes the state equation to give the general stability conditions. Then, it shows how P and PI controllers can be incorporated in the system to maintain stability. A virtual hybrid fire testing is performed on a 2D steel frame for validation and to compare the performance of the controllers.
Findings
Control system theory provides an efficient framework for hybrid fire testing and rigorously formulate the stability conditions of the system. The use of a P-controller stabilises the process, but this controller is not suitable for continuous change of stiffness of the substructures. In contrast, a PI-controller handle the stiffness changes. The results of a virtual hybrid fire testing of a 2D steel frame shows that the PI-controller succeeds in reproducing the global behaviour of the frame, even if the surrounding structure is non-linear and subjected to fire.
Originality/value
The paper provides a rigorous formulation of the general problem of hybrid fire testing and shows the interest of a PI controller to control the process under varying stiffness. This methodology is a step forward for hybrid fire testing because it allows capturing the global behaviour of a structure, including where the numerical substructure behaves nonlinearly and is subjected to fire.
Journal Article