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"Control stability"
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Mechanisms of MicroRNA Biogenesis and Stability Control in Plants
MicroRNAs (miRNAs), a class of endogenous, non-coding RNAs, which is 20–24 nucleotide long, regulate the expression of its target genes post-transcriptionally and play critical roles in plant normal growth, development, and biotic and abiotic stresses. In cells, miRNA biogenesis and stability control are important in regulating intracellular miRNA abundance. In addition, research on these two aspects has achieved fruitful results. In this review, we focus on the recent research progress in our understanding of miRNA biogenesis and their stability control in plants.
Journal Article
Intelligent Vehicle Lateral Control Method Based on Feedforward + Predictive LQR Algorithm
Aiming at the problems of control stability of the intelligent vehicle lateral control method, single test conditions, etc., a lateral control method with feedforward + predictive LQR is proposed, which can better adapt to the problem of intelligent vehicle lateral tracking control under complex working conditions. Firstly, the vehicle dynamics tracking error model is built by using the two degree of freedom vehicle dynamics model, then the feedforward controller, predictive controller and LQR controller are designed separately based on the path tracking error model, and the lateral control system is built. Secondly, based on the YOLO-v3 algorithm, the environment perception system under the urban roads is established, and the road information is collected, the path equation is fitted and sent to the control system. Finally, the joint simulation is carried out based on CarSim software and a Matlab/Simulink control model, and tested combined with hardware in the loop test platform. The results of simulation and hardware-in-loop test show that the transverse controller with feedforward + predictive LQR can effectively improve the accuracy of distance error control and course error control compared with the transverse controller with feedforward + LQR control, LQR controller and MPC controller on the premise that the vehicle can track the path in real time.
Journal Article
Fixed-time dynamic control allocation for the distribution of braking forces in a vehicle ESC system
This paper proposes a design technique for vehicle lateral stability control. In this structure, reference variables are first determined based on the driver’s input. Using a fixed-time control technique, an upper controller, also known as virtual control, is designed to ensure vehicle stability for the desired yaw moment. Subsequently, optimal braking forces, also known as lower controls, are designed by virtual control and are utilized to generate the control inputs for the actuators. The optimal braking forces, which are constrained, are designed using a fixed-time dynamic control allocation method. This ensures their convergence to optimal values in a fixed time. Unlike static optimization methods, the proposed control allocation method introduces a dynamic update law. This approach not only reduces computational complexity but also guarantees the fixed-time convergence of braking forces to the optimal solution. The overall closed-loop stability in constant time is also achievable via the Lyapunov stability method. Simulations were conducted on a 10-DOF nonlinear dynamic vehicle model for standard test maneuvers of the electronic stability control system. The results indicate that the proposed method outperforms numerical optimization-based methods such as weighted least squares, weighted pseudoinverse, and asymptotic dynamic control allocation in terms of efficiency.
Journal Article
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
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
Nonlinear wheel-slip dynamics of battery electric vehicle for anti-lock brake system control by traction motor
Anti-lock brake system control by traction motor requires optimal utilization of ground adhesion coefficient during regenerative braking, and it is essential to maintain the stability of battery electric vehicle throughout the process. Further, the wheel slip ratio control of brake-electric system differs from that of brake-hydraulic system due to the large difference in the response time of brake torque. Therefore, it is particularly challenging to prevent the lock of all traction wheels through torque control of the traction motor. While much of the research on brake-electric system has focused on optimizing the energy regeneration efficiency in the barke process, comparatively little is known about the stability control of battery electric vehicle. Here this article discusses a series of studies on the nonlinear dynamics of wheel slip and model predictive controller, and a torque demand control approach was designed based on both of these. That is, how a nonlinear model predictive controller could be used for anti-lock brake control of traction wheels. In order to find the optimum value of the wheel slip ratio, an ideal slip ratio curve illustrated by ground adhesion coefficient and wheel slip ratio was developed, which is used as an optimal target boundary of control algorithm. The developed approach has been downloaded into a vehicle control unit, and tested in real-world conditions using a battery electric vehicle to fully realize practical application of anti-lock brake system control by traction motor torque.
Journal Article
Model Predictive Control for Integrated Lateral Stability and Rollover Prevention Based on a Multi-actuator Control System
It is a challenge to realize the coordinated control of multiple actuators and ensure anti-roll stability and lateral stability in an integrated control system. To address this problem, this study presents a novel integrated multiobjective control strategy for electric vehicles using multiple actuators. The main control objectives consist of lateral stability control, handling performance, rollover prevention and trajectory tracking. First, the proposed multiobjective control strategy uses a model predictive control method to coordinate the control of multiple actuators and provide the optimal solution of the multiple objectives. The control strategy considers the interaction between different actuators and the conflict between different control objectives. Second, the uncertainty of vehicle mass is accounted for, and a dual unscented Kalman filter (UKF) observer is proposed to estimate the sideslip angle, roll angle and vehicle mass in real time. Third, variable wheelbase reference model technology is used to reduce the vehicle rollover index under high-speed turning conditions. Finally, the simulation results demonstrate that the proposed integrated multiobjective control strategy can effectively coordinate multiple actuators to achieve multiple control objectives.
Journal Article