Stability Control System Research Articles

On the Lateral Stability System of Four-Wheel Driven Electric Vehicles Based on Phase Plane Method

To improve the handling and stability of four-wheel independent drive electric vehicles (FWID EVs), this paper introduces a hierarchical architecture lateral stability control system. The upper-level controller is responsible for generating the additional yaw moment required by the vehicle. This includes a control strategy based on feedforward control and a Linear Quadratic Regulator (LQR) for handling assistance control, an LQR-based stability control, a PID controller-based speed-following control, and a stability assessment method. The lower-level controller uses Quadratic Programming (QP) to optimally distribute the additional yaw moment to the four wheels. A “normalized” method was proposed to determine vehicle stability. After comparing it with the existing double-line method, diamond method, and curved boundary method through the open-loop Sine with Dwell test and the closed-loop Double Lane Change (DLC)test simulation, the results demonstrate that this method is more sensitive and accurate in determining vehicle stability, significantly enhancing vehicle handling and stability.

A Dual-Layer Control System for Steering Stability of Distributed-Drive Electric Vehicle

In addressing the limitations of traditional steering stability control strategies applied to distributed-drive electric vehicles (DDEVs)—which primarily focus on measuring yaw rate and sideslip angle and may result in loss of control during steering maneuvers—this study conducts a more comprehensive analysis of DDEVs’ steering control stability. It specifically investigates the relationships among the lateral positions of both the front and rear wheels, the slip ratios, and the angular orientation of the vehicle’s body during steering processes. Furthermore, a dual-layer steering stability control system aimed at enhancing the steering stability performance of DDEVs is introduced. This control system consists of two components: a lateral controller and a longitudinal controller. The lateral controller aims to establish clear linkages among four key variables, the front and rear wheel sideslip angles, yaw rate, and sideslip angle, and then to compute the necessary active front wheel steering angle and corresponding yaw moment based on the current vehicle body attitude. The findings indicate that, in comparison to the conventional DDEV controller, the proposed two-layer controller achieves substantially closer alignment to the reference curve during steering, with the accuracy increased by a factor of approximately 5 to 20. These results unequivocally affirm the efficacy and viability of the proposed approach.

Performance evaluation of a low-voltage SVC utilizing IoT streamed data for distribution systems

This paper presents the design, implementation, and performance evaluation of a novel 50 kvar Static Var Compensator (SVC) integrated with an Internet of Things (IoT) controller for a low-voltage power distribution system in Moscow. This integration enhances real-time monitoring and control capabilities over traditional SVC systems. The study focuses on advanced control systems for reactive power compensation, voltage stabilization, and overall system efficiency. Data collected over two months demonstrate the SVC’s effectiveness in maintaining a stable power factor close to unity and reducing reactive power demand. The device successfully kept voltage levels within acceptable limits across all phases, reducing fluctuations and ensuring balanced voltage levels. Key findings include enhanced reactive power compensation, voltage stabilization (minimum voltage not less than 218 V), improved system efficiency (reactive power demand from the source near zero most of the time), and significant improvements in power quality and grid stability. The case study at Kosinskaya Street, Moscow, confirms the device’s role in improving power quality and grid stability. These results support the broader deployment of IoT-integrated SVC technology in low-voltage power distribution systems.

Lateral-directional stability and control augmentation system design for civil aircraft simulator

Abstract In this paper, we first introduce the necessity, history, and classification of stability and control augmentation systems. The structure of the lateral-directional stability and control augmentation control system in the normal mode is studied, and a comparison of advantages and disadvantages of several design schemes including yawing rate feedback, rolling rate feedback, and sideslip angle feedback is given. Lateral-directional stability and control augmentation control law for a certain type of civil aircraft simulator is designed. Finally, the stability and control augmentation system is simulated and the simulation results are analyzed, which shows that the handling qualities of the aircraft with stability and control augmentation system are better than those without it.

Research on Stability Control System of Two-Wheel Heavy-Load Self-Balancing Vehicles in Complex Terrain

Research on Stability Control System of Two-Wheel Heavy-Load Self-Balancing Vehicles in Complex Terrain

Research on Vehicle Stability Control Based on a Union Disturbance Observer and Improved Adaptive Unscented Kalman Filter

This paper considers external disturbances imposed on vehicle systems. Based on a vehicle dynamics model of the vehicle with three degrees of freedom (3-DOFs), a union disturbance observer (UDO) composed of a nonlinear disturbance observer (NDO) and an extended state observer (ESO) was designed to obtain external disturbances and unmodeled items. Meanwhile, an improved adaptive unscented Kalman filter (iAUKF) with anti-disturbance and anti-noise properties is proposed, based on the UDO and the unscented Kalman filter (UKF) method, to evaluate the sideslip angle of vehicle systems. Finally, a vehicle yaw stability controller was designed based on UDO and the global fast terminal sliding mode control (GFTSMC) method. The results of co-simulation demonstrated that the proposed UDO was effectively able to observe external disturbances and unmodeled items. The proposed iAUKF, which considers external disturbances, not only achieves adaptive updating and adjustment of filtering parameters under different sensor noise intensities but can also resist external disturbances, improving the estimation accuracy and robustness of the UKF. In the anti-disturbance performance test, the maximum estimation error of the sideslip angle of the iAUKF under the three working conditions was less than 0.1°, 0.02°, and 0.5°, respectively. Based on the UDO and the GFTSMC, a vehicle yaw stability controller is described, which improves the accuracy of control and the robustness of the vehicle’s stability control system and greatly strengthens the driving safety of the vehicle.

Research on Voltage Coordinated and Stability Control of Condensers Based on Reactive Power Replacement

Abstract In this research, we investigated condenser voltage coordination and stability control systems by analyzing voltage coordinated control mode among excitation, voltage coordination and stability as well as automatic-voltage reactive power control systems. By using dynamic excitation regulation and steady-state regional voltage source control replacement, dynamic reactive power quickly output under fault condition as well as optimized regional reactive power under steady state were realized. The correctness and practicability of the proposed strategy was verified through engineering application. Adopting the reactive power displacement of voltage coordination control system to solve local voltage instability problem after UHV DC blocking. The proposed method realized multi-time scale emergency, recovery and steady-state control of the system under steady and dynamic states.

Anti-windup design for supercavitating vehicle based on sliding mode control combined with RBF network

During the longitudinal motion of a supercavitating vehicle, the stability control problem is complicated because of the nonlinear planing force on the tail part. The dynamic model of a supercavitating vehicle in longitude plane is nonlinear, simultaneously, the control instructions of a supercavitating vehicle may exceed the physical limits of an actuator. Therefore, designing a longitudinal stability control system for a supercavitating vehicle, not only the treatment of nonlinear planing force, but also the physical constraints of the actuator should be considered. For the longitudinal motion model of supercavitating vehicle, a cascade model is proposed, which decomposes the longitudinal motion of supercavitating vehicle into two subsystems. Sliding mode control based on RBF neural network compensation is adopted in the controller design process, and RBF neural network is exploited to approach the deviation caused by actuator saturation. The proposed control method can effectively compensate the performance degradation caused by control variable saturation, and has strong robustness.

Collaborative control of path tracking and roll stability in intelligent commercial vehicle: A minimax robust regulator based on Nash game

—Currently, most vehicles are generally equipped with roll stability control system or electronic stability control system to improve stability. However, when encountering emergency obstacle avoidance and similar conditions, roll stability control system may compete with path tracking control system for vehicle control, resulting in the inability to balance path tracking and roll stability. Therefore, a closed-loop feedback Nash game collaborative control method is proposed to solve the collaborative problem between the two control systems. Firstly, a fifth-order vehicle model with coupled yaw-roll dynamics is presented, which was extended to a vehicle-road closed-loop model based on lateral position, yaw angle and road preview information. Secondly, the path tracking control system and roll stability control system are regarded as two agents in the dynamic game control process. On this basis, a Nash game collaborative control strategy is designed by fully considering the control interaction between two game agents. Finally, considering the influence of uncertain disturbances, a finite-time minimax robust control strategy is proposed by using minimax optimization theory. Simulation and hardware in loop experiments show that the minimax robust regulator based on Nash game controller can effectively improve the path tracking and roll stability performance of vehicles. Moreover, the regulator improves the robustness of the system when it is subjected to bounded uncertain lateral disturbances.

Active suspension for all-terrain vehicle with intelligent control using artificial neural networks

The automotive industry focuses on developing advanced protection and stability control systems, particularly for suspension and steering, to enhance vehicle comfort, luxury, and safety. This research presents an intelligent controller for all-terrain vehicle (ATV) suspension systems based on Artificial Neural Network (ANN) technology. The controller leverages ANN capabilities to optimize system performance. MATLAB simulations were conducted to evaluate its effectiveness under various disturbances. A comparative analysis compared the ANN regulator, classic ANFIS regulator, and passive performance in different disturbance scenarios. The simulation results demonstrate exceptional performance of the ANN-based controller in displacement reduction, speed, acceleration, and robustness. The controller effectively mitigates disturbances, enhancing overall suspension system performance. These findings highlight the advantages of employing ANN technology in ATV suspensions. This research contributes to intelligent control systems advancement in the automotive industry, specifically in ATV suspensions. The demonstrated improvements have the potential to enhance passenger comfort, vehicle stability, and safety across terrains. By implementing ANN-based controllers, automotive manufacturers can optimize suspension systems, leading to improved vehicle performance. Several indicators, including RMSE, MRE, and R2, were utilized to test and validate the models. The R2 values for the three quality parameters ranged from 0.989 to 0.999, indicating a high level of consistency in the predictions made by the ANN, a "5-12-1" structure is employed. The results of this study add to the expanding body of knowledge endorsing the efficacy of ANNs in simulating and optimizing quarter-vehicle dynamics.

BIZON–UGV for Airport Pavement Testing: Mechanics and Control

The paper presents a study of the performance and development of unmanned ground vehicles (UGVs), establishing mathematical and numerical models of the chassis system. The model analysis is performed by 3D software package SolidWorks 2018 with finite element discretization. The mesh modelling and analysis are focused on studying the strength and stiffness of the robotic platform chassis and the distribution of stress and deformation in the extremal condition. The paper also presents an autopilot design with a new cascade control system for the autonomous motion of an unmanned ground vehicle based on proportional–integral–derivative (PID) and feedforward (FF) control. The PID-FF controller is part of a UGV used in a hybrid control system for precise control and stabilization, which is necessary to increase the vehicle motion stability and maneuver precision. The hybrid PID-FF control system proposed for the ground vehicle model gives satisfactory control quality while maintaining the simplicity of the control system. The presented tests performed in mechanical design and control analysis give good results and prove the usefulness of the designed unmanned device.

Principles of adaptive control of roll stability of reconfigurable chassis with planetary-wheeled propulsion system

BACKGROUND: Roll stability control is a relevant issue in transport platforms’ design in general. Well-known methods of roll stability control are used in development of vehicles of various types. However, these methods can not always be applied in design of small unmanned platforms, so development of special solutions is needed. AIM: Justification of feasibility of application of anti-roll balancing mechanisms in small unmanned vehicles. METHODS: The study is based on the analysis of technical solutions implemented in the design of platforms with extreme off-road capabilities and space rovers. Well-known methods of fundamentals of vehicle dynamics are the main tools of the study. RESULTS: The options of roll stability control system for small unmanned platforms are described. The conclusions regarding feasibility of different options of balancing mechanisms for addressing the issue of counteraction of stability losing and overturning are made. CONCLUSIONS: The discussed principles of roll stability control could be implemented in special small unmanned vehicles with any type of propulsion system. The further research in this field considers building of mathematical models capable of evaluating the required kinematics and power properties of the system of adaptive roll stability control, as well as testing using the mockup of a moving platform.

Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques

Expanding upon the well-established Takagi–Sugeno (T–S) fuzzy model, the T–S fuzzy descriptor model emerges as a robust and flexible framework. This article introduces the development of optimal and robust-optimal controllers grounded in the principles of stability control and fuzzy descriptor systems. By transforming complicated inequalities into linear matrix inequalities (LMI), we establish the essential conditions for controller construction, as delineated in theorems. To substantiate the utility of these controllers, we employ the rotary inverted pendulum as a testbed. Through diverse simulation scenarios, these controllers, rooted in fuzzy descriptor systems, demonstrate their practicality and effectiveness in ensuring the stable control of inverted pendulum systems, even in the presence of uncertainties within the model. This study highlights the adaptability and robustness of fuzzy descriptor-based controllers, paving the way for advanced control strategies in complex and uncertain environments.

Control of a Path Following Cable Trench Caterpillar Robot Based on a Self-Coupling PD Algorithm

Underground cable trench inspection robots work in narrow, variable friction coefficient, and complex road environments. The running trajectory easily deviates from the desired path and leads to a collision, or even the destruction of the robot or cable. Addressing this problem, a path-following control method for the dual-tracked chassis robot based on a self-coupling PID (SCPID) control algorithm was developed. The caterpillar robot dynamics were modelled and both the unknown dynamics and external bounded disturbances were defined as sum disturbances, thus mapping the nonlinear system into a linearly disturbed system, then the self-coupling PD (SCPD) controller was designed. The system proved to be a robust stability control system and only one parameter, the velocity factor, needed to be tuned to achieve parameter calibration. Meanwhile, to solve the problem that the error-based speed factor is not universal and to improve the adaptive ability of the SCPD controller, an iterative method was used for adaptive tuning. The simulation results showed that the SCPID can achieve better control. The field test results showed that the SCPD’s maximum offset angle was 56.7% and 10.3% smaller than incremental PID and sliding mode control (SMC), respectively. The inspection time of the SCPD was 20% faster than other methods in the same environment.

Adaptive Finite-Time Backstepping Integral Sliding Mode Control of Three-Degree-of-Freedom Stabilized System for Ship Propulsion-Assisted Sail Based on the Inverse System Method

The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude of the sail is adjusted to ensure optimal thrust along the target course. An adaptive finite-time backstepping integral sliding mode control based on the inverse system method (ABISMC-ISM) is presented for attitude tracking of the sail. Considering the nonlinear dynamics and strong coupling of the system, a decoupling strategy is established using the inverse system method (ISM). Constructing inverse dynamics to eliminate internal coupling, the system is transformed into independent pseudolinear subsystems. For the decoupled open-loop subsystems, an adaptive finite-time backstepping integral sliding mode control is designed to achieve closed-loop control. A backstepping-based integral sliding surface is proposed to eliminate the phase-reaching stage of the sliding surface. Considering the unmodelled dynamics and external disturbances, an adaptive extreme learning machine (AELM) was designed to estimate the disturbances. Furthermore, a sliding mode reaching law based on finite-time theory was employed to ensure that the system returns to the sliding surface in a finite time under chattering conditions. Experiments on a principle prototype demonstrate the effectiveness and energy-saving performance of the proposed method.

Code generation for Security and Stability Control System based on extended reactive component

The Security and Stability Control System (SSCS) is developed to ensure the safe and stable operation of power grids, effectively mitigating failure propagation through emergency control strategies. However, due to the diversity, complexity, and region-specific nature of SSCS, the need for individualized development often arises, leading to time-consuming and error-prone in SSCS development. To address this challenge, we introduce ERC-Code, an automated development framework that empowers developers to prioritize design over implementation. ERC-Code includes extended reactive component modeling, correctness specifications, and model-to-code transformations. The extended reactive component offers the advantage of capturing the complex logic of SSCS at a high level of abstraction, including loops, branches and synchronizations. The correctness specifications prevent the creation of incomplete and invalid models, ensuring the robustness of the generated code. Additionally, the model-to-code engine automatically generates code from the extended reactive component. Our evaluation covers three key aspects: firstly, we assessed the effectiveness of ERC-Code in three real-world SSCS applications. We then conducted a comparison between the traces generated by ERC-Code and the ERC model. Finally, we conducted an experiment to evaluate developer productivity, drawing comparisons between ERC-Code and a code-centric approach. Our results exhibit promise, affirming ERC-Code’s applicability and code quality, along with enhanced productivity.

Synergizing Wind and Solar Power: An Advanced Control System for Grid Stability

In response to the escalating global energy crisis, the motivation for this research has been derived from the need for sustainable and efficient energy solutions. A gap in existing renewable energy systems, particularly in terms of stability and efficiency under variable environmental conditions, has been recognized, leading to the introduction of a novel hybrid system that combines photovoltaic (PV) and wind energy. The innovation of this study lies in the methodological approach that has been adopted, integrating dynamic modeling with a sophisticated control mechanism. This mechanism, a blend of model predictive control (MPC) and particle swarm optimization (PSO), has been specifically designed to address the fluctuations inherent in PV and wind power sources. The methodology involves a detailed stability analysis using Lyapunov’s theorem, a critical step distinguishing this system from conventional renewable energy solutions. The integration of MPC and PSO, pivotal in enhancing the system’s adaptability and optimizing the maximum power point tracking (MPPT) process, improves control efficiency across key components like the doubly fed induction generator (DFIG), rectifier-sourced converter (RSC), and grid-side converter (GSC). Through rigorous MATLAB simulations, the system’s robust response to changing solar irradiance and wind velocities has been demonstrated. The key findings confirm the system’s ability to maintain stable power generation, underscoring its practicality and efficiency in renewable energy integration. Not only has this study filled a crucial gap in renewable energy control systems, but it has also set a precedent for future research in sustainable energy technologies.

System with nano piezoengine under randomly influences for biomechanics

The sufficient condition of absolute stability system with nano piezoengine by using the derivative of the hysteretic piezoengine deformation is determined for the randomly influences. The set of equilibrium positions of the piezoengine in the control system is stable relative to mathematical expectations, when the condition of absolute stability with the maximum piezo module is met. The statistical linearization method is using for the determination condition of absolute stability control system with the nano piezoengine.

Magnitude-phase equivalent circuit and steady-state power-angle characteristic analysis of DFIG

Circuit model representing generator characteristics is essential in stability analysis and control system design of doubly-fed induction generator (DFIG). This paper develops the relationship between generated voltage and magnetic field in DFIG, and establishes an equivalent circuit model considering rotor motion. The novel magnitude-phase equivalent circuit (MPEC) model is established based on vector magnitude and angle. Furthermore, the paper analyzes phasor diagrams, calculates the power expression under the MPEC, and obtains steady-state power-angle characteristic of the DFIG. In the proposed power-angle characteristic, the DFIG's output incorporates variations in slip ratio and power-angle, which combines the characteristics of asynchronous and synchronous machines. Based on the proposed MPEC and power-angle characteristic, the steady-state maximum power of the DFIG is determined at the critical stable power-angle of π/2. Finally, simulation and experimental results are given to validate the effectiveness of the proposed equivalent circuit model and power-angle characteristic of DFIG. The results show that the MPEC model is capable of analyzing the DFIG stability from the power-angle motion perspective, and the system exhibits a potential for instability when the power-angle exceeds 1.5.

Adaptive multi-mode control system for stability and tracking control of distributed drive automated electric vehicle

Conventional tracking control algorithms of Distributed Drive Automated Electric Vehicles (DDAEVs) are typically designed for a unique control mode, which may lead to poor lateral stability under various driving conditions. Aimed this problem, an Adaptive Multi-mode Control System (AMCS) is proposed. Firstly, according to the adhesion utilization between tires and road surface, the driving condition is classified into three categories, and three control modes corresponding to them are proposed. Secondly, an Adaptive Neuro-fuzzy Inference-based Mode Matching Control System (ANFI-MMCS) is constructed to calculate the matching degree between vehicle states and control modes. Then, in order to achieve the ideal distribution of road wheel angle and yaw moment while avoiding approaching the limit speed corresponding to the reference trajectory, a model predictive control trajectory tracking controller and a speed controller with limitations were built. Finally, to achieve smooth switching between control modes, the outputs of AMCS are weighted according to the matching degree. In the experimental section, AMCS is evaluated on Carsim-Simulink co-simulation platform, and the results under different tests reveal that the proposed controller is more adaptable.