Anti-roll Control Research Articles

Intelligent control of the Magnus anti-rolling device: A co-simulation approach

In this study, we present an artificial intelligence control method specifically designed for the Magnus anti-rolling device. The core of our approach is the development of a co-simulation framework that integrates an intelligent algorithm with a three-dimensional numerical computational programme within a complex hydrodynamic environment. This integration is achieved through the use of a deep reinforcement learning algorithm, which allows for intelligent adaptation of the anti-rolling device's rotating speed in real time. Our research focuses on evaluating the performance of the intelligent anti-rolling control algorithm under a variety of conditions, including different ship-model roll angles, column geometry models, and varying swinging or slewing speeds. Through numerical studies, we compare the effects of these variables on the effectiveness of the control method. The co-simulation technology provides a platform for testing the intelligent control method. It allows a detailed examination of how the intelligent algorithm interacts with the hydrodynamic responses of the Magnus anti-rolling device, ensuring that the control method can adapt to a wide range of operational scenarios. This adaptability is crucial for maintaining stability and improving the performance of the anti-rolling device in real maritime environments. This study highlights the potential for integrating artificial intelligence with traditional maritime engineering solutions.

Diagnostic methodology for vehicles equipped with antilock braking system and electronic stability control

Currently, several automotive companies are joining forces through the analysis and development of active safety systems for hazard avoidance and mitigation; from which according to the current regulations in the European Union the Anti-lock Braking System (ABS) and the Electronic Stability Control (ESC) outstand as mandatory for each new vehicle. The above has motivated the study of these two safety systems. Then, this research examines the ABS and ESC systems through a proposed diagnostic methodology, which identifies the main effect of these systems on the vehicle dynamics. To achieve this goal a software was developed, looking for processing the data acquired during the development of some specific vehicle maneuvers. The diagnostic results expose: (1) an indicator about the ABS/ESC systems performance; and (2) the impact of these systems on the vehicle dynamics; also, some of the results here obtained can also be taken as reference for the Brake Assistant System and the Anti-Roll Control analysis.

Proposing a new control method for active stabilizer bars using an intelligent self-learning algorithm

This article’s main content is directed toward designing and applying a new control algorithm for automotive stabilizer bars. Previous studies often only used classical control algorithms or simple fuzzy algorithms to control hydraulic anti-roll systems on cars based on safety criteria. In this article, a self-learning algorithm (ANFIS) is established based on inheriting the advantages of previous algorithms. Additionally, this algorithm is modified and improved to increase the convergence of the results after the end of the steering process. Simulations show that when the self-learning solution is applied to active anti-roll bars, the roll angle value and the attenuation of the vertical force at wheels decrease significantly. In complex motion conditions (second case, v3), rollover occurs if the automobile does not have an anti-roll bar. However, roll stability and road holding ability are always ensured when applying the ANFIS algorithm to control active anti-roll bars. According to these findings, the minimum value of the vertical force at the rear wheel can be up to 1384.02 N even when the car is traveling in extremely harsh conditions (second case, v4). In addition, the response speed and convergence of values are always well-controlled when the intelligent self-learning algorithm is applied to the anti-roll control system.

Path Tracking and Anti-Roll Control of Unmanned Mining Trucks on Mine Site Roads

Path Tracking and Anti-Roll Control of Unmanned Mining Trucks on Mine Site Roads

Analysis of Flow Instability and Mechanical Energy Loss of Fluid Field in Fluid Momentum Wheel

A new type of anti-rolling device denoted as a fluid momentum wheel (FMW) is proposed to address the limitations of traditional gyrostabilizers in reducing the roll responses of floating platforms in waves. The proposed device is based on the same gyroscope theorem, which differs from a rigid gyrostabilizer in that the internal fluid generates secondary flow in the cross-section under the combined effects of inertial centrifugal force and a radial pressure gradient, and the streamwise velocity exhibits a non-uniform distribution. These instability phenomena may cause mechanical energy loss in the flow field, which is critical for selecting the driving device and the anti-roll control performance of offshore platforms. In the study, different turbulence models are compared with the results of a Direct Numerical Simulation (DNS) and experiments to ensure the accuracy of the numerical method, and the spatiotemporal distribution characteristics of the flow field in FMW are analyzed. Therein, the SST k-ω model accurately verifies the flow instability phenomenon of the FMW observed in the Particle Image Velocimetry (PIV) experiment. Next, this paper proposes corresponding evaluation parameters to assess the impact of typical parameters on the flow field instability. The results show that the flow instability increases with an increase in the typical parameters of FMWs (such as the pipe diameter, curvature radius, and velocity). Furthermore, the paper discusses the relationship between dimensionless mechanical factors (Reynolds number, curvature ratio) and the spatiotemporal instability of the flow field, revealing the essential effects of the curvature ratio and Reynolds number on the loss coefficient.

Lift analysis and anti-rolling control system design of Magnus rotating roll stabilizer at full speed range

To analyze the impact of the operating mode of the Magnus rotating roll stabilizer on anti-rolling performance, a full speed range lift calculation method is proposed. By combining the micro-element approach with the mechanism of the Magnus effect force, the lift law of the rotating stabilizer in different modes could be obtained theoretically. Subsequently, correction factors are fitted for various operating conditions to correct the full speed range lift model through hydrodynamic simulation analysis of the stabilizer. In addition, RBF neural networks are introduced to approximate uncertain ship models under different modes to achieve anti-rolling control of the Magnus rotating stabilizer in various operating modes. When the stabilizer switches operating mode, this network provides a corresponding adaptive ship model for the sliding mode controller to optimize the anti-rolling effect of the sliding mode controller. The simulation shows that the corrected lift model has good predictive performance. Compared to traditional fin stabilizers and rotating stabilizers, the sliding mode control algorithm based on the RBF neural network can maintain excellent anti-rolling performance at full speed range, with a maximum anti-roll efficiency of over 93%.

Wavelet Neural Network-Based Half-Period Predictive Roll-Reduction Control Using a Fin Stabilizer at Zero Speed

Among the commonly used ship-stabilizing devices, the fin stabilizer is the most effective. Since the lift force of the conventional fin stabilizer is proportional to the square of the incoming flow velocity, it has a better anti-rolling effect at higher speeds but a poor anti-rolling effect at low speeds and even no effect at zero speed. A combination of modelling analysis, simulation, and a model ship experiment is used in this paper to study the zero-speed roll-reduction control problem of the fin stabilizer. A simulation model of the rolling motion of a polar expedition ship is established. The lift model of the fin stabilizer at zero speed is established using the theory of fluid mechanics. The proportional–integral–differential (PID) controller is selected to control the fin to achieve zero-speed roll reduction. To obtain a better anti-rolling control effect under variable sea conditions, a wavelet neural network (WNN)-based half-period prediction algorithm is adopted to update and adjust PID control parameters in real time. A simulation was carried out, and the effectiveness of the proposed predictive control algorithm is proved. A reduced-scale ship model was established to carry out the water tank experiment, and the results verify the theoretical analysis and simulation. The results also verify the effectiveness of the proposed control strategy.

Essential analysis and quantitative evaluation on mechanical-energy loss of fluid momentum wheel

The Fluid Momentum Wheel (FMW), an innovative anti-roll device, requires accurate evaluations of mechanical-energy loss within its flow field due to the direct impact on its anti-roll capability. In this paper, the characteristics of the internal flow field and the essential reasons for the mechanical-energy loss of FMW were analyzed through numerical simulations. The results show that the mechanical-energy loss of FMW can be unified with the form of the traditional empirical formula. However, a substantial relative difference of up to 30.59% was observed between the empirical formula and numerical solutions, indicating limitations of traditional empirical formula in predicting the mechanical-energy loss of the FMW. Secondary flow in the cross-section and the asymmetrical distribution of fluid velocity in the main flow direction were identified as essential factors limiting the traditional formula's accuracy. Next, three dimensionless parameters of Reynolds number, curvature ratio, and center-distance ratio are presented to evaluate the mechanical-energy loss according to the fluid characteristics of FMW. Orthogonal experiments are conducted for parametric sensitivity analysis to study the interactive effects and significance of these parameters on the mechanical-energy loss. Finally, the characteristics of the loss coefficients with the variation of parameters are explained by the results of the flow velocity and turbulent kinetic energy in the cross-section. A linear relationship between the loss coefficients and the logarithm of the Reynolds number at various curvature ratios. Based on the above analysis, a new quantitative evaluation formula for the mechanical-energy loss of FMW is proposed and validated, which can support improved anti-roll control of FMW.

Rudder/fin joint anti-rolling control system based on interference model predictive control and sliding mode observer

To overcome the difficulties of time-varying disturbance, model mismatch, and frequent operation in the rudder/fin joint control system, an interference model predictive control (I-MPC) rudder/fin joint control system with sliding mode observer is proposed. Considering that the model mismatch problem occurs when the ship is sailing, the model mismatch and external disturbance are regarded as the total disturbance. A discrete 3-degree-of-freedom ship disturbance mathematical model is established. The rudder angle and fin angle are selected as the system inputs, then a sliding mode observer is designed to observe the time-varying disturbance and system output in real time. Different from traditional MPC and feedforward compensation, I-MPC will predict the output based on the disturbance observation value, and the control law is solved under rudder/fin angle and angular velocity constraints. Simulation results show that the proposed method improves the tracking performance and anti-disturbance performance of the rudder/fin system. The observer has high observation accuracy for constant, sinusoidal, and time-varying disturbances. Mechanism wear and energy loss caused by frequent operation are avoided.

Coordinated control of ESC with active front steering and active suspension normal force control for better vehicle’s dynamic response

Advances in vehicle technologies brought changes into architectures of integration of chassis control systems. Alongside other improvements, integration can provide better vehicle handling, stability and safety. Different chassis control systems can use different control methods. Considering while in motion vehicle has movements in longitudinal, lateral and vertical direction, different control systems target different motion. If there is no coordination among active control systems, interaction and performance conflict can arise. This paper presents coordination of three control systems: electronic stability control (ESC), active front steering control (AFSC) and active suspension normal force control (ASNF). ESC is actually direct yaw and anti-roll control using selective wheel braking. ASNF is considered only on front axle. All systems use fuzzy-logic as a control method. Vehicle is presented as 14-DOF nonlinear full vehicle model and for the control purposes 3-DOF reference model was introduced. Emphasis was given on vehicle parameters characterizing dynamic behavior in longitudinal and lateral direction. Benefits of coordinated action of the three systems can be seen from the results gained through simulation of cornering event and single lane change in Matlab/Simulink. Coordinated control adds to the action of ESC itself, resulting in improved stability and handling, and thus safety of the vehicle.

Analysis and Roll Prevention Control for Distributed Drive Electric Vehicles

This work presents an approach to improve the roll stability of distributed drive electric vehicles (DDEV). The effect of the reaction torque from the in-wheel motor exerts additional roll moment, which is different from traditional vehicles. The additional roll moment can be achieved by active control of the wheel torque adjustment, which achieves a control effect similar to the active suspension. The anti-roll control strategy of decoupling control of roll motion and yaw motion are proposed. The direct yaw moment is calculated by the linear quadratic regulator (LQR) algorithm while the additional rolling moment is calculated by the sliding mode variable structure. For maneuvering rollover caused by excessive lateral acceleration, an anti-rollover control strategy is designed based on differential braking. A fuzzy control theory is used to decide the yaw moment to be compensated. The distribution method of the braking torque applied to the outer wheel alone, and the lateral load transfer rate is the main evaluation index for simulation verification of typical working conditions. The simulation results show that the proposed control strategy for DDEV is effective.

Intelligent ship anti-rolling control system based on a deep deterministic policy gradient algorithm and the Magnus effect

Anti-rolling devices are widely used in modern shipboard components. In particular, ship anti-rolling control systems are developed to achieve a wide range of ship speeds and efficient anti-rolling capabilities. However, factors that are challenging to solve accurately, such as strong nonlinearities, a complex working environment, and hydrodynamic system parameters, limit the investigation of the rolling motion of ships at sea. Moreover, current anti-rolling control systems still face several challenges, such as poor nonlinear adaptability and manual parameter adjustment. In this regard, this study developed a dynamic model for a ship anti-rolling system. In addition, based on deep reinforcement learning (DRL), an efficient anti-rolling controller was developed using a deep deterministic policy gradient (DDPG) algorithm. Finally, the developed system was applied to a ship anti-rolling device based on the Magnus effect. The advantages of reinforcement learning adaptive control enable controlling an anti-rolling system under various wave angles, ship speeds, and wavelengths. The results revealed that the anti-rolling efficiency of the intelligent ship anti-rolling control method using the DDPG algorithm surpassed 95% and had fast convergence. This study lays the foundation for developing a DRL anti-rolling controller for full-scale ships.

Rollover stability and anti-roll control of sport utility vehicle with driver in the loop

Rollover stability and anti-roll control of sport utility vehicle with driver in the loop

Rollover stability and anti-roll control of sport utility vehicle with driver in the loop

Rollover stability and anti-roll control of sport utility vehicle with driver in the loop

Anti-roll control and maneuverability test of X-rudder autonomous underwater vehicle

Anti-roll control and maneuverability test of X-rudder autonomous underwater vehicle

Research on Path Tracking and Anti-roll Control of Commercial Vehicle Based on Takagi-Sugeno Fuzzy Model

Abstract With the increasing demand for intelligent commercial vehicles, the path tracking technology of commercial vehicle autonomous driving systems has become a research hotspot. However, commercial vehicles are prone to roll over when they are making an emergency obstacle avoidance or making a sharp turn on the road surface with high adhesion coefficient, resulting in serious traffic accidents. In this paper, a steering control method based on the T-S fuzzy model for automatic driving of commercial vehicles is proposed, which takes path tracking and anti-roll as control objectives. Firstly, the three-degree-of-freedom model of commercial vehicle and the vehicle-road dynamic model was established to obtain the vehicle-road general model. Then, considering the influence of the nonlinear change of vehicle speed on the system performance, the speed is taken as the variable parameter of the system. Taking the speed as the prerequisite variable, the fuzzy rule is designed, and the vehicle-road model is transformed into a T-S fuzzy model. Then, the fuzzy controller is designed according to the Lyapunov method and the parallel distributed compensation (PDC) algorithm. Finally, sufficient conditions for the system to satisfy the H∞ performance index under the action of the fuzzy controller are given in the form of linear matrix inequality (LMI). LMI toolbox is used to solve the problem, and the robustness of the system is guaranteed. Simulation results show that the system can ensure the accuracy of path tracking and greatly reduce the risk of vehicle rollover.

Using gyro stabilizer for active anti-rollover control of articulated wheeled loader vehicles

Articulated wheeled loader vehicles have frequent rollover accidents as they operate in the complex outdoor environments. This article proposes an active anti-rollover control method based on a set of single-frame control moment gyro stabilizer installed on the rear body of the vehicle. The rollover dynamic model is first established for articulated wheeled loader vehicle with gyro stabilizer. The proposed control strategy is then applied in simulation to verify the rollover control effect on the vehicle under steady-state circumferential conditions. Finally, a home-built articulated wheel loader vehicle with gyro stabilizer is used to further verify the proposed control strategy. The results show that the vehicle can quickly return to the stable driving state and effectively avoid the vehicle rollover when a suitable anti-roll control moment can be provided by the gyro stabilizer. As a result, the articulated wheeled loader vehicle is able to operate safely in a complex outdoor environment.

Influences of Driver on Vehicle Rollover Stability and Anti-roll Control

Influences of Driver on Vehicle Rollover Stability and Anti-roll Control

Switched anti-roll control design for hydraulically interconnected suspension system with time delay

To improve a vehicle's anti-roll performance while consuming less energy, an active/passive dual-mode switched control method based on a hydraulically interconnected suspension (HIS) is proposed. This method has two key components as follows: modelling the “mechanical-liquid-gas” coupled dynamic system consisting of hydraulic cylinders, a hydraulic pump and accumulators; and robustly controlling a time-delayed system with uncertain model and lag time. In this study, the nonlinear characteristics of the underlying actuators were considered, and a four degrees-of-freedom (4DOF) roll-plane half-car model was employed. The backstepping algorithm was adopted to maintain the body in the desired posture. Subsequently, a modified Smith predictor and a Taylor expansion of lateral acceleration were applied simultaneously to compensate for the time delay. Finally, simulations with uncertain parameters and lag time were performed. The results indicate that the proposed method is robust in the case of an uncertain control system and can effectively improve the vehicle's anti-roll performance.

Switched anti-roll control design for hydraulically interconnected suspension system with time delay

To improve a vehicle's anti-roll performance while consuming less energy, an active/passive dual-mode switched control method based on a hydraulically interconnected suspension (HIS) is proposed. This method has two key components as follows: modelling the “mechanical-liquid-gas” coupled dynamic system consisting of hydraulic cylinders, a hydraulic pump and accumulators; and robustly controlling a time-delayed system with uncertain model and lag time. In this study, the nonlinear characteristics of the underlying actuators were considered, and a four degrees-of-freedom (4DOF) roll-plane half-car model was employed. The backstepping algorithm was adopted to maintain the body in the desired posture. Subsequently, a modified Smith predictor and a Taylor expansion of lateral acceleration were applied simultaneously to compensate for the time delay. Finally, simulations with uncertain parameters and lag time were performed. The results indicate that the proposed method is robust in the case of an uncertain control system and can effectively improve the vehicle's anti-roll performance.