Browse Topic: Stability control
This study investigated the feasibility of using Deep Reinforcement Learning (DRL) for aeroelastic stability control of a Tiltrotor Aeroelastic Stability Testbed (TRAST) model. The DRL controllers use rotor swashplate inputs to minimize oscillatory wing root bending moments of the tilt rotor model. First, three DRL-based agents including Deep Deterministic Policy Gradient (DDPG), Twin Delayed Deep Deterministic Policy Gradient (TD3), and Soft Actor-Critic (SAC) were investigated to control the aeroelastic stability of the TRAST model throughout a wide range of airspeed including where the whirl flutter occurs. All three agents demonstrated the capability of stability augmentation while the SAC agent demon-strated the most robust performance. Next, the effectiveness of the SAC agent was studied further by training the SAC agent at a certain airspeed and applying the trained agent through the TRAST whirl flutter conditions. Finally, additional tuning of the SAC agent was performed to improve performance further through a hyperparameter optimization framework called Optuna.
This study presents an integrated vehicle dynamics framework combining a 12-degree-of-freedom full vehicle model with advanced control strategies to enhance both ride comfort and handling stability. Unlike simplified models, it incorporates linear and nonlinear tire characteristics to simulate real-world dynamic behavior with higher accuracy. An active roll control system using rear suspension actuators is developed to mitigate excessive body roll and yaw instability during cornering and maneuvers. A co-simulation environment is established by coupling MATLAB/Simulink-based control algorithms with high-fidelity multibody dynamics modeled in ADAMS Car, enabling precise, real-time interaction between control logic and vehicle response. The model is calibrated and validated against data from an instrumented test vehicle, ensuring practical relevance. Simulation results show significant reductions in roll angle, yaw rate deviation, and lateral acceleration, highlighting the effectiveness of the proposed approach. Overall, the framework offers a scalable and robust foundation for developing adaptive stability control systems in modern four-wheeled vehicles
How a mechanically simple idea has kept cars stable for decades, and why it can still evolve for an autonomous future. Since debuting in 1995, Bosch's electronic stability program (ESP) has become one of the most essential safety features in modern vehicles. It's now a standard on nearly every new car sold in America and has been deployed in over 350 million vehicles worldwide. ESP is more than just legacy tech. It's the foundation behind advanced driver assistance, motion control and a more automated future.
Direct debugging of a vertical takeoff and landing (VTOL) fixed-wing aircraft’s control system can easily result in risk and personnel damage. It is effectively to employ simulation and numerical methods to validate control performance. In this paper, the attitude stabilization controller for VTOL fixed-wing aircraft is designed, and the controller performance is verified by MATLAB and visual simulation software, which significantly increases designed efficiency and safety of the controller. In detail, we first develop the VTOL fixed-wing aircraft’s six degrees of freedom kinematics and dynamics models using Simulink module, and the cascade PID control technique is applied to the VTOL aircraft’s attitude stabilization control. Then the visual simulation program records the flight data and displays the flight course and condition, which can validate the designed controller performance effectively. It can be concluded that the designed VTOL fixed-wing aircraft control visual simulation system, can demonstrate the effectiveness of the control algorithm, which has a wide range of potential applications.
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