Mingyao Ma

Bio: Mingyao Ma is an academic researcher from Hefei University of Technology. The author has contributed to research in topics: Low voltage & Fault (power engineering). The author has an hindex of 1, co-authored 2 publications receiving 20 citations.

Active Front Steering-Based Electronic Stability Control for Steer-by-Wire Vehicles via Terminal Sliding Mode and Extreme Learning Machine

Abstract: In this article, a novel active front steering (AFS) control strategy including the upper controller and the lower controller is proposed to improve the yaw stability and maneuverability for steer-by-wire (SbW) vehicles. The adaptive recursive integral terminal sliding mode (ARITSM) control is adopted in the upper controller for guaranteeing the convergence performance of both the actual sideslip angle and the yaw rate with strong robustness and fast convergence rate. Then, a fast nonsingular terminal sliding mode (FNTSM) control with extreme learning machine (ELM) estimator to estimate its equivalent control is designed in the lower controller to track the desired front wheel steering angle calculated from the upper controller for driving the sideslip angle and the yaw rate to converge ideal value. It is shown that the upper controller takes two controlled variables (vehicle sideslip angle and yaw rate) and only one control input (front steering angle) into consideration, which can obtain a better performance compared with the case of using only one of these values. Since using the ELM technique in the lower controller to estimate the equivalent control of the FNTSM, not only the dependence of SbW system dynamics can be alleviated in the process of designing controller but also the excellent steering control performance can be achieved. Comparative simulations are carried out by utilizing Carsim and Matlab software to validate the excellent performance of the proposed control strategy for different steering maneuvers.

Robust Backstepping Super-Twisting Sliding Mode Control for Autonomous Vehicle Path Following

Abstract: This paper focuses on the path following control problems for autonomous driving vehicles. Aiming at enhancing the robustness and attenuating the chattering phenomenon, a super-twisting sliding mode control algorithm (STA) is developed based on Lyapunov theory, where the proof of the stability of the control system is presented by applying the backstepping technique. Moreover, co-simulation between Matlab/Simulink and Carsim is carried out to verify the path following control performance. In this research, Stanley controller, conventional sliding mode control (SMC), and model predictive control (MPC) are used as the benchmark controllers for evaluating the proposed STA performance. Two driving scenarios are considered in the simulations, including normal driving and fierce driving. To comprehensively assess the control performance and control effort (i.e. magnitude of steering), an integrated and weighted performance evaluation index $\left ({IWPEI }\right)$ is novelly provided. Simulation results show that the $IWPEI$ of the proposed STA can be reduced by 40.5%, 25.8%, 10.9% in the normal driving scenario; and 62.5%, 24%, 6.8% in the fierce driving scenario as compared with Stanley controller, conventional SMC, and MPC, respectively. The results also indicate that the proposed STA outperforms the conventional SMC in terms of the chattering attenuation, resulting in a smoother front steering wheel angle input and a smoother yaw rate performance. As compared with MPC, the advantage of the proposed STA lies in its much lower computational complexity. Furthermore, the robustness of the controllers is verified by changing the vehicle mass and tire parameters. The proposed STA can reduce the fluctuation of the $IWPEI$ by 22.6%, 22.3%, and 5.9% compared with the benchmark approaches. These results imply that the consideration of system perturbations is very critical in the design of the super-twisting sliding mode controller which can improve the robustness of the autonomous vehicle path following system.

Fractional-order sliding mode control based guidance law with impact angle constraint

Abstract: In this paper, the terminal guidance problem of unpowered lifting reentry vehicle to stationary target is studied. Based on the requirement of attacking the target with high precision and high impact angle constraint, a fractional-order theory combined sliding mode guidance law is proposed. Its sliding surface is specially designed to satisfy the requirements in the terminal guidance phase. The novel fractional-order sliding mode guidance law is established in both two-dimensional environment and three-dimensional environment; then, the systems are proved to be asymptotically stable according to the Lyapunov stability principle. Finally, compared with the one without fractional-order term, experiments show the novel guidance law has better stability. Monte Carlo simulation verifies that the designed guidance law is more robust against the disturbance of random noise and ensures higher precision in terms of impact angle error and miss distance.