Showing 2 results for Disturbance
Dr Hossein Chehardoli,
Volume 13, Issue 3 (9-2023)
Abstract
In this article, the optimal robust H2 / H∞ control of self-driving car platoons (SDCPs) under external disturbance is investigated. By considering the engine dynamics and the effects of external disturbance, a linear dynamical model is presented to define the motion of each self-driving car (SDC). Each following SDC is in direct communication with the leader. By utilizing the relative position of following SDCs and the leader, the error dynamics of each SDC is calculated. The particle swarm optimization (PSO) method is utilized to find the optimal control gains. To this aim, a cost function which is a linear combination of H2 and H∞ norms of the transfer function between disturbance and target variables is constructed. By employing the PSO method, the cost function will be minimized and therefore, the robustness of the controller against external disturbance is guaranteed. It will be proved that under the presented robust control method, the negative effects of disturbance on system performance will significantly reduce. Therefore, the SDCP is internally stable and subsequently, each SDC tracks the motion of the leader. In order to validate the proposed method, simulation examples will be presented and analyzed.
Mr. Pooriya Sanaie, Dr. Morteza Mollajafari,
Volume 15, Issue 1 (3-2025)
Abstract
Electric Power Steering (EPS) systems are increasingly being integrated into modern vehicles, offering enhanced fuel efficiency and improved maneuverability. However, these systems are often subject to noise and disturbances, which can significantly impact steering precision and driver comfort. Addressing these challenges requires the implementation of robust control strategies capable of mitigating noise and disturbances in EPS systems. This paper explores advanced methods for achieving robust control in Electric Power Steering systems by reducing noise interference and countering external disturbances. Key techniques involve adaptive control algorithms and robust filtering mechanisms that maintain system stability and performance even under variable operating conditions. Experimental results demonstrate that these robust control approaches effectively minimize noise levels and disturbance impacts, leading to smoother steering response and greater reliability. This study underscores the critical role of robust control in enhancing the functionality and safety of Electric Power Steering systems while highlighting the intricate dynamics between noise, disturbances, and control system robustness in automotive applications.
