In the existing literature, studies on position controller design using only position feedback, considering the disturbances for single-rod electro-hydrostatic actuators (EHAs), have not been reported. Herein, we propose a robust nonlinear position control with an extended state observer (ESO) for single-rod EHAs. A new EHA model that consists of position, velocity, and acceleration with an internal state variable is developed. Instead of the separated port pressure dynamics, the acceleration dynamics were defined. The external disturbance, model, and input function uncertainties were lumped into a disturbance. An ESO is developed to estimate the disturbance, as well as the position, velocity, and acceleration. In practice, it is difficult to accurately estimate the disturbance because it includes the external disturbance, system dynamics, and input function uncertainty. The poor estimation performance may degrade the position tracking performance, but a high gain cannot be used to suppress the estimation error because of the measurement noise amplification. To resolve this problem, a robust nonlinear position controller is developed via a backstepping procedure. In the controller, a nonlinear gain is implemented to sufficiently suppress position tracking without the use of a high gain. The stability of the closed-loop system is mathematically proven using the input-to-state stability. The proposed method is simple and suitable for real-time control.

In this study, we present an innovative approach to risk assessment for rear-end collision avoidance using a cooperation concept for an autonomous lane change system. A Kalman filter is designed to estimate the longitudinal acceleration and predict the relative longitudinal position, velocity, and acceleration. Risk assessment is performed using the predicted motion of the object vehicle in the target lane. The cooperation concept is proposed to improve the flexibility of the lane change. If the risk assessment for the lane change indicates collision risk, the cooperativeness of the driver of the object vehicle is determined. If the driver of the object vehicle is regarded as a cooperative driver, within the original lane, the ego vehicle moves toward the target lane in preparation for the lane change. Subsequently, as soon as the risk assessment indicates that there is no collision risk, the lane change is performed. Thus, unlike conventional methods, the autonomous lane change using the proposed risk assessment can be initiated. Furthermore, the proposed risk assessment using cooperation concept is more flexible compared with previous methods for autonomous lane change in cluttered traffic.

This paper proposes a collision avoidance method for vehicle longitudinal velocity control based on multi-vehicle collision distance estimation. The method begins by estimating the position and shape of object vehicles with collision risk using environmental sensors. The collision point is identified from the object vehicle’s surface, and a Kalman filter is applied for accurate estimation. The optimal collision distance is then determined by evaluating the collision risk at the identified point. A longitudinal control technique, incorporating the optimal collision distance and time gap, is employed to implement the collision avoidance system. The proposed method was validated through scenario-based simulations involving multi-vehicle collision avoidance, which were implemented in an environment combining ROS and the MORAI simulator, along with comparative experiments. Comparative studies with conventional vehicle center-based approaches demonstrated that the proposed surface-based collision point method significantly enhances collision avoidance performance. While the conventional method led to a collision between the ego and object vehicles, the proposed method successfully avoided the collision by maintaining a separation of about 3.6 m, demonstrating its feasibility and reliability.

In this paper, a nonlinear differential braking control method is developed to avoid collision during lane change under driver torque. The lateral dynamics consist of lateral offset error and yaw error dynamics and can be interpreted as a semi-strict feedback form. In the differential braking control problem under the driver torque, a matching condition does not satisfy, and the system is not in the form of, the strict feedback form. Thus, a general backstepping control method cannot be applied. To overcome this problem, the proposed method is designed via the combination of the sliding mode control and backstepping. Two sliding surfaces are designed for differential braking control. One of the surfaces is designed considering the lateral offset error, and the other sliding surface is designed using the combination of the yaw and yaw rate errors as the virtual input of the lateral offset error dynamics. A brake steer force input is developed to regulate the two sliding surfaces using a backstepping procedure under the driver torque. Integral action and a super twisting algorithm are used in the lateral controller to ensure the robustness of the system. The proposed method, which is designed via the combination of the sliding mode control and backstepping, can improve the lateral control performance using differential braking. The proposed method is validated through simulations.

Because of their substantial weight and high centers of gravity, commercial vehicles require braking systems that ensure maximum performance and safety. Accurate braking control is vital for preserving safe vehicle dynamics by preventing lateral instability due to excessive deceleration or rear-wheel lock-up. Considering the growing demand for safety in medium-duty commercial vehicles, we introduce a rule-based dynamic braking controller for pneumatic electronic parking brake (EPB) systems. The proposed system is established using a model-based design (MBD) framework involving a V-cycle development process. The rule-based controller is designed to control the braking force based on wheel slip, thereby ensuring both adequate braking distance and lateral stability during emergency braking. Simulations and real-vehicle tests confirmed that the proposed control strategy can maintain lateral stability across varying loading and road-surface conditions. The results highlight the dynamic braking capability of the proposed pneumatic EPB system and its feasibility as an emergency braking solution. The effectiveness of the proposed controller in preventing wheel lock supports the use of MBD for developing safety-aware controllers.

Optimizing the performance of motion control systems with variations in nonlinear parameters is not an easy task. To accomplish this task, it is important to design the controller using the linear system approach. In this study, a linear parameter varying (LPV) control method is proposed in which nonlinearities are treated as parameter variations for planar motors. The proposed control method consists of the force and torque modulation with the commutation scheme and the nonlinear current controller with H_∞ state feedback control in the form of LPV synthesis to improve the position-tracking performance. An interpolated gain-scheduling controller based on LPV synthesis is determined by applying H_∞ control to a linear matrix inequality technique. An interpolated gain-scheduling controller can attenuate disturbance without disturbance estimation. The effectiveness of the proposed control method is evaluated using simulation results and compared with the conventional proportional–integral–derivative control to verify both improved position-tracking performance and disturbance attenuation.