In adapting to the demands of this modernized landscape, a conventional human-operated forklift within an industrial or warehouse setting falls short. However, the adoption of autonomous forklifts remains a distant prospect for many companies, primarily due to the formidable implementation and switching costs associated with artificial intelligence and complex control mechanisms. To bridge this gap, we present the development of a teleoperated forklift utilizing mecanum wheels for enhanced maneuverability. A key contribution of this work lies in the design of a novel synchronization method for the precise position control of the pallet carriers. This method surpasses the conventional independent and master–slave approaches, demonstrably achieving superior tracking and synchronization performance. Also, a model-based velocity control algorithm was designed for the mecanum wheels to facilitate the mobility of the system. The forklift was successfully able to carry a maximum load of 300 kg. For the comparison of the tracking and synchronization performance, the independent and master–slave methods were also applied to the system. The proposed method showed better performance compared to other structures.

Synchronous control of multi-motor systems (MMS) is attracting attention as a method to achieve the objectives of accurate operation, load distribution, vibration, and noise reduction while responding to the demands of large forces, high speed, etc. in industrial sites. The performance of synchronous control is evaluated by command tracking and synchronization between motors. In order to improve these two goals, the existing synchronous control structures mainly designed controllers in the case of command tracking, and synchronization between motors used a compensation method using synchronous error. However, this method makes it difficult to analyze or control the level of synchronous error. This paper presents a novel control structure that directly controls tracking commands and synchronous errors by setting the input and output mean and differences of MMS as control targets. The model applying the proposed structure can reduce the resonance due to the combined compliance of the MMS in the input and output relationship, which has been validated by the experimentally measured frequency response function. In addition, experiments were conducted to verify the effectiveness of synchronous control performance when the proposed control structure was applied. The algorithm was constructed using Matlab/Simulink, and the actual equipment was controlled using a data acquisition (DAQ) board. In order to compare the existing synchronous control structures with the proposed control structure, a model-based controller based on dynamic analysis was designed, and the results were derived through two commands. Through this, it was verified that the proposed control structure can improve synchronous control performance.

Since the steer-by-wire system removes the mechanical connection and uses electrical signals to drive the system, it has the disadvantage of being less stable in the failure of parts or systems. Therefore, in this paper, we present a methodology for developing a digital model of the road wheel actuator of the steer-by-wire system. First, the detailed dynamics of the road wheel actuator are analyzed and simplified, and the friction model is estimated and compensated to obtain the equilibrium inertia and damping coefficient of the motor and the road wheel actuator. And to verify the accuracy of the digital model developed based on these parameters, the outputs are compared by giving the same inputs under open-loop control. Furthermore, to solve the problem caused by nonlinear disturbance and model uncertainty, a disturbance observer-based position controller is proposed. The validity of the proposed controller and the validity of the digital model development methodology are confirmed by the results of the position control experiment.

This paper presents a high-order model-based robust control strategy for a dual-motor road wheel actuating system in a steer-by-wire (SbW) architecture. The system consists of a belt-driven and a pinion-driven motor collaboratively actuating the road wheels through mechanically coupled dynamics. To accurately capture the interaction between actuators, structural compliance, and road disturbances, a four-degree-of-freedom (4DOF) lumped-parameter model is developed. Leveraging this high-order dynamic model, a composite control framework is proposed, integrating feedforward model inversion, pole-zero feedback compensation, and a disturbance observer (DOB) to ensure precise trajectory tracking and disturbance rejection. High-fidelity co-simulations in MATLAB/Simulink and Siemens Amesim validate the effectiveness of the proposed control under various steering scenarios, including step and sine-sweep inputs. Compared to conventional low-order control methods, the proposed approach significantly reduces tracking error and demonstrates enhanced robustness and disturbance attenuation. These results highlight the critical role of high-order modeling in the precision control of dual-motor SbW systems and suggest its applicability in real-time, safety-critical vehicle steering applications.

This article proposes a mode-decoupled control framework for steering position regulation in electronic corner modules based vehicles. In vehicles based on eCM, where each module integrates steering, braking, driving, and suspension, the absence of mechanical linkage can cause unequal steering responses between wheels and reduced driving stability. To address this issue, the proposed framework transforms the steering dynamics of individual wheels into two modal dynamics: a common steering motion and wheel synchronization. Based on this two-mode formulation, steering patterns are expressed as combinations of the two modal components. The experiments show improved steering angle reference tracking and reduced wheel synchronization error compared to conventional wheel-level control.