Mechatronics最新文献

This article presents a novel adaptive contour control scheme for dual-linear-motors-driven gantry stages (DLMDGSs) with time-varying model parameters and disturbances, aiming to realize high-precision contour control. Specifically, a novel adaptive contour controller based on a coupled model is proposed, incorporating powerful projection adaption laws, to achieve the synchronization of multi-axis motors, regression of adaptive parameters, and high-precision contour performance. Additionally, a contour error estimation (CEE) method with four-order convergence rate is designed to ensure estimation accuracy, enhance estimation robustness, and reduce estimation time. Moreover, considering the periodicity of common control contour tasks, an iterative learning control (ILC) reference trajectory compensation structure is adopted to further improve the contour control effect. Finally, the stability and convergence of the closed-loop system are rigorously proven, and comparative experiments are conducted on a DLMDGS platform to demonstrate the superiority of the proposed control strategy.

In mechanical shaft driven roll-to-roll (R2R) printing systems, tension propagation caused by the regulation of dancer rolls increase the control difficulty of the whole system. In this paper, a cooperative compensate control (CoComC) method is proposed for the R2R printing systems to attenuate tension fluctuation and reduce the register errors. Specifically, a mechanical model is established to quantify the relationship among the web tension, linear velocity of dancer roll and register error. Based on the model, a well-tuned feedback control law is designed for each dancer roll, and a cooperative matrix is proposed to coordinate the feedback control to attenuate the tension fluctuation and reduce the register error in the corresponding printing unit. Further, the stability and convergence condition of the proposed control system are provided and proved via Lyapunov stability theory. The effectiveness of the proposed control method is demonstrated by experiments. Comparisons of the existing control method are carried out to show the superior performance of CoComC, i.e., higher register accuracy, superior fluctuation attenuation performance and less waste of printing material.

We present a 4-degrees-of-freedom (4-DoF) wearable haptic device for the palm, able to provide the sensation of interacting with slanted surfaces and edges. It is composed of a static upper body, secured to the back of the hand, and a mobile end-effector, placed in contact with the palm. They are connected by two articulated arms, actuated by four servo motors housed on the upper body and along the arms. The end-effector is a foldable flat surface that can make/break contact with the palm to provide pressure feedback, move sideways to provide skin stretch and tangential motion feedback, and fold to elicit the sensation of interacting with different curvatures. The paper presents the design of the wearable haptic device, together with its mobility, statics, and manipulability, as well as direct, inverse, and differential kinematics. We also present a position control scheme for the device, which is then quantitatively evaluated.

Cross-coupled iterative learning control (ILC) can improve the contour tracking performance of manufacturing systems significantly. This paper aims to develop a framework for norm-optimal cross-coupled ILC that enables intuitive tuning of time- and iteration-varying weights of the exact contour error and its tangential counterpart. This leads to an iteration-varying ILC algorithm for which convergence conditions are developed. In addition, a resource-efficient implementation is developed that reduces the computational load significantly and enables the use of long reference signals. The approach is experimentally validated on an industrial flatbed printer.

In this study, we analyze the hysteresis behavior of robotic joints equipped with harmonic drivers under various speeds and loads, focusing on a range of hysteresis models including the Bouc–Wen (BW), Fractional Order Bouc–Wen (FOBW), and their integration with the Krasnoselskii–Pokrovskii (KP) model. This integration, which forms the KP-FOBW model, is a novel aspect of our research, offering an enhanced understanding of non-linear and hysteresis behaviors in robotic joints. We employ the Monte Carlo method, particularly focusing on the Stochastic Gradient Hamiltonian Monte Carlo (SGHMC), for precise parameter identification. Our results demonstrate that the FOBW model, especially when combined with the KP model, provides a more accurate representation of the hysteresis curves under varying operating conditions. The KP-FOBW combination emerges as a powerful tool to predict the output torque in robotic joints. This study contributes to a deeper understanding of hysteresis in joints with harmonic drivers, showcasing its potential for complex dynamic modeling in robotics.

To enhance the precision of on-orbit assembly for large space optical telescopes, the control of attitude motion in the Autonomous Space-based Simulator (ASS) is imperative. This paper presents a robust finite-time trajectory tracking control method aimed at improving the position and attitude tracking performance of ASS. Considering the dynamic characteristics inherent in ASS, we introduce an improved non-singular fast terminal sliding mode controller (INFTSMC) incorporating an adaptive fuzzy mechanism to attain finite-time error convergence and robust control. The adaptive fuzzy logic control (AFLC) method yields an equivalent gain, eliminating discontinuous switching in terminal sliding mode control (TSMC). This reduction minimizes chattering in control inputs and compensates for uncertainties and time-varying disturbances within the dynamic model. The proposed method’s effectiveness is validated through comprehensive simulation and experimental studies.

The development of ultrasensitive silicon-based microcantilevers has significantly improved the imaging resolution of the Atomic Force Microscope (AFM). However, most of these microcantilevers require one or more external actuators and sensors for imaging, thus increasing the footprint and operational complexity of the instrument. Here we propose a novel active microcantilever that does not require any external actuator apart from the sample positioner to perform high-resolution AFM imaging. The proposed microcantilever is equipped with two different on-chip actuators: a piezoelectric actuator for oscillating the probe at a high frequency and an electrothermal actuator for providing large-range Z-motion. An on-chip differential piezoelectric sensor measures probe oscillation during imaging. To demonstrate the proof of concept, the microcantilever was microfabricated and integrated with an in-house developed AFM setup comprising of sample positioner and drive electronics. Finally, 3 different calibration gratings were imaged with a closed-loop bandwidth of $150\mathrm{Hz}$.

In Networked Control System (NCS), the absence of physical communication links in the loop leads to relevant issues, such as measurement delays and asynchronous execution of the control commands. In general, these issues may significantly compromise the performance of the NCS, possibly causing unstable behaviours. This paper presents an original approach to the design of a complete digital control unit for a system characterized by a varying sampling time and asynchronous command execution. The approach is based on the Embedded Model Control (EMC) methodology, whose key feature is the estimation of the disturbances, errors and nonlinearities affecting the plant to control and their online cancellation. In this way, measurement delays and execution asynchronicity are treated as errors and rejected up to a given frequency by the EMC unit. The effectiveness of the proposed approach is demonstrated in a real-world case-study, where the NCS consists of a differential-drive mobile robot (the plant) and a control unit, and the two subsystems communicate through the web without physical connection links. After a preliminary verification using a high-fidelity numerical simulator, the designed controller is validated in several experimental tests, carried out on a real-time embedded system incorporated in the robotic platform.

Teleoperation technology has become a feasible solution for the mobile manipulator to carry out complex tasks in remote environments, with its advantages of mobility and manipulability. However, due to the high redundancy of the mobile manipulator, its application in the field of teleoperation inevitably suffers from the problem of heterogeneity. This paper proposed an automatic-switching-based teleoperation framework with asymmetrical mapping and force feedback. Namely, special coefficients are designed to automatically switch the motion states of the remote robot, so that the traditional manual-based switching strategy can be replaced. Based on these coefficients, the hybrid asymmetrical mapping including the position–velocity and position–position modes can be achieved, as well as the force feedback considering the switching between the remote mobile platform and the manipulator, and thereby accomplishing the automatic switching during the teleoperation of the mobile manipulator. The comparative experiments and user study were carried out on the teleoperation platform. The experimental results show that this proposed teleoperation framework can reduce the time needed to complete the tasks and decrease the decision-making pressure of the operator, thus demonstrating the feasibility of the proposed framework.