Precision Motion Control Research Articles

Development of a software platform for automatic train operation: Integrating meso- and microscopic layers

This article presents a comprehensive study on the development and integration of the mesoscopic and microscopic layers within the control architecture of railway systems, enabling autonomous operation. A key outcome of this research is developing a software platform that provides the foundation for improving autonomous train control algorithms. The mesoscopic layer, defined as the high-level component of the automatic train operation (ATO) subsystem, focuses on generating setpoints to control the traction system, which are subsequently transmitted to the low-level component of the ATO subsystem. A simplified model is employed in the mesoscopic layer to enhance planning capabilities and facilitate efficient decision-making processes, while a detailed model represents the physical system. Simulations evaluate the effectiveness of this integrated system, considering various disturbances to thoroughly assess the performance of the mesoscopic layer algorithm and the microscopic layer control system. The results confirm that by successfully integrating these layers, precise and efficient control of train motion is achieved while considering all constraints imposed by the macroscopic layer. Furthermore, this software platform is set for future development, including implementing intelligent control techniques to enhance autonomous train control.

Neural network–based transfer learning to improve stiffness modeling of industrial robots with small experimental data sets

AbstractStiffness modeling is an essential subject for the composition of robot control. Accurate stiffness modeling is helpful for improving the control accuracy of industrial robots, particularly under dynamic load circumstances. The classic virtual joint modeling (VJM) method is challenging in predicting the deformation of the end-effector throughout the full workspace due to the nonlinear deformation of the robot joint and its serial articulated structure. This paper proposes a full-space stiffness modeling method for robots based on the integration of a multi-layer perceptual (MLP) model and VJM. To provide enough training data for the MLP model, VJM is used to build a stiffness model with a small set of experimental data to generate 106,400 training data. A model-based transfer learning approach is proposed to improve the model’s accuracy and generalization regarding the difference between generated training data and actual experimental data. The VJM stiffness model is compared with the MLP stiffness model and the existing CNN-based transfer learning model based on the same experimental data. Considering the deformation prediction in the three directions in Cartesian space, the mean absolute error, standard deviation, and maximum error of the MLP model are decreased by at least 24.90%, 14.20%, and 8.50%, respectively, than the VJM. These prediction results demonstrate that the proposed modeling technique can significantly increase the accuracy of robot stiffness modeling, which is essential for position compensation in precise motion control of robots under dynamic load.

Research on intelligent cutting control technology of transverse moving machine for large cross-section roadheader

With the continuous development of the coal mine industry in our country, the cross-section of the roadway is getting larger and larger. The widely used EBZ series roadheader cannot complete the roadway cutting operation with a large cross-section at one time, so it usually needs to move the equipment left and right to complete all its cutting tasks. This paper studies the intelligent control technology of large cross-section roadway cutting, which mainly solves the positioning and attitude determination technology of roadheader in the large cross-section, and offers an accurate shape-cutting control technology and a path planning technology using a lateral moving machine. This paper proposes to combine the signals of laser sensor and fiber-optic inertial navigation system to form a combined positioning and attitude determination system, so as to make use of the advantages and avoid the disadvantages of their respective systems, and improve the accuracy of roadheader positioning and attitude determination. A swing kinematics model of the cutting arm is established, based on which the precise motion control of the first roadway section cutting and the second roadway section cutting can be realized. A key parameter calculation model of roadheader lateral moving machine is put forward to calculate the operation parameters for roadheader lateral moving machine path planning. Finally, the experimental research on intelligent cutting control technology of large cross-section roadheader is carried out in 12307 intelligent heading face of Wangjialing Coal Mine. The results show that the positioning error of the combined positioning and attitude determination system proposed in this paper is between 50-90 mm in the X-axis direction and between 25-45 mm in the Y-axis direction. The average attitude measurement error of heading angle is between 0.5 and 1.5°. This makes the technology appropriate for engineering use. The studied cutting control system achieves a cutting error of 25-50 mm for the first section, and a cutting error of 40-90 mm for the complete section. The complete section cutting error meets the ±100 mm cutting error requirement required in engineering. The intelligent cutting control technology of the lateral moving machine of the large-section tunnel boring machine studied in this paper can realize accurate cutting of the large-section tunnel of 5.6 meters. The research results of this paper provide a reference for the intelligent construction of heading faces.

Amplifying Colossal Thermal Expansion of a Martensitic Molecular Crystal through Interlayer Shear‐Induced Side‐Chain Liberation

AbstractMolecular crystals capable of colossal thermal expansion (TE) are fascinating owing to their substantial and continuous volume changes and reasonably linear responses to temperature. This makes them promising candidates for micromachine applications. Macroscopic motion is driven by subtle yet cooperative movements of molecules that respond to the thermal motions of dynamic functional units. The study of p‐TIPS‐DSB presented here offers a compelling case highlighting the relationship between the degree of dynamicity of functional units and TE behavior. In its α‐phase, the p‐TIPS‐DSB crystal undergoes an irreversible martensitic transition to the β‐phase, accompanied by significant cooperative interlayer shear. This process substantially enhances the mobility of the side‐chains driven by the increased free volume surrounding them. This nearly doubles the volumetric TE coefficient from 255.3 (10) to 444.9 (32) MK−1, particularly in the actuation direction from 175.0 (7) to 291.7 (20) MK−1, enabling about 4.5 % elongation/contraction. As demonstrated here, p‐TIPS‐DSB exhibits a decent force density (>1.4×107 N m−3) and precise motion control capabilities due to its hysteresis‐free and non‐abrupt TE nature. Furthermore, we demonstrated the limited operating distance of colossal TE materials can be amplified by utilizing levers, highlighting the high potential of these materials for use in micromachines.

A multimodal rotational acoustic manipulation device for hydrophilic/hydrophobic floating and submerged particles

Rotational acoustic manipulation technology offers precise control of particle motion, making it advantageous for applications in microfluidics, biomedicine, materials research, and so on. Current advanced techniques that use acoustic waves to rotate particles include microstructure vibration, microbubble oscillation, and acoustic holography. Although these methods have achieved some success in rotational acoustic manipulation, they face challenges such as limited types of particles, complex device fabrication, and single-mode manipulation. To address these issues, this study proposes a novel rotational acoustic manipulation device based on traveling wave acoustic fields. The traveling wave acoustic field is achieved by planning the vibration modes of the vibrational source. In this study, a ring-shaped piezoelectric ceramic with four-quadrant dual polarization is designed to excite two orthogonal B11 bending vibration modes of the vibrator. By adjusting the phase difference of the excitation signals, these two B11 bending vibration modes can be coupled into either clockwise or counterclockwise traveling wave vibration modes, thereby establishing unidirectional rotating traveling waves in the water within the PDMS ring. The PDMS ring features an open structure, meeting the requirements for manipulating both floating and submerged particles. The performance of the proposed acoustic manipulation device is validated and analyzed through experiments with hollow glass particles, hollow polystyrene particles, and solid polystyrene particles. The results demonstrate that the proposed acoustic manipulation device can achieve precise fixed-point self-rotation and regional revolution manipulation of particles, regardless of their floating, submerged, hydrophilic, or hydrophobic properties. This indicates the high universality and robustness of the device, making it applicable for the manipulation of various types of particles. Overall, this study introduces a novel acoustic manipulation method for particle rotation, providing strong support for the development and application of acoustic manipulation devices in diverse fields.

Development of mathematical modeling of a mobile robot's motion control system

This study focuses on developing a mathematical model for precise control and stabilization of unmanned aerial vehicles (UAVs) in various spatial conditions. Addressing the problem of achieving precise control and stability, the proposed solution designs a control system based on a linear-quadratic controller (LQR) and simulates it using a proportional-derivative (PD) controller implemented in Matlab/Simulink. The results demonstrate high precision and stability in controlling the UAV motion parameters – roll, pitch, yaw, and altitude. This important level of performance is achieved due to the adaptivity of the LQR-based control system, which optimizes control actions according to the unsteady dynamics of the UAV. The integration of the PD controller improves responsiveness and stability, providing precise motion control over a range of spatial states. These features effectively solve the problem by handling the complex dynamics of the UAV and providing precise control. The results are explained by the ability of the LQR to provide optimal control laws that minimize deviations using a quadratic cost function, while the PD controller quickly corrects errors and responds to disturbances. The benefits of this approach include a significant reduction in control errors by about 25–30 %, increased response speed to external disturbances, and reduced computational latency due to efficient processing compared to more resource-intensive methods such as model predictive control. The developed mathematical model can be applied in practice in conditions requiring robust real-time control and adaptation to dynamic changes in the environment. It is especially suitable for industries such as logistics, surveillance, and environmental monitoring, providing an effective and optimal solution for stabilizing and controlling the motion of UAVs in various spatial states. This approach improves the performance of UAVs and expands their capabilities in various operating conditions.

Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force

The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Design and implementation of a multifunctional desktop robot for computer peripherals

Abstract As an important component of the intelligent machinery field, desktop robots not only enrich people’s entertainment lives but are also gradually expanding into applications in education, healthcare, and other fields. However, existing products often struggle to meet the increasingly diverse needs due to short battery life and limited computing resources. In response to this challenge, this study designs a multifunctional desktop robot that can be used as a computer peripheral, which significantly improves power supply and computing capabilities. The design uses the STM32F4 series microcontroller as the main control chip, combined with high-performance servos and their self-developed driver boards, to achieve precise motion control. By integrating USB-HS PHY and USB-CDC protocol, the communication efficiency with the computer is greatly improved, and new screen-driving technology is developed using open-source routines, thus optimizing the user interaction experience. In addition, an innovative adaptive algorithm is incorporated into the firmware program, enhancing the robot’s working stability in different environments. Through systematic hardware debugging and software testing, the robot can achieve efficient performance and stable response when executing complex tasks. This research will promote the expansion of desktop robot technology into broader application fields and support future intelligent work and lifestyle.

Precise motion control for a space mining robot based on improved African vultures optimization

Space mining robots can develop and utilize abundant mineral resources in the outer space to solve the problem of the depletion of earth mineral resources. However, the motion errors of space mining robots in complex environments on the outer space surface of asteroids greatly hinder its applications. To bridge this research gap, a precise motion controller of the space mining robot is proposed in this study. Firstly, the kinematics model of robot’s wheels and the whole vehicle dynamics model in soft soil are established. Then, the optimal PID motion controller is developed based on the improved African vultures optimization algorithm (IAVOA). The Henon chaotic mapping, nonlinear adaptive incremental inertial weight factor and reverse learning competition strategy are introduced to optimize the initial population position, position update method and optimal solution output, respectively. Meanwhile, the excellent optimization performance of IAVOA is also validated by test results of nine benchmark functions. Lastly, the performance of controller is verified by simulations and experiments. The simulation results show that the proposed IAVOA-PID controller is superior to the original PID and AVOA-PID controller with faster response time and smaller overshoot. The experiment results show the space mining robot with the assistance of proposed motion controller can move with a trajectory error of less than 0.2 m and a motion error of less than 0.01 m.

Light-Armed Nitric Oxide-Releasing Micromotor In Vivo.

The delivery of NO at a high spatiotemporal precision is important but still challenging for existing NO-releasing platforms due to the lack of precise motion control and limited biomedical functions. In this work, we propose an alternative strategy for developing the light-armed nitric oxide-releasing micromotor (LaNorM), in which a main light beam was employed to navigate the microparticle and stimulate NO release and an auxiliary light beam was used to cooperate with the released NO to act as a remotely controlled scalpel for cell separation. Benefiting from the advantages of fully controlled locomotion, photostimulated NO release, and microsurgery ability at the single-cell level, the proposed LaNorM could enable a series of biomedical applications in vivo, including the separation of flowing emboli, selective removal of a specific thrombus, and inhibition of thrombus growth, which may provide new insight into the precise delivery of NO and the treatment of cardiovascular diseases.

Research on the application and prospects of variable reluctance inductive sensors

Variable reluctance inductive sensors are extensively utilized in the industrial field due to its unique working mechanism and good performance characteristics. Based on the working principle of Variable Reluctance Inductive Sensors, this paper reviews its development history, application in industrial automation and medical industry. Through the analysis of variable reluctance inductive sensors, variable reluctance inductive sensors have the advantages of high sensitivity, low cost and reliability which can support its wide application in precision measurement, position detection and motion control, but it is susceptible to the interference of the external magnetic field and the influence of the temperature which limits its development space and scope. However, the advancement of new materials, intelligent technologies and multi-mode integration has broadened the potential of future development of sensors and created more challenges for the development of variable reluctance inductive sensors. The update of new research conditions also provides a valuable reference of research and application in related fields

Amplifying Colossal Thermal Expansion of a Martensitic Molecular Crystal through Interlayer Shear-Induced Side-Chain Liberation.

Molecular crystals capable of colossal thermal expansion (TE) are fascinating owing to their substantial and continuous volume changes and reasonably linear responses to temperature. This makes them promising candidates for micromachine applications. Macroscopic motion is driven by subtle yet cooperative movements of molecules that respond to the thermal motions of dynamic functional units. The study of p-TIPS-DSB presented here offers a compelling case highlighting the relationship between the degree of dynamicity of functional units and TE behavior. In its α-phase, the p-TIPS-DSB crystal undergoes an irreversible martensitic transition to the β-phase, accompanied by significant cooperative interlayer shear. This process substantially enhances the mobility of the side-chains driven by the increased free volume surrounding them. This nearly doubles the volumetric TE coefficient from 255.3 (10) to 444.9 (32) MK-1, particularly in the actuation direction from 175.0 (7) to 291.7 (20) MK-1, enabling about 4.5 % elongation/contraction. As demonstrated here, p-TIPS-DSB exhibits a decent force density (>1.4×107 N m-3) and precise motion control capabilities due to its hysteresis-free and non-abrupt TE nature. Furthermore, we demonstrated the limited operating distance of colossal TE materials can be amplified by utilizing levers, highlighting the high potential of these materials for use in micromachines.

An enhancing flexibility piezoelectric stick-slip actuator by introducing perforation of flexible hinge

Piezoelectric stick-slip actuators (PSSAs) utilize sliding friction between the mover and stator to convert and transmit motion. However, the phenomenon of backward displacement often hinders the output performance of PSSAs. This paper proposes a method to mitigate backward displacement and enhance output performance by modifying the overall flexibility of the actuator. The key idea of this approach is to propose a novel flexible hinge structure and apply it to PSSA. Numerical calculations and finite element analysis confirm that the flexibility and output performance of the PSSA are significantly improved. The method's feasibility is supported by comparing experiments. The experimental results show that under the same locking force, the optimal excitation frequency of perforated Elliptical Flexure Hinge (EFH) is significantly lower than the non-perforated EFH and the speed is increased over 53 %. Furthermore, the PSSA has a maximum load capacity of 190 g, which is 31.7 times its own weight (6 g). The proposed PSSA can provide valuable insights for its application in precision motion control systems in the foreseeable future.

Conductive hydrogels‐based self‐sensing soft robot state perception and trajectory tracking

AbstractSoft robots face significant challenges in proprioceptive sensing and precise control due to their highly deformable and compliant nature. This paper addresses these challenges by developing a conductive hydrogel sensor and integrating it into a soft robot for bending angle measurement and motion control. A quantitative mapping between the hydrogel resistance and the robot's bending gesture is formulated. Furthermore, a nonlinear differentiator is proposed to estimate the angular velocity for closed‐loop control, eliminating the reliance on conventional sensors. Meanwhile, a controller is designed to track both structural and nonstructural trajectories. The proposed approach integrates advanced soft sensing materials and intelligent control algorithms, significantly improving the proprioception and motion accuracy of soft robots. This work bridges the gap between novel material design and practical control applications, opening up new possibilities for soft robots to perform delicate tasks in various fields. The experimental results demonstrate the effectiveness of the proposed sensing and control approach in achieving precise and robust motion control of the soft robot.

Development of a numerical and analytical methodology for analyzing hybrid laminates with multi-oriented piezoelectric and structural layers

Piezoelectric materials can generate an electrical response under mechanical stress, functioning as sensors. Conversely, applying an electrical field to these materials enables precise motion control, making them effective as actuators. Using a proposed methodology, this work focuses on evaluating the effective properties of hybrid multi-oriented composite laminates consisting of structural and piezoelectric layers driven by monoclinic constitutive equations. Square unit cell model was used to calculate all coefficients of the material tensor. The finite element (FE) homogenization method and periodic boundary conditions implemented by node-to-node constraint equations are used to study a representative volume element (RVE) modeled as three-layer unit cell in the mesoscale. The pre-processing, FE analysis, and post-processing are conducted in the FE package ABAQUSⓇ through Python scripts. The computational approach yields results that align closely with the analytical effective coefficients derived from the Asymptotic Homogenization Method (AHM), demonstrating the robustness and accuracy of the proposed methodology.

Novel Iontronic Pressure Sensor Coupling High Sensitivity and Wide‐Range for Stiffness Identification and Long‐Distance Precise Motion Control

Novel Iontronic Pressure Sensor Coupling High Sensitivity and Wide‐Range for Stiffness Identification and Long‐Distance Precise Motion Control

An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV “Silver Fox”, considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency.

Data driven digital twin system for the cross-domain vehicle

The Cross-Domain Vehicle (CDV) is a sophisticated marine equipment capable of performing tasks across different domains. This paper aims to develop a data-driven digital twin system for the CDV to achieve precise motion control and data monitoring during its operation. Leveraging the kinematic physical characteristics of the CDV, the digital twin system constructs a virtual counterpart of the vehicle, establishing a mapping relationship between the physical and virtual entities. The use of a Long Short-Term Memory (LSTM) network model is proposed for forecasting the motion state of the CDV within the digital twin framework, supporting the vehicle's autonomous motion decision-making process. Additionally, an innovative model predictive control strategy is employed to achieve surface speed tracking control for the CDV, leveraging predictive data within the digital twin system. Utilizing the digital twin system to optimize control parameters, better underwater depth control effects can be achieved for the CDV. Finally, through the system implementation and experiment verification, the effectiveness of the digital twin system is successfully demonstrated, providing reliable results for both surface speed tracking control and underwater depth control.

A Large-Stroke Reluctance-Actuated Nanopositioner: Compliant Compensator for Enhanced Linearity and Precision Motion Control

A Large-Stroke Reluctance-Actuated Nanopositioner: Compliant Compensator for Enhanced Linearity and Precision Motion Control

Energy-Selected Iterative Learning Control: A Novel Perspective to Analyze Precision Motion Control Tasks

Energy-Selected Iterative Learning Control: A Novel Perspective to Analyze Precision Motion Control Tasks