High Precision Motion Control Research Articles

Rapid phase current sampling in a permanent magnet synchronous motor servo system utilizing flexible memory controller bus

Background The permanent magnet synchronous motor (PMSM) servo system, integral to robots and other high-precision motion control applications, has its performance directly influenced by the current loop in the PMSM servo system. Though the theoretical adjustment time of the current loop can approach the electrical time constant of PMSM in order of magnitude, constraints such as control frequency make the adjustment time significantly larger than this theoretical limit. Methods This paper introduces a PMSM servo system using a flexible memory controller (FMC) bus for rapid phase current sampling. It leverages an independent current sampling module, equipped with an external analog-to-digital (AD) conversion chip for precise sampling of the output phase current of the PMSM. The sampling precision is 16-bit with a range of 0-3V. The sampled signal is preprocessed by a field-programmable gate array (FPGA), with the phase current data finally transmitted to the primary control chip through the FMC bus. Results By implementing this rapid current sampling architecture, we have successfully reduced the current sampling time by 95.4% while maintaining sampling accuracy. This scheme also substantially shortens the microcontroller unit’s (MCU) interrupt response time, potentially enhancing the current loop's control frequency, ultimately increasing the current loop bandwidth to 20kHz. Conclusions In conclusion, the proposed PMSM servo system with rapid current sampling significantly enhances the performance of the current loop. This advancement in sampling efficiency and control frequency offers substantial improvements for high-precision motion control applications, making it a valuable contribution to the field.

The Design and Real-Time Optimization of an EtherCAT Master for Multi-Axis Motion Control

To address the issues of low bandwidth, weak real-time performance, and poor synchronization in traditional fieldbuses for multi-axis motion control, a solution for the implementation of an EtherCAT master based on the IgH EtherCAT Master open-source software framework and an embedded hardware platform is proposed. On a hardware platform centered around the AM64x Sitara processor, a Linux real-time operating system based on the Xenomai real-time kernel is constructed, and the IgH master framework is ported to realize a high-performance EtherCAT master. The configuration process of the EtherCAT bus is detailed, a master application program is developed, and methods for the real-time performance optimization of the master—such as exclusive CPU usage by the master process and the optimization of the network card driver—are proposed. Finally, experiments are conducted on a six-axis servo control platform, with the packet analysis of the periodic EtherCAT data frames sent by the master. The experimental results show that the optimized master, under a high-speed communication cycle of 500 microseconds, maintains maximum jitter within 20 microseconds and average jitter within 1 microsecond, meeting the requirements for high-precision multi-axis motion control.

Symmetrical Modeling of Physical Properties of Flexible Structure of Silicone Materials for Control of Pneumatic Soft Actuators

With the ongoing advancements in material technology, the domain of soft robotics has garnered increasing attention. Soft robots, in contrast to their rigid counterparts, offer superior adaptability to the environment, enhanced flexibility, and improved safety, rendering them highly suitable for complex application scenarios such as rescue operations and medical interventions. In this paper, a new type of pneumatic software actuator is proposed. The actuator adopts a combination of a soft structure and pneumatic control, which is highly flexible and versatile. By using the flow of gas inside the soft structure, high-precision and flexible motion control is realized. In the design process, the extensibility and adaptability of the structure are considered, so that the actuator can adapt to different working environments and task requirements. The experimental results show that the pneumatic soft actuator exhibits excellent performance in terms of accuracy, response speed, and controllability. This research provides new ideas and methods for the development of the field of pneumatic actuators and has wide application prospects. The main research content of this paper is as follows: first, the soft pneumatic actuator is modeled and simulated, the structure is optimized on the basis of simulation, and finally, the performance of the actuator is tested.

Design and Analysis of 5-DOF Compact Electromagnetic Levitation Actuator for Lens Control of Laser Cutting Machine.

In laser beam processing, the angle or offset between the auxiliary gas and the laser beam axis have been proved to be two new process optimization parameters for improving cutting speed and quality. However, a traditional electromechanical actuator cannot achieve high-speed and high-precision motion control with a compact structure. This paper proposes a magnetic levitation actuator which could realize the 5-DOF motion control of a lens using six groups of differential electromagnets. At first, the nonlinear characteristic of a magnetic driving force was analyzed by establishing an analytical model and finite element calculation. Then, the dynamic model of the magnetic levitation actuator was established using the Taylor series. And the mathematical relationship between the detected distance and five-degree-of-freedom was determined. Next, the centralized control system based on PID control was designed. Finally, a driving test was carried out to verify the five-degrees-of-freedom motion of the proposed electromagnetic levitation actuator. The results show it can achieve a stable levitation and precision positioning with a desired command motion. It also proves that the proposed magnetic levitation actuator has the potential application in an off-axis laser cutting machine tool.

Policy Learning for Nonlinear Model Predictive Control With Application to USVs

The unaffordable computation load of nonlinear model predictive control (NMPC) has prevented it for being used in robots with high sampling rates for decades. This paper is concerned with the policy learning problem for nonlinear MPC with system constraints, where the nonlinear MPC policy is learned offline and deployed online to resolve the computational complexity issue. A deep neural networks (DNN) based policy learning MPC (PL-MPC) method is proposed to avoid solving nonlinear optimal control problems online. The detailed policy learning method is developed and the PL-MPC algorithm is designed. The strategy to ensure the practical feasibility of policy implementation is proposed, and it is theoretically proved that the closed-loop system under the proposed method is asymptotically stable in probability. In addition, we apply the PL-MPC algorithm successfully to the motion control of unmanned surface vehicles (USVs). It is shown that the proposed algorithm can be implemented at a sampling rate up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{5}~Hz$</tex-math></inline-formula> with high-precision motion control.

Forward Kinematics Analysis of High-Precision Optoelectronic Packaging Platform

Abstract To meet the requirements of high-precision motion control for optoelectronic packaging platforms, we propose an improved particle swarm optimization (PSO) and backpropagation (IPSO-BP) neural network for solving the forward kinematics problem (FKP) of platforms. The focus of this paper is the 6-pss flexible parallel platform commonly used in optoelectronic packaging. First, a platform inverse kinematics problem (IKP) based on a flexibility matrix is solved using geometric and vector analysis. The conventional PSO-BP network is then optimized utilizing uniform design (UD), a random learning strategy, and space reduction techniques in FKP. Finally, simulations and experiments demonstrate that the proposed IPSO-BP network for solving the FKP on high-precision optoelectronic packaging platforms is feasible. Compared to BP and PSO-BP, this network has a higher resolution, faster convergence speed, and error control at the submicron level, which satisfies the motion control requirements of the platform at the micron level. This study lays a solid foundation for the production of high-quality devices in optoelectronic packaging.

Kinematic calibration and feedforward control of a heavy-load manipulator using parameters optimization by an ant colony algorithm

AbstractMost of the currently available three-degree-of-freedom manipulators are light load and cannot achieve full continuous rotation; given this, we designed a heavy-load manipulator that achieves unrestricted and continuous rotation. Due to manufacturing and assembly errors, parameter deviations between the real manipulator and its underlying theoretical model were unavoidable. Because of the lack of high-precision, high-frequency, and real-time closed-loop detection methods, we proposed a type of kinematics calibration of parameterized ant colony optimization and feedforward control methods. This was done to achieve high-precision motion control. First, an error model combining structural parameters and joint output angles was established, and the global sensitivity of each error source was analyzed to distinguish both primary and secondary sources. Based on the measured data of a laser tracker, the ant colony optimization was then used to identify six error sources. This resulted in both link length and joint driving errors of the designed manipulator. As it is a type of systematic error, the rounding error of the theoretical trajectory was carefully analyzed, and feedforward control methods with different coefficients were designed to further improve positioning accuracy based on the kinematic calibration. Experimental results showed that the proposed kinematic calibration and feedforward control methods achieved relatively precise motion control for the designed manipulator.

A double-iterative learning and cross-coupling control design for high-precision motion control

A double-iterative learning and cross-coupling control design for high-precision motion control

Iterative Learning Observer-Based High-Precision Motion Control for Repetitive Motion Tasks of Linear Motor-Driven Systems

Iterative Learning Observer-Based High-Precision Motion Control for Repetitive Motion Tasks of Linear Motor-Driven Systems

High-Precision and Modular Decomposition Control for Large Hydraulic Manipulators

It is difficult to achieve a high-precision motion control in hydraulic manipulators due to their structural redundancy, strong coupling of closed-chain structures, and flow–pressure coupling. In this paper, a high-precision motion control method for hydraulic manipulators is proposed based on the traditional virtual decomposition control (VDC). The method proposed avoids an excessive virtual decomposition of the hydraulic manipulator and requires fewer model parameters than the traditional VDC. Further, the control precision improved by combining an adaptive real-time update of the inertial parameters. Compared with MBC, the proposed control method improved the motion accuracy of the hydraulic manipulator by more than 40% and 20% under elliptical and triangular trajectories. The simulation results showed that the proposed control method reduced the maximum position errors in Cartesian space by 90.4%, 86.8%, 23.6%, and 44.3% compared with PID and model-based control (MBC) in the absence of disturbances. The maximum position error in Cartesian space was reduced by 76.5% compared with that of MBC in a simulation with external disturbances. It can be seen from all the simulation results that with the proposed control method, the position error of the manipulator was less than 50 mm. The proposed control method effectively improved the motion precision of the examined hydraulic manipulator.

Quantitative Measurement and Evaluation of High-Resolution Ultrasonic Sound Fields using a Novel Automated Ultrasonic Immersion Scanner

Ultrasonic probes are an integral part of the automated ultrasonic non-destructive inspection machines to detect and size the defects in a wide range of materials in production lines. A complete quantitative assessment of the performance characteristics of an application-specific ultrasonic probe is needed to be evaluated on the basis of the European Standard DIN EN ISO 22232-2. This requirement not only improves the quality assurance of the manufactured probes but also provides the useful technical data to the end-user to optimize the ultrasonic testing on-site. In addition, the evaluation of probe characteristics should be carried periodically throughout their service life. The main aim of this work is to develop and validate a novel ultrasonic immersion scanner for the quantitative measurement and evaluation of ultrasonic sound beam characteristics of an application-specific UT Probe. A novel ultrasonic immersion scanner integrated with high-precision motion control unit (Hexapod) with six axes is developed to measure the full ultrasonic probe characteristics, which include the squint angle measurement in three different planes (XY, XZ, and YZ), RF-signal and its frequency spectrum at watersteel interface and sound beam parameters including the angle of beam divergence in different directions. The automated scanning, data acquisition, evaluation, visualization and test report generation are performed based on DIN EN ISO 22232-2. The measured sound beam characteristics of both focused and non-focused applicationspecific ultrasonic probes with center frequencies ranging from 0.2 - 15 MHz using the pulse-echo technique on a 3 mm half-ball steel reflector are presented. The quantitative analysis of the measured sound field parameters and the acceptance criteria in accordance with DIN EN ISO 22232-2 are discussed. By using the newly developed automated immersion scanner, we achieved a few micrometer (~15 µm) spatial resolution in the measured sound field patterns and a good angular resolution (~0.05°) in the squint angle measurement of a wide range of UT probes.

Self-Organizing Interval Type-2 Fuzzy Neural Network Compensation Control Based on Real-Time Data Information Entropy and Its Application in n-DOF Manipulator.

In order to solve the high-precision motion control problem of the n-degree-of-freedom (n-DOF) manipulator driven by large amount of real-time data, a motion control algorithm based on self-organizing interval type-2 fuzzy neural network error compensation (SOT2-FNNEC) is proposed. The proposed control framework can effectively suppress various types of interference such as base jitter, signal interference, time delay, etc., during the movement of the manipulator. The fuzzy neural network structure and self-organization method are used to realize the online self-organization of fuzzy rules based on control data. The stability of the closed-loop control systems are proved by Lyapunov stability theory. Simulations show that the algorithm is superior to a self-organizing fuzzy error compensation network and conventional sliding mode variable structure control methods in control performance.

Nonlinear voltage error analysis and control of resonant high precision converter

The current nonlinear distortion of power converter can cause motion trajectory error and positioning error of motor, and affect the nano motion and positioning accuracy of ultra-precision system. The resonant pole-based dual buck soft-switching power converter (RPDBSPC) topology does not​ suffer current distortion caused by blanking time, and can support the high-frequency operation. It is suitable for the field of high dynamic and high-precision motion control. In order to realize the low nonlinear distortion current, the dual buck soft-switching topology should possess high linear output characteristics, and its nonlinear voltage error needs to be suppressed. This paper analyzes the operation principle of resonant power converter, and establishes its state space average model. Based on this, the nonlinear voltage error related resonant process of soft-switching topology is researched. Combined with the resonant equivalent circuit under unbalanced voltage sharing condition and the nonlinear characteristics of switching output capacitance, the expressions of nonlinear voltage error and zero voltage time are deduced, and a nonlinear voltage error suppression method based on zero voltage time control is proposed, which effectively reduces the current nonlinear distortion of resonant power converter.

Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery

The working environment of construction machinery is harsh, and some operations are highly repetitive. The realization of intelligent construction machinery helps to improve economic efficiency and promote industrial development. Construction machinery is different from ordinary passenger vehicles. Aiming at the fact that the existing environmental perception data set cannot be directly applied to construction machinery, this paper establishes the corresponding data set in combination with the specific working conditions of construction machinery and carries out training based on the PointPillars network to realize the environmental perception function applicable to the working conditions of construction machinery. Most construction machinery runs on unstructured roads, and the existing passenger vehicle path planning algorithm is not applicable to construction machinery. Based on this, this paper uses a hybrid A* algorithm to achieve path planning that meets the kinematics of construction machinery and realizes real-time obstacle detection and avoidance. At the same time, this paper combines environmental perception with a path planning algorithm to provide a method of autonomous path finding and obstacle avoidance for construction machinery. Based on the improved pure pursuit algorithm, the high-precision motion control and established trajectory tracking of construction machinery are realized, which lays a certain foundation for the follow-up research and development of related intelligent technologies of construction machinery.

Robot 3D spatial motion measurement via vision-based method

Measuring the motion of a robot accurately is an important and integral part of evaluating the dynamic and static performance of the robot. The performance index of a robot, such as kinematic accuracy, bearing capacity, deformation, vibration, stability, and structural mode can all be calculated according to the motion displacement of the robot. Therefore, improving the robot motion measurement method, promoting the measurement accuracy, and enriching the measurement content have received considerable scholarly attention worldwide. In this paper, an approach based on binocular vision was proposed to measure the 3D spatial motion of a robot. In the process of reconstructing robot movement, a mathematical model that can facilitate the solving process and improve the accuracy of results was derived to build 3D coordinates information. A novel coordinate transformation method that is based on the singular value decomposition was drawn up to realize the transformation from camera coordinates to robot coordinates. Several experiments were carried out on the self-built three-degree-of-freedom rectangular coordinate robot platform. The marker was designed specially and glued to the end of robot, and a new train of thought was adopted to extract the marker’s feature point. The vision-based measurement results were compared with the actual coordinate value. Results of experiments demonstrated that the proposed method can successfully reconstruct the 3D spatial motion of a robot more exactly, which can meet the requirements of high-precision motion control, motion performance evaluation, and operation state evaluation.

Nonlinear robust adaptive precision motion control of motor servo systems with unknown actuator backlash compensation

In this article, the problem of high precision motion control for motor servo systems with modeling uncertainties and unknown actuator backlash is addressed. The combination of synthesized adaptive laws and continuous nonlinear robust term handles parameter uncertainties and system disturbances. The adaptive technique updates the unknown parameters of actuator backlash in real time and the backlash inverse function eliminates the backlash effect. Meanwhile, the designed controller without knowing the range of the disturbance upper bound but automatically estimates through the adaptive law, which improves the engineering practicability. Finally, the theoretical analysis proves the perfect asymptotic stability of the presented controller even with unmodeled disturbances and unknown actuator backlash. Extensive comparative experiments reveal the superiority of the presented method.

A Novel Single-arm Single-port Micro-traumatic Laparoscopic Robotic Surgical System

As the robotic assisted single port surgery arousing attention, a novel single-arm single-port micro-traumatic laparoscopic robotic surgical system is proposed in this study. From the perspective of the mechanics, joints with high rigidity and high reliability were utilized to realize the remote center of motion (RCM). Besides, the cost of consumables was reduced by adding the support of the rigid endoscope. From the perspective of the algorithm, high-precision motion control method and feedback force protection mechanism were implemented. The effectiveness of the aforementioned characteristics were verified by five clinical experiments of cholecystectomy. The results showed that the system is able to reduce the amount of bleeding, accelerate the patient recovery, reduce the infection risk and shorten the learning period. The robotic surgical system had significant clinical application value.

Model-Free Output-Feedback Sliding-Mode Control Design for Piezo-Actuated Stage

Hysteresis in a piezoelectric actuator must be compensated for, and this compensation constitutes the main challenge in the high-precision motion control of piezo-actuated stages. This paper presents an output-feedback sliding-mode control (SMC) scheme to suppress unknown nonlinearity; in this scheme, hysteresis behavior is considered an external disturbance, and complex hysteresis models are thus not required. The scheme functions in the absence of transfer function of system state information, and a robust loop-transfer recovery observer is employed as a noise-free differentiator to estimate the required signal derivatives when the relevant system is in a noisy environment.

Fractional-order feedforward control method for permanent magnet linear synchronous motor based on frequency-domain adjustment theory

For a permanent magnet linear synchronous motor motion system, following error is one of the key indexes used when the motion system is applied to high-performance manufacturing equipment. Owing to the uncomplete description of the motion system’s control frequency-domain characteristics, the integer-order feedforward control method adapted for a two-degree-of-freedom feedforward-feedback control system may result in large-trajectory following error. To address this problem, this paper proposes a fractional-order feedforward control method with the frequency-domain characteristics adjustment ability. For the proposed method, this paper constructs an equal-order fractional-order compensator to compensate the frequency-domain errors of the integer-order feedforward control method. According to the features of the equal-order fractional-order compensator, this paper decomposes the compensator into multiple independent units, clarifies the relationship between parameter selection and frequency-domain characteristics, and establishes an optimal solution formula for phase error minimization. Through compensator decomposition and optimal parameter determination, the proposed fractional-order feedforward control method can accurately describe the control frequency-domain characteristics of the motion system. The simulation experiment results show that the proposed method can effectively reduce the gain and phase errors. The physical experiments were conducted on a motion system constructed by permanent magnet linear synchronous motors. And the experiment results are presented herein to validate the effectiveness and advancements of the proposed method in high-precision motion control for the permanent magnet linear synchronous motor motion system.

Optimal design of Udwadia–Kalaba theory-based adaptive robust control for permanent magnet linear synchronous motor

The control performance of permanent magnet linear synchronous motor (PMLSM) is limited by uncertainty. The uncertainty is bounded by an unknown bound and may be time-varying. The boundary information of uncertainty is unknown but can be described by fuzzy set theory. To mitigate the impact of uncertainty on control performance, this paper proposes a Udwadia–Kalaba theory-based adaptive robust control (UKBARC). The proposed controller contains a Udwadia–Kalaba theory-based controller and an adaptive robust controller. In the Udwadia–Kalaba theory-based controller, the expected trajectory is taken as the expected constraint, and then the control task is converted to make the expected constraint be followed. Additionally, the adaptive robust controller is introduced to handle the system uncertainty without requiring the boundary information of uncertainty. The Lyapunov method is used to show that the performance of uniform boundedness (UB) and uniform ultimate boundedness (UUB) for the PMLSM system is guaranteed. The objective function used to characterize the trade-off between performance and control cost can be derived based on the fuzzy description of uncertainty. Thus, the optimal design of UKBARC (OUKBARC) can be achieved by minimizing the objective function. Simulation and experiment results together verify that high precision motion control can be ensured by using the proposed approach.