Closed-loop Motion Control Research Articles

Variational analysis of sensory feedback mechanisms in powerstroke-recovery systems.

Although the raison d'etre of the brain is the survival of the body, there are relatively few theoretical studies of closed-loop rhythmic motor control systems. In this paper we provide a unified framework, based on variational analysis, for investigating the dual goals of performance and robustness in powerstroke-recovery systems. To demonstrate our variational method, we augment two previously published closed-loop motor control models by equipping each model with a performance measure based on the rate of progress of the system relative to a spatially extended external substrate-such as a long strip of seaweed for a feeding task, or progress relative to the ground for a locomotor task. The sensitivity measure quantifies the ability of the system to maintain performance in response to external perturbations, such as an applied load. Motivated by a search for optimal design principles for feedback control achieving the complementary requirements of efficiency and robustness, we discuss the performance-sensitivity patterns of the systems featuring different sensory feedback architectures. In a paradigmatic half-center oscillator-motor system, we observe that the excitation-inhibition property of feedback mechanisms determines the sensitivity pattern while the activation-inactivation property determines the performance pattern. Moreover, we show that the nonlinearity of the sigmoid activation of feedback signals allows the existence of optimal combinations of performance and sensitivity. In a detailed hindlimb locomotor system, we find that a force-dependent feedback can simultaneously optimize both performance and robustness, while length-dependent feedback variations result in significant performance-versus-sensitivity tradeoffs. Thus, this work provides an analytical framework for studying feedback control of oscillations in nonlinear dynamical systems, leading to several insights that have the potential to inform the design of control or rehabilitation systems.

Research on underwater motion modeling and closed-loop control of bionic undulating fin robot

Aiming at the problems of unclear underwater motion characteristics and poor robustness of bionic undulating fin robots, the underwater motion characteristics of the robot are studied by force analysis and numerical simulation, and the dynamic model is established. Based on the dynamic model, the proportional-integral-derivative controller (PID) and neural network PID simulation model are established for numerical simulation, and the robot's underwater closed-loop motion control experiment is carried out. The accuracy of the dynamic model and the consistency between the numerical simulation and the experimental results can be verified. The results indicate that under the function of the neural network PID controller, the robot can be closer to the target depth, and the fluctuation range could be smaller. As the above characteristics improve, the control accuracy and stability of the robot could also be enhanced.

Low order speed harmonic suppression in FOC-PMSM based on the closed-loop transfer mechanism of injected voltage

In the field oriented control (FOC) permanent magnet synchronous motor (PMSM) servo system, torque ripple impairs motor performance. Harmonic injection methods can suppress torque ripple by injecting additional voltage harmonic to offset the existing speed harmonic. However, since FOC is a closed-loop motion control strategy, the transfer path from injected voltage harmonic to speed harmonic is affected by FOC, especially in very low frequency. Due to the influence of FOC on the transfer function, the relation between the injected voltage harmonic and speed harmonic varies with operating conditions and motor control parameters. It causes the existing harmonic injection methods ineffective to suppress low order speed harmonics. To solve the problem, in this paper, the closed-loop transfer mechanism of injected voltage harmonics is analyzed and the closed-loop transfer function is derived. Based on the derived closed-loop transfer function, a low order speed harmonic suppression method is proposed. With the derived transfer function, the proposed method can adapt to the variations of the relation between low order injected voltage harmonic and speed harmonic under different operation conditions. Finally, the accuracy of the derived closed-loop transfer function and the effectiveness of the proposed low order speed harmonic suppression method are evaluated by experiment.

Enhancement of EEG–EMG coupling detection using corticomuscular coherence with spatial–temporal optimization

Objective. Corticomuscular coherence (CMC) is widely used to detect and quantify the coupling between motor cortex and effector muscles. It is promisingly used in human–machine interaction (HMI) supported rehabilitation training to promote the closed-loop motor control for stroke patients. However, suffering from weak coherence features and low accuracy in contingent neurofeedback, its application to HMI rehabilitation robots is currently limited. In this paper, we propose the concept of spatial–temporal CMC (STCMC), which is the coherence by refining CMC with delay compensation and spatial optimization. Approach. The proposed STCMC method measures the coherence between electroencephalogram (EEG) and electromyogram (EMG) in the multivariate spaces. Specifically, we combined delay compensation and spatial optimization to maximize the absolute value of the coherence. Then, we tested the reliability and effectiveness of STCMC on neurophysiological data of force tracking tasks. Main results. Compared with CMC, STCMC not only enhanced the coherence significantly between brain and muscle signals, but also produced higher classification accuracy. Further analysis showed that temporal and spatial parameters estimated by the STCMC reflected more detailed brain topographical patterns, which emphasized the different roles between the contralateral and ipsilateral hemisphere. Significance. This study integrates delay compensation and spatial optimization to give a new perspective for corticomuscular coupling analysis. It is also feasible to design robotic neurorehabilitation paradigms by the proposed method.

Design of Double Closed Loop Control System for DC Motor Based on TX8C1010 Single Chip

In order to improve the operational strength and control precision of the DC motor, a double closed-loop control system based on TAIXIN TX8C1010 MCU is proposed. The single chip is based on a high-speed 8051 core, which is applied to home appliances and can realize the double closed-loop motor control algorithm. The given speed value provided by the potentiometer is compared with the real-time speed value and inputs the error to the speed loop function, which is based on the incremental PID algorithm, to calculate the reference current value. Then it is compared with the real-time current value and inputs the error into the current loop. The PWM signal duty cycle is determined by the output value of the current loop to adjust and stabilize the motor speed. The drive circuit outputs the PWM signal in the inverse amplification way to control the operation of the DC motor, and finally tests the function on the MAGTROL M-TEST7 motor test platform. The test results show that the control system has fast response speed, strong load capacity, good robustness and safety. Hence, TAIXIN TX8C1010 single-chip machine is feasible in the DC motor control. It can be improved to strengthen its load characteristics according to the parameters and applied to a variety of power DC motor control.

Closed-Loop Motion Control of Robotic Swarms – A Tether-Based Strategy

Swarm robots can achieve effective task execution via closed-loop motion control. However, such a goal can only be realized through accurate localization of the swarm. Past approaches have focused on addressing this issue using external sensors, static sensor networks, or through active localization—requirements that may restrict the motion of the swarm or may not be achievable in practice. We present a tether-based strategy that achieves closed-loop swarm-motion control by using a secondary team of mobile sensors. These sensors form a wireless tether that allows the swarm to indirectly sense a home base or a landmark, and to compensate for the accumulated motion errors via a closed-loop control strategy. The proposed strategy is the first to use a tether of mobile sensors that can dynamically reshape and reconnect to various points in the environment to achieve closed-loop motion control. The novelty of the strategy is in its ability to adapt to any swarm motion considered, and to be applied to swarms with limited sensing capabilities and knowledge of their environment. The performance of the proposed strategy was validated through extensive experiments.

Online Deflection Compensation of a Flexible Hydraulic Loader Crane Using Neural Networks and Pressure Feedback

The deflection compensation of a hydraulically actuated loader crane is presented. Measurement data from the laboratory are used to design a neural network deflection estimator. Kinematic expressions are derived and used with the deflection estimator in a feedforward topology to compensate for the static deflection. A dynamic deflection compensator is implemented, using pressure feedback and an adaptive bandpass filter. Simulations are conducted to verify the performance of the control system. Experimental results showcase the effectiveness of both the static and dynamic deflection compensator while running closed-loop motion control, with a 90% decrease in static deflection.

A calibration method for rotary optical encoder temperature error in a rotational inertial navigation system

A rotary optical encoder is an important component in a rotational inertial navigation system (RINS). It is used to form a closed-loop motor control system and calculate the system attitude. The system performance will be affected by the encoder’s error. Ín addition to the installation errors, the working temperature variants can lead to encoder error. Therefore, in this paper we propose a method to calibrate and compensate the temperature errors of rotary optical encoders. First, an independent testing mechanism with position limitation and a rotatable platform is designed and produced to verify the temperature influence on encoders. Then, the temperature error of the rotary optical encoder used in RINS is calculated by a gyroscope whose sensitive axis is parallel to the same motor axis. The method is verified by a self-researched single-axis RINS. According to the experimental results, the measurement accuracy is increased by more than 47.9% compared to the traditional method.

A Design of FPGA-Based Neural Network PID Controller for Motion Control System.

In the actual industrial production process, the method of adaptively tuning proportional–integral–derivative (PID) parameters online by neural network can adapt to different characteristics of different controlled objects better than the controller with PID. However, the commonly used microcontroller unit (MCU) cannot meet the application scenarios of real time and high reliability. Therefore, in this paper, a closed-loop motion control system based on BP neural network (BPNN) PID controller by using a Xilinx field programmable gate array (FPGA) solution is proposed. In the design of the controller, it is divided into several sub-modules according to the modular design idea. The forward propagation module is used to complete the forward propagation operation from the input layer to the output layer. The PID module implements the mapping of PID arithmetic to register transfer level (RTL) and is responsible for completing the output of control amount. The main state machine module generates enable signals that control the sequential execution of each sub-module. The error backpropagation and weight update module completes the update of the weights of each layer of the network. The peripheral modules of the control system are divided into two main parts. The speed measurement module completes the acquisition of the output pulse signal of the encoder and the measurement of the motor speed. The pulse width modulation (PWM) signal generation module generates PWM waves with different duty cycles to control the rotation speed of the motor. A co-simulation of Modelsim and Simulink is used to simulate and verify the system, and a test analysis is also performed on the development platform. The results show that the proposed system can realize the self-tuning of PID control parameters, and also has the characteristics of reliable performance, high real-time performance, and strong anti-interference. Compared with MCU, the convergence speed is far more than three orders of magnitude, which proves its superiority.

Online Iterative Learning Compensation Method Based on Model Prediction for Trajectory Tracking Control Systems

In this article, to guarantee the good tracking performance of the precision motion system for various tracking tasks, an online iterative learning compensation method is proposed for closed-loop motion control systems. The prediction model is based on the closed-loop model of the linear second-order system with a proportional-integral-derivative controller, and an estimation term is added to deal with the influence of slow-varying uncertain disturbances. On the basis of the accurate state prediction, the dynamical feedforward compensation can be obtained, which suppresses the tracking error caused by the dynamical lag. Furthermore, in order to simultaneously compensate the errors caused by nonlinear factors such as uncertain disturbances and to guarantee the smoothness of the compensated trajectory, the optimal compensation gain is determined through online iterative calculation. The online iterative approach is similar to iterative learning control, but does not require several offline iterations of a repeating trajectory. Comparative experiments are carried out on an industrial motion stage. Various experimental results consistently demonstrate that the proposed compensation scheme can achieve the tracking accuracy comparable to iterative learning, while maintaining the robustness to trajectory changes and uncertain disturbances without reoffline iteration.

Synchronization Control of a Dual-Cylinder Lifting Gantry of Segment Erector in Shield Tunneling Machine under Unbalance Loads

Segment assembling is one of the principle processes during tunnel construction using shield tunneling machines. The segment erector is a robotic manipulator powered by a hydraulic system to assemble prefabricated concrete segments onto the excavated tunnel surface. Nowadays, automation of the segment erector has become one of the definite developing trends to further improve the efficiency and safety during construction; thus, closed-loop motion control is an essential technology. Within the segment erector, the lifting gantry is driven by dual cylinders to lift heavy segments in the radial direction. Different from the dual-cylinder mechanism used in other machines such as forklifts, the lifting gantry usually works at an inclined angle, leading to unbalanced loads on the two sides. Although strong guide rails are applied to ensure synchronization, the gantry still occasionally suffers from chattering, “pull-and-drag”, or even being stuck in practice. Therefore, precise motion tracking control as well as high-level synchronization of the dual cylinders have become essential for the lifting gantry. In this study, a complete dynamics model of the dual-cylinder lifting gantry is constructed, considering the linear motion as well as the additional rotational motion of the crossbeam, which reveals the essence of poor synchronization. Then, a two-level synchronization control scheme is synthesized. The thrust allocation is designed to coordinate the dual cylinders and keep the rotational angle of the crossbeam within a small range. The motion tracking controller is designed based on the adaptive robust control theory to guarantee the linear motion tracking precision. The theoretical performance is analyzed with corresponding proof. Finally, comparative simulations are conducted and the results show that the proposed scheme achieves high-precision motion tracking performance and simultaneous high-level synchronization of dual cylinders under unbalanced loads.

Pose and shape error control in automated machining of fastener holes for composite/metal wing-box assembly

Composite/metal wing-boxes are hard to drill by the conventional drilling method. In this paper, an automated machine-tool-based machining system equipped with a multifunctional end-effector is developed for helical milling, as well as circular and ellipsoidal dimple drilling of composite/metal wing-boxes. The system constitution, the control system, and the application software of the machining system are demonstrated. In aircraft manufacturing, the out-of-tolerance pose and shape of fastener holes deteriorate an aircraft’s strength and fatigue performances. Thus, a multi-sensor information fusion and integration architecture is built for enhanced pose and shape accuracy of machined fastener holes. The relative pose error of the end-effector and an aerostructure is analyzed. A coarse-to-fine control method by the touch probe and LDSs is applied for controlling the error. The fastener holes’ shape errors are controlled through the elaborate structure design and multi-sensor-based closed-loop motion control of the end-effector. Experiments performed on the machining system show that the positioning errors, hole diameter errors, dimple depth errors, and ellipsoidal dimple shape can fulfill the wing-box assembly requirements.

Design and Locomotion Control of a Dactylopteridae-Inspired Biomimetic Underwater Vehicle With Hybrid Propulsion

This article presents the design and implementation of an innovative biomimetic underwater vehicle (BUV) and its locomotion controller. Through mimicking a dactylopteridae, the hybrid propulsion BUV is designed with two symmetrical bio-inspired long-fins and a double-joint fishtail. The mechatronic design of the dactylopteridae-inspired BUV with the pectoral long-fins and a double-joint fishtail is first provided. The two flexible long-fins compose the median and/or paired fin (MPF) propulsion, while the fishtail acts as the body and/or caudal fin (BCF) propulsion. Through the coordination of BCF and MPF propulsion modes, the BUV obtains excellent low-speed locomotion stability and also keeps high maneuverability. Moreover, the locomotion control methods based on central pattern generators (CPGs) model and fuzzy adaptive proportion integral differential (PID) are proposed for this BUV. In the end, the experimental results of the multimode motion and closed-loop motion control demonstrate the feasibility and effectiveness of the mechanism and the locomotion control system. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation behind this article is the design of a novel biomimetic underwater vehicle (BUV) that possesses low-speed locomotion stability and fast swimming ability, which is suitable for carrying relevant sensors to complete water quality monitoring, biological observation, underwater equipment inspection, underwater structure detection, and other marine tasks. Currently, BUVs are usually designed as only one propulsion mode by caudal fin or paired fins, which makes it difficult to have the advantages of both modes. In order to further study the problem, we designed a dactylopteridae-inspired BUV with the bilateral pectoral long-fins (providing low-speed locomotion stability) and a double-joint fishtail (providing fast swimming ability). A hybrid-driven motion control framework is presented for the BUV based on a central pattern generators (CPGs) model and fuzzy adaptive proportion integral differential (PID). A series of experiments suggests that the mechanism and the locomotion control system are practical and valid. Hopefully, our mechanism and control framework can provide valuable theoretical and technical support guidance to the practicing marine engineer for the codesign of propulsion mode and control.

Distributed Actuation and Control of a Morphing Tensegrity Structure

Abstract Structures and actuation systems need to be closely integrated together in the future to create faster, more efficient, lightweight dynamic machines. Such actuated structures would be used for morphing aircraft wings, lightweight actuated space structures, or in robotics. This approach requires actuators to be distributed through the structure. A tensegrity structure is a very promising candidate for this future integration due to its potentially excellent stiffness and strength-to-weight ratio, and the inherent advantage of being a multi-element structure into which actuators can be embedded. This paper presents methods for analysis of the structure geometry, for closed-loop motion control, and includes experimental results for a structure actuated by lightweight pneumatic muscles. In a practical morphing tensegrity structure, it cannot be assumed that tension and compression members always meet at a point. Thus, a form-finding method has been developed to find stable geometries and determine stiffness properties for tensegrity structures with nodes of finite dimension. An antagonistic multi-axis control scheme has been developed for the shape position and motion control. In the experimental actuated tensegrity system presented the pneumatic muscles are controlled by on-off valves, for which a dead-band switching controller is designed based on a new stability criterion. The experimental system demonstrates accurate control of shape change while maintaining a desired level of internal preload in a stiff structure, showing considerable promise for future lightweight dynamic machines.

MROBerTO 2.0 – An Autonomous Millirobot With Enhanced Locomotion for Swarm Robotics

Numerous millirobots were developed in the past decade for autonomous swarm systems that aim to utilize large numbers of these units in space-constrained environments. However, the size limitation of these robots has often resulted in their reduced computational, sensing, and locomotion capabilities. mROBerTO (milli-ROBot-TOronto) was developed in response to such limitations. Despite its enhanced features, the reliable and repeatable locomotion of mROBerTO has still been of some concern due to lack of effective closed-loop motion control – as is the case with all other similar millirobots. In this letter, we present the next version of mROBerTO with a new locomotion mechanism that utilizes stepper motors, capable of micro-stepping down to 1/32 of a full step, to yield a millirobot with maneuvering capabilities superior to current similar-sized robots. mROBerTO 2.0 is novel in that it utilizes these stepper motors without relying on a separate processor for controlling them. This letter also presents a complementary new algorithm for efficiently converting desired trajectories into robot-motion commands. The proposed algorithm was developed to allow millirobots to execute complex trajectories reliably in an open-loop manner.

Visual sensing based ultra-high precision motion control with compensated mechanical drift across different stages

Ultrahigh precision motion control across different stages in a multistage system plays a central role in many micro/nanoscale applications. However, it remains a challenge due to the mechanical drift. Here, we propose a visual sensing based approach to implement the cooperative motion control in a multistage platform. In this method, microsized beads are attached to individual stages and taken as visual sensing probes. By tracking the motion of visual sensing probes, the positions of individual stages are measured. The principle of the proposed method is presented, followed by the experimental demonstration of the real-time mechanical drift compensation and high-precision cooperative motion control in a home-made dual piezoelectric flexural stage platform. With the proposed method, ultrahigh precision motion control between the two stages are achieved in a 3-D manner, with closed-loop motion control resolution of 1.5, 1.3, and 4.2 nm for X , Y , and Z axes, respectively. The proposed method provides an effective approach for ultrahigh precision motion control across different stages, which is believed to be significant for nanoscale manipulation related applications.

Design of an isokinetic knee dynamometer for evaluation of functional electrical stimulation strategies

BackgroundThe limitations of functional electrical stimulation (FES) cycling directly affect the health benefits acquired from this technology and prevents its’ full potential to be realised. Experiments should be done on a test bed which can isolate and focus only on one muscle group, namely the quadriceps. The aim of this work was to design and develop an isokinetic robotic leg extension/flexion dynamometer which can mimic knee joint motion during actual cycling to be used for evaluation of novel functional electrical stimulation strategies. Although the main motivation for development of the dynamometer was for application in FES studies, it has the potential to be used for various different muscle physiology studies. MethodsA feedback control system with integrated electrical stimulation for isokinetic knee joint torque measurement has been developed and tested for safety and functionality. The leg extension/flexion device was modified and equipped with a DC motor drive system to imitate isokinetic knee joint motion during cycling when the hip joint remains fixed. Real-time bi-directional effective torque on the lever arm was measured by a magnetostrictive torque sensor and a load cell. Closed-loop motor control system was also designed to mimic the cyclical motion at desired angular velocity. ResultsA functional model of the robotic dynamometer was developed and evaluated. The dynamometer is capable of simulating the knee angle during cycling at a cadence of up to 70 rpm with range of motion of 72∘. The magnetostrictive torque sensor can measure torque values up to 75 Nm. The lever arm can be adjusted and the target knee angle was controlled with RMSE tracking error of less than 2.1∘ in tests with and without a test person, and with and without muscle stimulation. ConclusionsThe isokinetic knee joint torque measurement system was designed and validated in this work, and subsequently used to develop and evaluate novel muscle activation strategies. This is important for fundamental research on effective stimulation patterns and novel activation strategies. This will, in turn, enhance the efficiency of FES cycling exercise and has the potential to improve the health-beneficial effects.

A Contactless and Biocompatible Approach for 3D Active Microrobotic Targeted Drug Delivery.

As robotic tools are becoming a fundamental part of present day surgical interventions, microrobotic surgery is steadily approaching clinically-relevant scenarios. In particular, minimally invasive microrobotic targeted drug deliveries are reaching the grasp of the current state-of-the-art technology. However, clinically-relevant issues, such as lack of biocompatibility and dexterity, complicate the clinical application of the results obtained in controlled environments. Consequently, in this work we present a proof-of-concept fully contactless and biocompatible approach for active targeted delivery of a drug-model. In order to achieve full biocompatiblity and contacless actuation, magnetic fields are used for motion control, ultrasound is used for imaging, and induction heating is used for active drug-model release. The presented system is validated in a three-dimensional phantom of human vessels, performing ten trials that mimic targeted drug delivery using a drug-coated microrobot. The system is capable of closed-loop motion control with average velocity and positioning error of 0.3 mm/s and 0.4 mm, respectively. Overall, our findings suggest that the presented approach could augment the current capabilities of microrobotic tools, helping the development of clinically-relevant approaches for active in-vivo targeted drug delivery.

External Force Self-Sensing Based on Cable-Tension Disturbance Observer for Surgical Robot End-Effector

The external force sensing ability of the end-effector plays a significant role in restricting the refine operation of a surgical robot. This paper proposes an external force self-sensing method based on the cable-tension disturbance observer for a four-degree-of-freedom (4-DoF) surgical robot end-effector, which is actuated by three backdrivable cable-driven series elastic actuators (BCDSEAs). First, the design of the surgical robot end-effector is introduced with the experimental prototype of a 1-DoF flexible finger joint. Second, four kinds of dynamic models of the flexible finger joint are established and experimentally identified. A joint angle estimator is proposed based on a simplified dynamic model. Then, a closed-loop motion control method for the flexible finger joint is proposed. Third, a driving cable-tension estimator is constructed as the benchmark for the cable-tension disturbance observer under free motion. Meanwhile, an external force self-sensing estimator is proposed based on the motion control strategy and the cable-tension disturbance observer. Finally, the experimental results of joint tracking control present a good performance. The compensation algorithm for the external force under free motion is studied to reduce the system error. The experimental results of the external force self-sensing show an overall estimation accuracy of 85.97% with a range of 0.10–2.00 N.

Magnetic localization and control of helical robots for clearing superficial blood clots.

This work presents an approach for the localization and control of helical robots during removal of superficial blood clots inside in vitro and ex vivo models. The position of the helical robot is estimated using an array of Hall-effect sensors and precalculated magnetic field map of two synchronized rotating dipole fields. The estimated position is used to implement closed-loop motion control of the helical robot using the rotating dipole fields. We validate the localization accuracy by visual feedback and feature tracking inside the in vitro model. The experimental results show that the magnetic localization of a helical robot with diameter of 1 mm can achieve a mean absolute position error of 2.35 ± 0.4 mm (n = 20). The simultaneous localization and motion control of the helical robot enables propulsion toward a blood clot and clearing at an average removal rate of 0.67 ± 0.47 mm3/min. This method is used to localize the helical robot inside a rabbit aorta (ex vivo model), and the localization accuracy is validated using ultrasound feedback with a mean absolute position error of 2.6 mm.