Impedance Control Research Articles

Human‐centered active torque‐based AAN impedance control for lower limb patient‐exoskeleton coupling system in the rehabilitation

AbstractThis article presents a human‐centered active torque‐based assist‐as‐needed (ATAAN) impedance control for lower limb patient‐exoskeleton coupling system (LLPECS), which considers the coupling effects (e.g., elastic connections, human soft tissues). The proposed double loop structure controller is composed of the establishment of the ATAAN impedance model in the outer‐loop and an adaptive interaction torque‐based controller in the inner‐loop. In the outer‐loop, the patient's muscle torque is estimated by a nonlinear disturbance observer, and the estimated result is used to approximate the patient's active torque. The parameters of ATAAN impedance model are modulated according to the approximation of active torque and the patient's position error to achieve the assist‐as‐needed property. In the inner‐loop, the desired interaction torque, which is required to realize the target ATAAN impedance model, is designed by a robust computed torque controller. The desired trajectory of the exoskeleton is planned online according to the desired interaction torque with the dynamics model of coupling effects. The prescribed performance controller is utilized to achieve accurate trajectory tracking of the exoskeleton, which further enables the interaction torque to track the desired value. The stability of the system and realization of the target ATAAN impedance model are rigorously proved by the Lyapunov method. Co‐simulation experiments are conducted to demonstrate the superiority of the proposed method compared with other existing controllers and its robustness against modeling uncertainties. The effectiveness of the proposed method has been verified through experiments in rehabilitation scenarios.

Generating synthetic gait patterns based on benchmark datasets for controlling prosthetic legs

BackgroundProsthetic legs help individuals with an amputation regain locomotion. Recently, deep neural network (DNN)-based control methods, which take advantage of the end-to-end learning capability of the network, have been proposed. One prominent challenge for these learning-based approaches is obtaining data for the training, particularly for the training of a mid-level controller. In this study, we propose a method for generating synthetic gait patterns (vertical load and lower limb joint angles) using a generative adversarial network (GAN). This approach enables a mid-level controller to execute ambulation modes that are not included in the training datasets.MethodsThe conditional GAN is trained on benchmark datasets that contain the gait data of individuals without amputation; synthetic gait patterns are generated from the user input. Further, a DNN-based controller for the generation of impedance parameters is trained using the synthetic gait pattern and the corresponding synthetic stiffness and damping coefficients.ResultsThe trained GAN generated synthetic gait patterns with a coefficient of determination of 0.97 and a structural similarity index of 0.94 relative to benchmark data that were not included in the training datasets. We trained a DNN-based controller using the GAN-generated synthetic gait patterns for level-ground walking, standing-to-sitting motion, and sitting-to-standing motion. Four individuals without amputation participated in bypass testing and demonstrated the ambulation modes. The model successfully generated control parameters for the knee and ankle based on thigh angle and vertical load.ConclusionsThis study demonstrates that synthetic gait patterns can be used to train DNN models for impedance control. We believe a conditional GAN trained on benchmark datasets can provide reliable gait data for ambulation modes that are not included in its training datasets. Thus, designing gait data using a conditional GAN could facilitate the efficient and effective training of controllers for prosthetic legs.

Design, Control, and Validation of a Polycentric Hybrid Knee Prosthesis

This paper presents a novel polycentric hybrid knee prosthesis (PHKP) by enabling a multi-bar linkage to work for high-torque activities in active mode and for low-torque activities in passive mode. The mode transition is implemented by a servo-controlled telescopic slide rails. Distinguished from the single-axis hybrid knee prostheses, the PHKP Knee provides geometric stability in stance and notably increases toe clearance in swing by using an optimally designed instantaneous center of rotation (ICR) trajectory. In active mode, the PHKP Knee provides high transmission ratio and continuous peak torque offering sufficient support for torque-demanding activities. Impedance control was employed to regulate joint torque as a response to knee motion in the active mode. It was found that due to the inherent geometric stability of the polycentric mechanism in stance, the damping coefficient of the controller can be tuned much smoother than the single-axis knees leading to more compliant and comfortable interactions among the wearer, the prosthesis and the ground. The stair ascent tests showed that the joint angle and torque profiles of the PHKP Knee are similar to those of the able-bodied by demonstrating a step-over-step pattern with a peak angle of 73 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\deg$</tex-math></inline-formula> and a maximum torque of 0.92 Nm/Kg.

Condition-based Design of Variable Impedance Controllers from User Demonstrations

This paper presents an approach to ensure conditions on Variable Impedance Controllers through the off-line tuning of the parameters involved in its description. In particular, we prove its application to term modulations defined by a Learning from Demonstration technique. This is performed through the assessment of conditions regarding safety and performance, which encompass heuristics and constraints in the form of Linear Matrix Inequalities. Latter ones allow to define a convex optimisation problem to analyse their fulfilment, and require a polytopic description of the VIC, in this case, obtained from its formulation as a discrete-time Linear Parameter Varying system. With respect to the current state-of-art, this approach only limits the term definition obtained by the Learning from Demonstration technique to be continuous and function of exogenous signals, i.e. external variables to the robot. Therefore, using a solution-search method, the most suitable set of parameters according to assessment criteria can be obtained. Using a 7-DoF KinovaGen3 manipulator, validation and comparison against solutions with relaxed conditions are performed. The method is applied to generate Variable Impedance Controllers for a pulley belt looping task, inspired by the Assembly Challenge for Industrial Robotics in World Robot Summit 2018, to reduce the exerted force with respect to a standard (constant) Impedance Controller. These controllers fulfil a set of safety constraints, namely stability, bounds on task variables and maximum response overshooting; and their performance is determined by the User Preference heuristic, which allows to intuitively define the desired compliant behaviour along the task. In the context of the task, this is used to generate new controllers for one-off modifications of the nominal belt looping task setup without new demonstrations.

Robot-Assisted Gravity Offloading Testing of Aerospace Structures

Abstract The demand for testing aerospace structures on Earth before they are launched into space has led to the development of equipment that is able to simulate orbit conditions, namely zero gravity. Several passive solutions have been proposed to perform offloading testing on Earth. However, they present limitations and lack the flexibility normally required by the complexity of the pathways. Active zero gravity emulation systems have been developed to mitigate the difficulties of the passive ones. Moreover, the emergence of robotic arms with the ability to perform complex and easily reprogrammable motion and force-controlled trajectories has opened the possibility of creating robot-based gravity compensation systems. This paper proposes and evaluates a solution for the gravity offloading testing of space devices based on currently available industrial robots. This solution takes advantage of the functionalities of collaborative robots, namely built-in force controllers, together with custom auxiliary subsystems. A setup was arranged to allow the communication between the robot controller and a computer running an internet of things (IoT) platform based on Node-RED so as to connect and control all components of the offloading system. Multiple robot control techniques were designed and tested based on several approaches employing impedance control functionalities and sensing data to create a closed-loop system. The results obtained are within the validation criteria, creating conditions to affirm for the application in question that the gravity compensation was achieved with success using the robot.

Human muscle fatigue monitoring method and its application for exoskeleton interactive control

Aiming at the human-computer interaction problem during the movement of the rehabilitation exoskeleton robot, this paper proposes an adaptive human-computer interaction control method based on real-time monitoring of human muscle state. Considering the efficiency of patient health monitoring and rehabilitation training, a new fatigue assessment algorithm was proposed. The method fully combined the human neuromuscular model, and used the relationship between the model parameter changes and the muscle state to achieve the classification of muscle fatigue state on the premise of ensuring the accuracy of the fatigue trend. In order to ensure the safety of human-computer interaction, a variable impedance control algorithm with this algorithm as the supervision link was proposed. On the basis of not adding redundant sensors, the evaluation algorithm was used as the perceptual decision-making link of the control system to monitor the muscle state in real time and carry out the robot control of fault-tolerant mechanism decision-making, so as to achieve the purpose of improving wearing comfort and improving the efficiency of rehabilitation training. Experiments show that the proposed human-computer interaction control method is effective and universal, and has broad application prospects.

Force Control of a Grinding Robotic Manipulator With Floating Base Via Model Prediction Optimization Control

In this article, a grinding robot for large area and an impedance-based force control method applied to the robot are described. With the development of science and technology, the demand for various industrial robots increased, and among them, the demand and importance of grinding robots that require high risk and precision increased. In particular, research on grinding robots targeting large areas has not been conducted relatively, and accordingly, the design and control mechanism of robots specialized in large areas was needed. A robot consisting of a manipulator and a grinding module with a 2-DOF parallel structure is proposed as the design of a new grinding robot. The control method is based on impedance force control mainly used in existing grinding robots, but to overcome the limitations of using only impedance control, the impedance control via model-based prediction optimization (MPO) is proposed as a control technique for grinding robots. Experiments were conducted to verify the force tracking ability of the proposed control, resulting in a 28.1% improvement in settling time for the desired force. Even for disturbance, more improved recovery performance than conventional controllers has been verified. As a result, proposed impedance force control via MPO shows improved force tracking performance over conventional impedance control, and is presented as one of the appropriate control methods for grinding robots targeting large areas.

SSK: Robotic Pen-Art System for Large, Nonplanar Canvas

We present a semiautonomous robotic pen-drawing system, called SSK, that is capable of creating pen art on a large nonplanar surface. Our robotic system relies on a seven-degree-of-freedom impedance-controlled manipulator with a three-degree-of-freedom holonomic mobile platform. We use a vector-graphics engine to take an artist's pen drawing as input, and we generate Bézier spline curves to be drawn on the given target drawing canvas. Then, our system finds a set of minimal, discrete configurations for the mobile platform to cover the entire canvas surface while considering the reachability of the manipulator. The drawing is split into multiple subdrawings according to the found configurations. Our system replicates the spline drawing on the target surface using impedance control, which enables us to compensate for the uncertainty and incompleteness inherent to canvas-surface representations and various robotic and sensor noises. We demonstrate that our system can create visually pleasing and complicated pen art on large, nonplanar surfaces.

Adaptive Fuzzy Neural Network Command Filtered Impedance Control of Constrained Robotic Manipulators With Disturbance Observer.

This article proposes an adaptive fuzzy neural network (NN) command filtered impedance control for constrained robotic manipulators with disturbance observers. First, barrier Lyapunov functions are introduced to handle the full-state constraints. Second, the adaptive fuzzy NN is introduced to handle the unknown system dynamics and a disturbance observer is designed to eliminate the effect of unknown bound disturbance. Then, a modified auxiliary system is designed to suppress the input saturation effect. In addition, the command filtered technique and error compensation mechanism are used to directly obtain the derivative of the virtual control law and improve the control accuracy. The barrier Lyapunov theory is used to prove that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. Finally, simulation studies are performed to illustrate the effectiveness of the proposed control method.

Adaptive impedance control for the hydraulic manipulator under the uncertain environment

Adaptive impedance control for the hydraulic manipulator under the uncertain environment

Decoupled Mitigation Control of Series Resonance and Harmonic Load Current for HAPFs With a Modified Two-Step Virtual Impedance Shaping

Hybrid active power filter (HAPF) with large series capacitor can reduce the rating of power converter, but it is associated with the risk of low frequency <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> resonance. The overlapping of series <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LC</i> resonance frequencies and the dominated load harmonic current frequencies makes the conventional active damping approaches less effective. To overcome this challenge, a two-step harmonic virtual impedance control approach is developed to compensate the load harmonic current and reshape the closed-loop equivalent circuit of the HAPF for resonance damping. First, the shunt capacitor harmonic voltage is regulated according to a term that is associated with both the harmonic load current and the HAPF harmonic line current. Further investigation on the equivalent circuit transformations indicates that HAPF is equivalent to a controlled current source to compensate for load harmonic current and a virtual harmonic damping resistor between the series capacitor and grid impedance. Accordingly, the resonance damping and the nonlinear load low order harmonic current compensation can be well decoupled with minimal interference.

Dual-Band High-Efficiency Power Amplifier Based on a Series of Inverse Continuous Modes With Second-Harmonic Control

This letter proposes a design approach for a dual-band (DB) power amplifier (PA) based on a series of inverse continuous modes (SICMs). The approach possesses a wider fundamental and second-harmonic impedance space compared with inverse continuous class-F, and the dual bandwidths of the DB PA can be improved flexibly. In addition, a variable knee voltage is considered for predicting the output performance of the PA more accurately. A simple impedance control network only for the second-harmonic is exploited to improve PA efficiency. Simulation and measurement results indicate that the fabricated DB PA achieves drain efficiencies of 65%–80.9% from 2.43 to 2.70 GHz, and 65%–76.2% from 3.37 to 3.52 GHz, respectively, and the obtained output power exceeds 10 W in DBs.

Model-Based Adaptive Collaboration of Multi-Terminal Internal Force Tracking

This paper proposes a multi-terminal adaptive collaborative operation method for solving the problem of unstable internal force tracking in the clamping and handling of unknown objects by multi-terminal robots. In the proposed method, the internal command force changes the complex internal force control problem into an internal force tracking problem from multi-slave to master. Moreover, we develop an algorithm for multi-slave setups to estimate the object stiffness and motion uncertainty in the direction of the internal command force according to Lyapunov theory. Finally, the impedance control generates a reference trajectory for the multi-slave to maintain the desired internal force and track the master’s motion. Several experiments were conducted on a self-made robot. The experimental results show that the oscillation amplitude of each slave end is less than 1 mm and the directional oscillation amplitude is less than 1 degree during the tracking of the desired commanded internal force. For objects with a low stiffness, the error of the commanded internal force is less than 1 N (6%) per slave. The error in tracking the commanded internal force for objects with a high stiffness is less than 2 N (8%). The results prove the feasibility and effectiveness of the proposed method.

Impedance Force Control of Manipulator Based on Variable Universe Fuzzy Control

Impedance control is a classic and straightforward control method that finds wide applications in various fields. However, traditional constant impedance control requires prior knowledge of the environment’s stiffness and position information. If the environmental information is unknown, constant impedance control is not capable of handling the task. To address this, this paper proposes a variable universe fuzzy model reference adaptive impedance control method that achieves effective force tracking even in the presence of unknown environmental information. A variable universe fuzzy controller was employed to determine the impedance parameters. The force tracking error and its rate of change were used as two input parameters for the variable universe fuzzy controller, which utilizes fuzzy inference to obtain the incremental values of the impedance parameters. For the introduced model reference controller, a novel adaptive law was employed to obtain the coefficients for contact force and torque. Subsequently, the contact force of the manipulator in Cartesian space was taken as the research object, and a simulation model of a six-joint manipulator was established in MATLAB/Simulink. By comparing it with the constant impedance control method, the feasibility and effectiveness of this control approach were validated.

Evaluating adaptiveness of an active back exosuit for dynamic lifting and maximum range of motion

Back exosuits deliver mechanical assistance to reduce the risk of back injury, however, minimising restriction is critical for adoption. We developed the adaptive impedance controller to minimise restriction while maintaining assistance by modulating impedance based on the user’s movement direction and nonlinear sine curves. The objective of this study was to compare active assistance, delivered by a back exosuit via our adaptive impedance controller, to three levels of assistance from passive elastics. Fifteen participants completed five experimental blocks (4 exosuits and 1 no-suit) consisting of a maximum flexion and a constrained lifting task. While a higher stiffness elastic reduced back extensor muscle activity by 13%, it restricted maximum range of motion (RoM) by 13°. The adaptive impedance approach did not restrict RoM while reducing back extensor muscle activity by 15%, when lifting. This study highlights an adaptive impedance approach might improve usability by circumventing the assistance-restriction trade-off inherent to passive approaches. Practitioner summary: This study demonstrates a soft active exosuit that delivers assistance with an adaptive impedance approach can provide reductions in overall back muscle activity without the impacts of restricted range of motion or perception of restriction and discomfort.

Optimal physical human–robot collaborative controller with user-centric tuning

Collaborative robots are increasingly used in different fields of application to physically interact with the human (e.g., manufacturing, rehabilitation, etc.) In order to improve the physical collaboration performance, the interaction between the user and the robot must be safe, smooth, and intuitive. Indeed, this paper proposes a controller which is composed of three nested loops. A Passive Velocity Field Control (PVFC) defines the lowest control layer, ensuring the passivity of the system. The intermediate control layer is defined by a Cartesian impedance controller, managing the interaction between the user and the robot and sending to the PVFC a reference position. The outer layer is defined by a Linear Quadratic Regulator (LQR), detecting the intention of motion of the user and deforming accordingly the Cartesian impedance setpoint to follow such a motion. In addition, to enhance the collaboration performance for each user, a preference-based optimization approach is employed to tune the control parameters, implementing a human-centric tuning procedure. In such a way, the controller is customized for the specific user to establish the proper interaction with the robot. The proposed controller has been evaluated by making use of a Franka EMIKA panda robot as a test platform, comparing the achieved performance with a controller previously developed by some of the authors in a free-motion collaborative task along the z vertical direction. Achieved results show the improved performance obtained by the proposed controller. In addition, an assembly task has also been optimized to show the potential of the proposed control framework in complex and realistic situations.

Parallel Power Sharing Control of Multi-Controllable Rectifiers in a High-Power DC Fast Charging Station

The increase in demand for the fast charging of electric vehicles (EVs) has promoted research and the application of high-power direct current (DC) fast charging stations, and research on the stability control of charging stations with a parallel structure of multi-controllable rectifier modules is of great significance. Taking into account the dynamic and steady-state performance, the parameters of the dual-loop controller based on virtual impedance control are designed to realize the power sharing of multi-controllable rectifier modules. The constant power load model of EV charging at a constant current is established, and the load capacity of the cascaded system of converters is studied by using the impedance analysis method. The experimental and simulation results verify the effectiveness and correctness of the power sharing control strategy and the cascaded system stability analysis.

Improvement of directional relays based on constant impedance angle control of inverter interfaced distributed generations

With a large number of Inverter Interfaced Distributed Generations (IIDGs) being connected to active distribution network, there is a serious problem that the sensitivity of directional relay declines. The basic reason has been found that the phase angle of IIDG equivalent impedance is no longer constant and fluctuates in a large range. Researchers have proposed some methods to improve the directional relay performance by means of controlling the characteristic of IIDG equivalent impedance after a fault. However, all existing methods ignore the mandatory requirement of low voltage ride through, resulting in less practical value. This paper proposes a novel IIDG control strategy of constant impedance angle considering the requirement of low voltage ride through and presents a coordination scheme of control and protection to improve the performance of directional relay. Firstly, this paper divides voltage drop degree represented by k into three intervals, which are k>0.9, 0.2⩽k⩽0.9 and k<0.2. In each interval, the calculation methods of inner loop reference currents for d-axis and q-axis are derived respectively to achieve the proposed control strategy. Then, the influence of fault current limitation on the adaptability of the proposed control strategy is analyzed in the interval of 0.2⩽k⩽0.9. In addition, the switching scheme of control strategies and the coordination scheme are also designed in detail. Finally, digital simulations verify that the proposed control strategy can achieve the control objective of constant impedance angle while satisfying the requirement of low voltage ride through, regardless of how deep the voltage drop degrees are. Afterwards, the proposed coordination scheme is compared with the scheme in which the pre-fault constant PQ control strategy continues to be used after a fault. The comparison results demonstrate that the coordination scheme can improve the performance of directional relays effectively.

RESEARCH ON HUMAN–ROBOT PHYSICAL INTERACTION CONTROL BASED ON ADAPTIVE IMPEDANCE CONTROL

An adaptive impedance control method based on dexterity for compliant interaction is proposed for the problem of compliance and motion performance of the human’s healthy side interacting with the manipulator in bilateral mirror rehabilitation motion-assisted training, and constructs a local virtual force field to hinder the movement of the manipulator to the low motion performance region, thus improving the motion performance of the manipulator. Firstly, the dynamic model of the manipulator and the human–robot interaction model based on impedance control are established. Then, a dexterity index based on the condition number is established, and an adaptive impedance control method based on the dexterity is proposed to construct a local virtual force field to hinder the movement of the manipulator to the low motion performance region. Finally, the effectiveness of the proposed method is demonstrated by experiments. The results have shown that the adaptive impedance control method based on dexterity can construct a local virtual force field, which can constrain the motion of the manipulator and keep the robot with good motion performance. It also laid the foundation for the training strategy of bilateral mirror rehabilitation.

Circulating Current Suppression Strategy Based on Virtual Impedance and Repetitive Controller for Modular Multilevel Converter Upper and Lower Bridge Arm Capacitance Parameter Asymmetry Conditions

In recent years, modular multilevel converters (MMCs) have been increasingly used in the field of electric vehicle charging and discharging due to their unique performance advantages. However, the unique cascade structure of MMCs raises the problem of the circulating current. Due to chemical processes, aging effects, etc., the capacitance parameters of the upper and lower bridge arms will be asymmetric, which will introduce odd harmonics into the circulating current, increasing system losses and threatening the system reliability. To address this phenomenon, this paper proposes a circulating current suppression strategy with additional virtual impedance (VI) based on a repetitive controller (RC). The corresponding simulation models were built for the comparative study of different circulating current suppression strategies. The results show that the VI-RC circulating current suppression strategy can significantly reduce the odd and even harmonics in the circulating current under asymmetric conditions, and the total harmonic distortion (THD) of the bridge arm current is only 0.98%, which verifies the effectiveness of the proposed strategy.