Impedance Control Approach Research Articles

Robotic grinding and polishing of complex aeroengine blades based on new device design and variable impedance control

Owing to the advantages of good flexibility and low cost, robots are gradually replacing manual labor as an effective carrier for the grinding and polishing of aeroengine blades. However, the geometric features of blades are complex and diverse, and the contour accuracy and surface quality requirements are high, making the robotic grinding and polishing of blades still a challenging task. For this reason, this article first designs a new device by integrating different tools, which can achieve full-feature grinding and polishing of blades. Then, in order to improve the accuracy and stability of force tracking during the robotic grinding and polishing processes, a variable impedance control approach with simultaneous changes in stiffness and damping and parameter boundaries is proposed. Finally, the superiority of the proposed variable impedance control method is verified by comparative experiments on surface tracking. In addition, by combining the device with the variable impedance control method in the robotic grinding and polishing experiments of an aeroengine blade, their effectiveness in practical situations is confirmed.

Nonlinear observer-based impedance control of a fully-actuated hexarotor for accurate aerial physical interaction

PurposeFully-actuated unmanned aerial vehicles (UAVs) are a growing and promising field of research, which shows advantages for aerial physical interaction. The purpose of this paper is to construct a force sensor-denied control method for a fully-actuated hexarotor to conduct aerial interaction with accurate force exerted outward.Design/methodology/approachFirst, by extending single-dimension impedance model to the fully-actuated UAV model, an impedance controller is designed for compliant UAV pose/force control. Then, to estimate the interaction force between UAV end-effector and external environment accurately, combined with super-twisting theory, a nonlinear force observer is constructed. Finally, based on impedance controller and estimated force from observer, an interaction force regulation method is proposed.FindingsThe presented nonlinear observer-based impedance control approach is validated in both simulation and environments, in which the authors try to use a fully-actuated hexarotor to accomplish the task of aerial physical interaction finding that a specified force is able to be exerted to environment without any information from force sensors.Originality/valueA solution of aerial physical interaction for UAV system enabling accurate force exerted outward without any force sensors is proposed in this paper.

A Variable Impedance Skill Learning Algorithm Based on Kernelized Movement Primitives

This paper proposes a novel learning from demonstrations (LfD) method based on kernelized movement primitives (KMP). The original KMP algorithm is excellent at generalizing and handling high-dimensional inputs, but it is slightly inadequate in reproduction accuracy. To address this issue, we make two improvements to the KMP algorithm. Firstly, a multivariate Gaussian process (MV-GP) is employed to model the reference trajectory, which preliminarily improves the reproduction accuracy of KMP. Secondly, an optimization problem is formulated to learn the hyperparameters of the kernel function in KMP, which reduces the dependence on experience. We also propose a novel variable impedance control (VIC) approach to trade off contact compliance against tracking accuracy by utilizing the probabilistic properties of the KMP. Comparative simulations and experiments are conducted to validate the proposed LfD algorithm.

Hierarchical control of manipulator with null-space compliance at the kinematic level

This article proposes a hierarchical control framework with null-space impedance at the kinematic level. The proposed framework aims to overcome the limitations of the prior methods for null-space compliance which rely on the dynamics of the manipulator. Two task-space control laws and a null-space control law at the kinematic level are designed to improve task-space errors and exhibit compliant joint motion behavior. The task-space’s end-effector force tracking uses an adaptive variable impedance control approach to enhance tracking performance. Experimental results conducted on a 7R manipulator demonstrate that the proposed control framework is capable of improving task performance when interaction forces act on the manipulator body.

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.

Model Predictive Variable Impedance Control of Manipulators for Adaptive Precision-Compliance Tradeoff

Impedance control (IC) is widely used in contact-rich manipulator tasks since it provides manipulators with both operation precision and contact compliance, and trades them off by impedance parameters. However, fixed impedance parameters limit the applicability of IC in complex tasks during which the focus on the operation precision or the contact compliance is variable, such as physical human–robot collaboration and complex assembly tasks. This article presents model predictive variable impedance control approaches for adaptive precision-compliance tradeoff to satisfy variable task requirements. Specifically, we establish a novel impedance model, which transforms the variable impedance law design problem into a control law design problem, and allows us to consider novel impedance constraints that can determine manipulators' extreme precision and compliance properties. According to whether state constraints are further considered, one-step (OS) and multistep (MS) model predictive control approaches are proposed to solve these transformed control problems, and the corresponding optimization problem of the OS MPC can be established as a QP problem due to the special form of the novel impedance model. A tank-based approach is further proposed to correct the variable impedance laws for the system passivity concern. Various comparative experiments are conducted to validate the effectiveness of the presented approaches.

Geometric Impedance Control on SE(3) for Robotic Manipulators

After its introduction, impedance control has been utilized as a primary control scheme for robotic manipulation tasks that involve interaction with unknown environments. While impedance control has been extensively studied, the geometric structure of SE(3) for the robotic manipulator itself and its use in formulating a robotic task has not been adequately addressed. In this paper, we propose a differential geometric approach to impedance control. Given a left-invariant error metric in SE(3), the corresponding error vectors in position and velocity are first derived. We then propose the impedance control schemes that adequately account for the geometric structure of the manipulator in SE(3) based on a left-invariant potential function. The closed-loop stabilities for the proposed control schemes are verified using Lyapunov function-based analysis. The proposed control design clearly outperformed a conventional impedance control approach when tracking challenging trajectory profiles.

Motion Planning and Cooperative Manipulation for Mobile Robots With Dual Arms

With large work space and dexterous manipulation capability, mobile robots with dual arms can be used in complex operation scenes such as active detection, disassembly, spraying, cleaning and assembly, is a promising direction for robot development. In this paper, a hybrid control approach is proposed for a mobile robot with dual arms to fulfil an explosive disposal task. Firstly, the motion planning for mobile base and trajectory planning for dual arms are developed, and a hierarchical task planner is designed using the finite state machine to make the robot system to deal with events sensed by active vision. A rapidly-exploring random tree-based motion planning is developed in task space for the mobile base to realize dynamic collision avoidance, while the trajectory planning approach is proposed in the framework of a dual-arm master-slave coordinated mechanism. Next, for mobile robots to complete complex task such as explosive disposal using two dexterous hands, the impedance control approach with slippage detection is developed by considering slippage tendency and slippage intensity to produce a stable in-hand manipulation. Furthermore, the Faster R-CNN is employed to determine the grasping region for robot manipulation through object detection and learning. Finally, the explosive disposal scene is designed to justify the effectiveness and good performance of the proposed methods.

Whole-Body Fuzzy Based Impedance Control of a Humanoid Wheeled Robot

Humanoid robots can imitate human behaviour and provide interactive services to humans due to their humanoid form, especially humanoid wheeled robots that can perform more complex tasks with the additional mobility. With the development of robotics technology, humanoid robots have been used increasingly in the domestic environment where the robot needs to interact with unknown environments. This requires the robot to have both the ability to track with high accuracy and the ability to comply with complex environments. It is known that the robots with impedance control can have a superior performance in terms of compliance with unknown contact environments. However, the mobility of humanoid robots with wheels complicates the dynamic model of robots, which makes the development of impedance control challenging. In this letter, a whole-body impedance control approach for humanoid wheeled robots is proposed, with fuzzy adaptive systems to compensate for the uncertain dynamics of the controlled system. This approach realizes safe interaction and compliant operation with unknown environments including humans. Additionally, the experimental results conducted on a humanoid wheeled robot illustrate the effectiveness of the proposed controller.

Distributed Control Scheme for Accurate Power Sharing and Fixed Frequency Operation in Islanded Microgrids

Global Positioning System (GPS) based control has recently been reported as a replacement of droop control to achieve fixed frequency operation in islanded microgrids. This article presents the perspective that the power sharing performance of a general microgrid synchronized by GPS is essentially determined by equivalent output impedance. A novel adaptive virtual impedance control approach, which implements different values of virtual resistance for d- and q-axis, is proposed accordingly. The virtual resistance concept is implemented comprising a basic local implementation for output impedance shaping, and a sparse resistance tuning network for the compensation of mismatched feeder impedance, which demands no knowledge of actual output impedance. The resistance tuning network utilizes the consensus protocol and only requires neighboring interactions among DG units. A complete tuning of output resistance for a given load condition results in accurate active and reactive power sharing even after communication is interrupted and will still outperform conventional droop control methods if load changes during the interruption. Small-signal analysis based on delay differential equations model of the overall microgrid is performed to investigate the adverse impact of communication delays on system stability. The efficacy of the proposed approach is validated by both simulation and experimentation.

Fuzzy impedance-based control with fast terminal sliding mode force control loop for a series elastic actuator system

This paper proposes a robust control scheme to accomplish the interaction control problem between a series elastic actuator (SEA) and a flexible environment. The adaptability of the controller to unknown variations and robustness of the controller during interaction of the system with environment are the main aims. The control scheme is based on a fuzzy impedance control approach and consists of an inner fast terminal sliding mode force control loop. An experimental setup is designed to prove the efficiency of the developed controller. The experimental results confirm that the proposed fuzzy logic controller guarantees the sensitivity of the controlled system to unpredictable variations. Moreover, by applying the fast terminal sliding mode algorithm for the inner force control loop, the system has faster convergence to the reference path compared with similar control methods found in the literature.

Stability-Guaranteed Variable Impedance Control of Robots Based on Approximate Dynamic Inversion

Variable impedance control has been considered as one of the most important compliant control approaches for its abilities in improving compliance, safety, and efficiency in robot–environment interaction. However, existing variable impedance controllers have deficits in stability guarantee. This article proposes a stability-guaranteed variable impedance control approach for robots with modeling uncertainties based on approximate dynamic inversion (ADI). Novel constraints on variable impedance profiles are given to guarantee the exponential stability of the desired variable impedance dynamics. An ADI-based impedance control law is designed to achieve the desired variable impedance dynamics through the convergence of a variable impedance error. Based on the extended Tikhonovs theorem, it is proven that the closed-loop control system has semiglobal practical exponential stability. The proposed impedance controller can be implemented in a PID form and is appealing for its simple structure, easy implementation, and control stability guarantee. The effectiveness of the proposed variable impedance controller is illustrated by an illustrative example taken on a five-bar parallel robot.

Novel fractional hybrid impedance control of series elastic muscle-tendon actuator

Purpose This paper aims to develope a novel fractional hybrid impedance control (FHIC) approach for high-sensitive contact stress force tracking control of the series elastic muscle-tendon actuator (SEM-TA) in uncertain environments. Design/methodology/approach In three different cases, the fractional parameters of the FHIC were optimized with the particle swarm optimization algorithm. Its adaptability to the pressure of the sole of the foot on real environments such as grass (soft), carpet (medium) and solid floors (hard) is far superior to traditional impedance control. The main aim of this paper is to derive the dynamic simulation models of the SEM-TA, to develop a control architecture allowing for high-sensitive contact stress force control in three cases and to verify the simulation models and the proposed controller with experimental results. The performance of the optimized controllers was evaluated according to these parameters, namely, maximum overshoot, steady-state error, settling time and root mean squared errors of the positions. Moreover, the frequency robustness analysis of the controllers was made in three cases. Findings Different simulations and experimental results were conducted to verify the control performance of the controllers. According to the comparative results of the performance, the responses of the proposed controller in simulation and experimental works are very similar. Originality/value Origin approach and origin experiment.

RLS Impedance Intelligence Control Algorithm for Wire Peeler of Robot in Complex Power Networks

Considering the wire core which is easily damaged because of the instability of the power distribution robot during the process of peeling the insulation layer, we have proposed a cutting force tracking control algorithm based on impedance control that is suitable for the end peeling instrument. At present, the task requirement of sudden changes about environment stiffness cannot be accomplished by many impedance control approaches due to the complexity of working environment stiffness about power distribution robot; then, the Recursive Least Square (RLS) method was introduced into the impedance control algorithm to identify the cable insulation layer and cable core stiffness online to achieve accurate and stable tracking of the cutting force. Furthermore, the impedance control of peeling cable insulation layer and the proposed RLS method were simulated and tested contrastively, and the high-voltage cable peeling experiment was performed. The results of simulation and experiment showed that the force control algorithm based on RLS parameter identification still has good force tracking performance during the environment stiffness changes suddenly, and the steady-state error approaches zero, demonstrating the feasibility and effectiveness of the RLS impedance control algorithm, which has important practical significance for improving power distribution efficiency.

Learning peg-in-hole assembly using Cartesian DMPs with feedback mechanism

Purpose This paper aims to enable the robot to obtain human-like compliant manipulation skills for the peg-in-hole (PiH) assembly task by learning from demonstration. Design/methodology/approach A modified dynamic movement primitives (DMPs) model with a novel hybrid force/position feedback in Cartesian space for the robotic PiH problem is proposed by learning from demonstration. To ensure a compliant interaction during the PiH insertion process, a Cartesian impedance control approach is used to track the trajectory generated by the modified DMPs. Findings The modified DMPs allow the robot to imitate the trajectory of demonstration efficiently and to generate a smoother trajectory. By taking advantage of force feedback, the robot shows compliant behavior and could adjust its pose actively to avoid a jam. This feedback mechanism significantly improves the dynamic performance of the interactive process. Both the simulation and the PiH experimental results show the feasibility and effectiveness of the proposed model. Originality/value The trajectory and the compliant manipulation skill of the human operator can be learned simultaneously by the new model. This method adopted a modified DMPs model in Cartesian space to generate a trajectory with a lower speed at the beginning of the motion, which can reduce the magnitude of the contact force.

A nonlinear robust optimal controller for an active transfemoral prosthesis: An estimator-based state-dependent Riccati equation approach

This article presents an estimator-based nonlinear robust optimal controller for an active prosthetic leg for transfemoral amputees. The proposed controller is derived from a combination of the state-dependent Riccati equation technique to optimize the energy consumption of the robot/prosthesis system and the sliding mode control to reduce the effects of the model parametric uncertainties and ground reaction forces as nonparametric uncertainties. In addition, the integral state control technique is employed to improve tracking; also, to have a compromise between tracking performance and control signal chattering, the boundary layer is then used. In this study, the performance of both the controller and estimator in the presence of noise and disturbance is assessed for nominal system while ±40% parametric uncertainty with respect to saturation bounds of control signals is considered. The results of the simulation in this research with ±40% parametric uncertainty compared to a robust adaptive impedance control approach with the only variation of ±30% on the system parameters, show high performance of the proposed controllers in reducing energy consumption, good robustness, improved position tracking performance, and good performance in estimating state variables, even in the presence of large initial errors compared to the extended Kalman filter.

Optimal Sliding Mode Controller for an Active Transfemoral Prosthesis Using State-Dependent Riccati Equation Approach

In this paper, a nonlinear robust optimal controller is designed for an active transfemoral prosthesis using sliding mode control and state-dependent Riccati equation control. In this method, unlike most nonlinear control methods, the Jacobian approach is not used for model linearization and system's state space equations are used directly. This is a reason for the accuracy and flexibility of the proposed controller in design compared to other conventional methods. Since the proposed approach is energy-driven, the main objective of this research is to optimize the energy consumption of the robot/prosthesis system, reduce the effects of disturbances, noise, and parametric uncertainties, and desirable trajectory tracking of the vertical displacement in hip and thigh and knee angles. To this aim, the integral state control technique and the boundary layer are used for reconciliation between tracking performance and control signal chattering. In this study, the performance of the controller is assessed for nominal system and uncertain system with ± 30% parameters’ uncertainty by considering the saturation bounds of control signals. The simulation results demonstrate a decrease in the control effort, good robustness in the presence of uncertainty, and desirable tracking performance compared to a robust adaptive impedance control approach.

Collision detection and force control based on the impedance approach and dynamic modelling

PurposeThis paper aims to address the collision problem between robot and the external environment (including human) in an unstructured situation. A new collision detection and torque optimization control method is proposed.Design/methodology/approachFirstly, when the collision appears, a second-order Taylor observer is proposed to estimate the residual value. Secondly, the band-pass filter is used to reduce the high-frequency torque modeling dynamic uncertainty. With the estimate information and the torque value, a variable impedance control approach is then synthesized to guarantee that the collision is avoided or the collision will be terminated with different contact models and positions. However, in terms of adaptive linear force error, the variation of the thickness of the boundary layer is controlled by the new proximity function.FindingsFinally, the experimental results show the better performance of the proposed control method, realizing the force control during the collision process.Originality/valueOrigin approach and origin experiment.

Impedance Reduction Control of a Knee Joint Human-Exoskeleton System

Reducing human lower limb effort during walking is still a challenge for wearable exoskeletons. From the wearer’s viewpoint, joint impedance increases while wearing the exoskeleton due to the fact that the exoskeleton’s mass, friction, and gravity are added to those of the human lower limbs. Active impedance is required from the exoskeleton to compensate not only the exoskeleton’s mechanical impedance but also that of the human limb. This paper presents a nonlinear impedance reduction control (IRC) approach applied to a knee joint exoskeleton during flexion/extension movements. The IRC approach ensures impedance adaptation of the human-exoskeleton system toward a desired level. The proposed method is an alternative to sensor-based impedance controllers where the human joint torque is estimated using electromyography (EMG) sensors, force/torque sensors, and so on. The performance of the proposed approach and its robustness with respect to modeling uncertainties are theoretically analyzed and discussed. Experiments were conducted with four healthy subjects to verify the effectiveness of human effort reduction. The root mean square of the EMG signals of the muscles involved in the flexion/extension was used as a metric. The experimental results show that EMG signal levels can be efficiently reduced by inertia, damping, and gravity compensation compared with those obtained without wearing the exoskeleton.

Impedance Control of Hydraulic Actuation Systems With Inherent Backdrivability

The demand for high-performance impedance control in electro-hydraulic actuation systems is a mainstream issue in the robot actuation research community. Although various nonlinear model-based impedance controllers have been developed and showed good performance in recent years, they remain hindered by the high cost of force sensors, and accurate internal dynamics models need to be derived to overcome the non-backdrivability and complex dynamics of hydraulic systems. As a solution to these problems, this paper presents an impedance control approach for hydraulic systems that require no external force sensors or chamber pressure sensors with a pressure control servovalve or backdrivable servovalve. First, we show that a backdrivable servovalve brings inherent backdrivability to hydraulic systems, such that high-performance impedance control can be implemented without requirement of force sensors and exact knowledge on the dynamics of hydraulic chambers, owing to its torque-source property and low effective valve inertia on the link side. Second, utilizing the obtained backdrivability, we develop a passivity-guaranteed impedance controller. A momentum-based external torque observation algorithm is incorporated to render desired impedance over a wide range, without using force/torque sensor. The performance of the proposed backdrivable servovalve and impedance controller was verified through extensive experimental results.