Impedance Control Of Robot Research Articles

Operational space robust impedance control of the redundant surgical robot for minimally invasive surgery.

The motion accuracy, compliance, and control smoothness for the surgical robot are of great importance to improve the safety of human-robot interaction. However, the end effector that interacts with soft tissue during surgery affects the dynamics of the robot. The control performance of the controller may be decreased if the changing dynamics are not identified and updated in time. This paper proposes a robust impedance controller for the redundant remote center of motion manipulator influenced by external disturbances, including external torque, uncertainties, and unmodeled terms in the dynamics. To achieve the desired impedance, a continuously switching sliding manifold is proposed. When the sliding manifold is driven to zero, the motion error will converge to a bounded region. This can overcome the adverse effects of external disturbances while guaranteeing motion accuracy and compliance. Chattering of the sliding mode control is alleviated through the formulated continuously switching sliding manifold and integrated nonlinear disturbance observer. Simulations and experiments demonstrate that the proposed controller has excellent motion accuracy, compliance, and control smoothness. This provides potential application prospects for the redundant surgical robot to guarantee safe human-robot interaction.

DESIGN, DEVELOPMENT AND HYBRID IMPEDANCE CONTROL OF AN ANKLE REHABILITATION ROBOT

DESIGN, DEVELOPMENT AND HYBRID IMPEDANCE CONTROL OF AN ANKLE REHABILITATION ROBOT

Confutation of the “Counterexample to Passivity Preservation for Variable Impedance Control of Compliant Robots”

Confutation of the “Counterexample to Passivity Preservation for Variable Impedance Control of Compliant Robots”

Event-triggered critic learning impedance control of lower limb exoskeleton robots in interactive environments

In this paper, we present an event-triggered critic learning impedance control algorithm for a lower limb rehabilitation exoskeleton robot in an interactive environment, where the control objective is specified by a desired impedance model. In comparison to many other traditional impedance controller design algorithms, in this paper, the impedance control problem is transformed into an optimal control problem. Firstly, the interactive environment accounts for the interaction between the exoskeleton, the human, and the environment, and is modeled by a linear time-invariant exogenous system. Secondly, in contrast to time-triggered control design mechanisms, the event-triggered controller is updated only when the system states deviate from prescribed threshold values. To obtain the event-triggered optimal controller, a critic neural network is developed through the framework of reinforcement learning. A modified gradient descent method is introduced to update the weights of the critic network with an additional stable term employed to eliminate the need for an initial admissible control. Meanwhile, with the simultaneous application of historical and transient state data to the critic neural network, the persistent excitation conditions are relaxed. The Lyapunov method is used to rigorously demonstrate the stability of the overall system. Finally, the effectiveness of the proposed algorithm is demonstrated via simulation.

Research on fuzzy impedance control of upper-limb rehabilitation robot based on membership functions online optimization learning strategy

PurposeTo improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.Design/methodology/approachFirst, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.FindingsThis method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.Originality/valueThe TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.

Adaptive fuzzy impedance control of exoskeleton robots with electromyography-based convolutional neural networks for human intended trajectory estimation

Adaptive fuzzy impedance control of exoskeleton robots with electromyography-based convolutional neural networks for human intended trajectory estimation

Contact force cancelation in robot impedance control by target impedance modification

AbstractA force sensorless impedance controller is proposed in this paper for robot manipulators without using force estimators. From the observation of the impedance control law, the force feedback term can be canceled if the inertia matrix in the target impedance is the same as the robot inertia matrix. However, the inertia matrix in the target impedance is almost always a constant matrix, while the robot inertia matrix is a function of the robot configuration, and hence, they may not be identical in general. A modification of the coefficient matrix for the contact force term in the target impedance is suggested in this paper to enable cancelation of the force feedback term in the impedance control law so that a force sensorless impedance controller without using force estimators can be obtained. The tracking performance in the free space phase and the motion trajectory in the compliant motion phase of the new design are almost the same as those in the traditional impedance control. Modification of the inertia matrix in the target impedance will result in small variations of the contact force which is acceptable in practical applications. For robot manipulators containing uncertainties, an adaptive version of the new controller is also developed in this paper to give satisfactory performance without the need for force sensors. Rigorous mathematical justification in closed-loop stability is given in detail, and computer simulations are performed to verify the efficacy of the proposed design.

Impedance Control of a Wrist Rehabilitation Robot Based on Autodidact Stiffness Learning

Dynamic control of an intrinsically compliant robot is paramount to ensuring safe and synergistic assistance to the patient. This paper presents an impedance controller for the rehabilitation of stroke patients with compromised wrist motor functions. The control design employs a Koopman operator-based autodidactic system identification model to predict the anatomical stiffness of the wrist joint during its various degrees of rotational motion. The proposed impedance controller, perceiving the level of the subjects’ participation from their joint stiffness, can modify the applied force. The end-effector robot has a parallel structure that uses four biomimetic muscle actuators as parallel links between the end-effector and the base platform. The controller performance is corroborated by testing the end-effector robot with three healthy subjects.

Impedance control and parameter optimization of surface polishing robot based on reinforcement learning

Polishing robot is an automatic system in which the robot controls the end effector to fix the polishing tool and finish the workpiece polishing efficiently. In order to solve the problem of how to maintain the stability of actuator contact force in the robot automatic polishing system, a learning algorithm of robot impedance control parameters based on reinforcement learning is proposed and the impedance control model is established in this paper. The influence parameters (inertia M, damping B, stiffness K) of impedance performance are analyzed by numerical simulation method and the optimized impedance parameters are obtained at last. Due to the small number of iterations and high data utilization rate, reinforcement learning algorithm is more suitable for robot constant force tracking. In the process of applying reinforcement learning algorithm, a combination of dynamic matching method and linearization method is proposed to predict the output distribution of the state, which greatly improves the cost function of the evaluation strategy, and impedance parameters corresponding to the optimal strategy are obtained. Finally, steam turbine blade is taken as polishing test part. The average roughness of the selected points of test part after polishing is only 0.302μm, and much less than 1.151μm before polishing, which verifies the feasibility of the proposed impedance control method.

Application of the Half-Order Derivative to Impedance Control of the 3-PUU Parallel Robot

This paper presents an extension of impedance control of robots based on fractional calculus. In classical impedance control, the end-effector reactions are proportional to the end-effector position errors through the stiffness matrix K, while damping is proportional to the first-order time-derivative of the end-effector coordinate errors through the damping matrix D. In the proposed approach, a half-derivative damping is added, proportional to the half-order time-derivative of the end-effector coordinate errors through the half-derivative damping matrix HD. The discrete-time digital implementation of the half-order derivative alters the steady-state behavior, in which only the stiffness term should be present. Consequently, a compensation method is proposed, and its effectiveness is validated by multibody simulation on a 3-PUU parallel robot. The proposed approach can be considered the extension to MIMO robotic systems of the PDD1/2 control scheme for SISO mechatronic systems, with potential benefits in the transient response performance.

Passive Impedance Control of Robots With Viscoelastic Joints Via Inner-Loop Torque Control

This article presents passive impedance control of flexible joint robots (FJRs) via inner-loop torque control of elastic joints. However, according to our theoretical analysis, the torque control methods of series elastic actuators (SEAs) are often limited by the fact that the acceleration signals are amplified by the control gains. Since the acceleration signals are often affected by differentiation noise, the analysis may become invalid in practice. To alleviate this limitation, we propose the use of the so-called series viscoelastic actuator (SvEA), which significantly reduces the acceleration amplification. Consequently, in contrast to the SEA case, the theoretical analysis of an SvEA-based FJR is valid in real implementations. We would like to highlight the fact that the theoretical analysis (more specifically, passivity analysis) is performed for nonlinear robot dynamics without linearization. As a result, the passive impedance controller can be realized more robustly with enhanced inner-loop torque control.

Adaptive variable impedance control of dual-arm robots for slabstone installation

The conventional dual-arm cooperative control method employed in the construction field cannot adequately meet the requirements of high precision and adaptability because of the use of large objects, heavy load, unstructured environment, and constraints related to the complex operation processes involved. Dual-arm robots are highly complex multi-degree-of-freedom system, and when using this robots for slabstone installation, it is necessary to consider not only the position constraint and force coupling relationship of the closed chain system, but also the force/position control while the slabstone contacts the wall. To solve this problem, this paper presents slabstone-installation model and motion element decomposition for dual-arm robots. Moreover, a control strategy is proposed by combining an adaptive variable impedance tracking controller for the force/position control of the slabstone and a tracking controller for the end-effector trajectories of the dual arms; the controllers proposed meet the requirements of position tracking and contact force tracking of the slabstone. Finally, different slabstone installation scenarios are simulated to verify the effectiveness of the proposed algorithm. The results show that the algorithm is compliant for the slabstone installation process and can meet the requirements of force/position control.

Analytical methodology for the analysis of vibration for unconstrained discrete systems and applications to impedance control of redundant robots

This paper presents a general methodology for the analysis and synthesis of a positive semi-definite system described by mass, damping and stiffness matrices that is often encountered in impedance control in robotics research. This general methodology utilizes the fundamental kinematic concept of rigid-body and non-rigid-body motions of which all motions consist. The rigid-body mode results in no net change in the potential energy from the stiffness matrix of the multiple degree-of-freedom (DoF) discrete mechanical system. Example of an unconstrained discrete mechanical system is presented to illustrate the theoretical principle as applied in obtaining the free and forced vibration responses, as well as the dynamic characteristics of the system in natural frequency, omega_n and damping ratio, zeta. In addition, the methodology is applied to the impedance control of redundant robots. The rigid-body mode is equivalent to the motions of a redundant robot which result in no net change in potential energy, also called the zero-potential or ZP mode, of impedance control. Example of a redundant robot is used to demonstrate the application of the methodology in robotics. The dynamic characteristics of omega _n and zeta in the modal space are analyzed, which can be synthesized to modulate the damping of the system analytically.

Neural network-based physiological organ motion prediction and robot impedance control for teleoperated beating-heart surgery

Compared to conventional arrested heart surgery, beating-heart surgery is promising as the advantages of eliminating adverse effects caused by a heart-lung bypass machine and enabling intraoperative evaluation of heart motion. However, the fast motion of the heart introduces a significant challenge for beating-heart surgery. In this paper, a teleoperation system, which employs an impedance control for the master robot and an ultrasound image-based position control for the slave robot (surgical robot), is proposed to achieve non-oscillatory force feedback and heart motion compensation, respectively. Specifically, an impedance model is designed for the master robot to provide the human operator (surgeon) with non-oscillatory haptic feedback. To compensate for the beating heart’s motion, ultrasound imaging is used to obtain the position of the point of interest (POI) on the heart tissue. As the use of ultrasound imaging introduces non-negligible time delay caused by image acquisition and processing, a recurrent neural network (NN)-based physiological organ motion predictor is proposed. The predicted POI position is used to control the slave robot to automatically compensate for the beating heart’s motion. The proposed method is validated through experiments. The proposed control strategy with NN-based heart motion predictor is compared to the other two strategies without heart motion predictor and with an extended Kalman filter (EKF)-based heart motion predictor. The experimental results present that the proposed strategy with NN algorithm shows significant advantages (higher synchronization accuracy and relatively steady slave-heart contact force) over the other two strategies.

잔여외란을 고려한 외란관측기 기반 고자유도 로봇의 강인 임피던스제어

잔여외란을 고려한 외란관측기 기반 고자유도 로봇의 강인 임피던스제어

Design, modeling, and impedance control of a new in-pipe inspection robot equipped by a manipulator

In this paper, a new in-pipe robot is designed and modeled, which is equipped by a manipulator in order to perform repairing tasks within the pipelines. Also, in order to provide a good manipulation process, impedance control is designed and implemented for the robot. Most of the in-pipe robots are limited to perform inspecting operations and are not capable of conducting manipulating tasks. In order to cover the mentioned deficiency, the robot is redesigned by adding a manipulator on the main body of the moving platform. Afterward, the model of the overall robot is extracted. Finally, impedance control is also designed and implemented for the robot so that not only the position of the end-effector can be controlled, but also the required force to cover the repairing task can be precisely provided. The correctness of modeling and efficiency of the proposed mobile in-pipe robot is verified by conducting some simulation scenarios in MATLAB. It will be seen that by the aid of the proposed mechanism and employing the designed force controlling strategy, the manipulation process of the robot in the pipes can be realized successfully.

Fuzzy Adaptive Sliding Mode Impedance Control of Fracture Reduction Robot

With the development of robotics, it will be possible for fracture reduction robots to replace doctors in performing surgery operations. The surgery accuracy and safety by the reduction robot is important. In order to compensate various uncertainties and nonlinear problems in the reduction robot impedance control system, this paper proposes a fuzzy adaptive sliding mode impedance control of the reduction robot, which includes force residual observer (FRO) and fuzzy adaptive sliding mode controller (FASMC). The FRO is used to estimate the external force between the reduction robot and the fractured musculoskeletal tissue in real-time, no force sensor is installed at the end-effector of reduction robot. The FASMC mainly includes three parts: linearizing the system by inverse dynamics and PD control, improving the system's robustness by the sliding mode control and fuzzy adaptive switching gain to reduce chattering, eliminating the nonlinear disturbance term of the system, and the normalized factor linear combination fuzzy system is used to compensate. The co-simulation of the fracture reduction robot shows that the FASMC impedance control method has a better steady-state position and force tracking accuracy, the steady-state position accuracy is -0.733 mm, and the steady-state force accuracy is -2.12 N. This paper provides an effective method for impedance control of the fracture reduction robot.

Impedance control of multi-arm space robot for the capture of non-cooperative targets

Robotic systems are expected to play an increasingly important role in future space activities. The robotic on-orbital service, whose key is the capturing technology, becomes a research hot spot in recent years. This paper studies the dynamics modeling and impedance control of a multi-arm free-flying space robotic system capturing a non-cooperative target. Firstly, a control-oriented dynamics model is essential in control algorithm design and code realization. Unlike a numerical algorithm, an analytical approach is suggested. Using a general and a quasi-coordinate Lagrangian formulation, the kinematics and dynamics equations are derived. Then, an impedance control algorithm is developed which allows coordinated control of the multiple manipulators to capture a target. Through enforcing a reference impedance, end-effectors behave like a mass-damper-spring system fixed in inertial space in reaction to any contact force between the capture hands and the target. Meanwhile, the position and the attitude of the base are maintained stably by using gas jet thrusters to work against the manipulators' reaction. Finally, a simulation by using a space robot with two manipulators and a free-floating non-cooperative target is illustrated to verify the effectiveness of the proposed method.

Learning impedance control of robots with enhanced transient and steady-state control performances

This study proposes a learning impedance controller comprising a proportional feedback control term, a composite-learning-based uncertainty estimation term, and a robot-environment interaction control term. The impedance control problem is converted into a particular reference-trajectory tracking problem based on a generated reference trajectory. The proposed controller ensures the exponential convergence of the auxiliary tracking error and the uncertainty estimation error. The interaction control term improves the transient control performance through suppression/encouragement of the incorrect/correct robot movements. The composite-learning update law enhances the transient and steady-state control performances based on the exponential convergence of the uncertainty estimation error and auxiliary tracking error. Finally, the effectiveness and advantages of the proposed impedance controller are validated by theoretical analysis and simulations on a parallel robot.

Exponentially convergence for the regressor-free adaptive fuzzy impedance control of robots by gradient descent algorithm

Having the capability to estimate parametric and non-parametric uncertainties, this paper investigates a regressor-free adaptive model-reference scheme for impedance control of robotic systems interacting with an environment. Using the gradient descent algorithm for designing a fuzzy estimator makes the tune of controller’s parameters possible in different physical situations and uncertainties. Thanks to the voltage control strategy and fuzzy systems, there is no need for designers to have the knowledge of robots and actuators’ dynamics. In addition, the force feedback is not employed in the structure of control law. Using the Lyapunov-like stability analysis, not only the exponential convergence of error signal and its time derivative to zero are guaranteed in the decentralised form but also the boundedness of all signals is ensured. To confirm the efficiency of proposed control algorithm, several simulations as well as a comparison with a positioned-based impedance controller and a regressor-based adaptive impedance controller are conducted on a two-link planar robot manipulator considering a tunable desired trajectory and different stiffness of environment. Additionally, the proposed adaptive impedance controller is applied to a six degree of freedom revolute-joint manipulator to provide better evaluation.