Joint Servo Research Articles

Dynamic modelling and a model-based control strategy of joint servo system for power transmission line inspection robot

Abstract The time-varying load inertia is one of the important dynamic characteristics of the power transmission line inspection robots (PTLIRs) in joint space, which can heavily affect the stability of the robot in the inspection process. In this paper, with considering the time-varying characteristics of load inertia, a method for modelling and control of the flexible joint servo system of the PTLIR is studied. First, the control system of the PTLIR is established based on the two inertia system. In order to calculate the load inertia, a dynamic model of the inspection robot is established. Then, the model-based notch filter is designed to improve dynamic performance of the robot, and suppress the vibration amplitude change which caused by the time-varying load inertia. Finally, the comparison of the control performance between the traditional control strategy and the model-based control strategy with notch filter are compared. The simulation results show that the paper can provide an effective tool for modelling and improving the stability of the PTLIR.

Characteristic Analysis and Control Loop Design of Transmission Torque and Jerk for Flexible Joint Servo Systems

Characteristic Analysis and Control Loop Design of Transmission Torque and Jerk for Flexible Joint Servo Systems

Vibration characteristics of industrial robot joint servo transmission system based on electromechanical coupling

The complex electromechanical coupling effect of an industrial robot’s electromechanical system significantly influences the dynamic characteristics and stability of the joint servo transmission system. This study proposes a kind of electromechanical coupling dynamic model for the industrial robot’s joint servo transmission system, incorporating multiple parameters, and investigates the vibration response characteristics of the system. Firstly, an electromechanical coupling analysis of the industrial robot’s joint servo transmission system is conducted, simplifying it as a ‘motor-reducer-load’ system and establishing the corresponding electromechanical coupling vibration mathematical model. Secondly, a dynamic model of the robot’s joint servo transmission system is developed to analyze its speed characteristics. Finally, the model is used to analyze the electromechanical coupling vibration process of the joint servo transmission system with the introduction of mechanical and electrical parameters and other factors to obtain the vibration characteristics of the industrial robot joint servo transmission system under electromechanical coupling. The experimental results show that this model can better analyze the electromechanical coupling vibration characteristics of the joint servo transmission system, which is significant for improving the performance and fault traceability of the industrial robot joint transmission.

Intelligent Servo Control Strategy for Robot Joints With Incremental Bayesian Fuzzy Broad Learning System

Intelligent servo control significantly reduces the need to adjust control parameters, and is, therefore, widely used in robot joint control. However, existing intelligent servo control strategies for robot joints have problems of computational redundancy, limited prediction accuracy, and insufficient generalization capability. To solve these problems, this article proposes a servo control strategy for robot joints that is based on the incremental Bayesian fuzzy broad learning system (IBFBLS). First, we construct an intelligent servo control strategy with broad learning system on the basis of fuzzy rules to achieve good self-learning and generalization abilities. Second, the learning parameters of the control strategy are optimized by Bayesian inference to achieve precise joint servo control. Finally, the convergence of the control strategy is enhanced by combining it with Lyapunov theory to constrain the learning parameters of the proposed control strategy. The feasibility and superiority of the proposed control strategy are verified by simulation to compare it with existing intelligent servo control methods. In addition, experiments are conducted using robot joint test bed. Both the simulation and experiments verify that the proposed servo control strategy outperforms other servo control methods with respect to tracking accuracy, stability, and convergence. The root-mean-square error in servo control of robot joints was 0.012 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , which has been reduced by 55.56 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> compared with the current state of the art.

Adaptive lead-through teaching control for spray-painting robot with closed control system

AbstractIndustrial robots are widely used in the painting industry, such as automobile manufacturing and solid wood furniture industry. An important problem is how to improve the efficiency of robot programming, especially in the current furniture industry with multiple products, small batches and increasingly high demand for customization. In this work, we propose an outer loop adaptive control scheme, which allow users to realize the practical application of the zero-moment lead-through teaching method based on dynamic model without opening the inner torque control interface of robots. In order to accurately estimate the influence of joint friction, a friction model is established based on static, Coulomb and viscous friction characteristics, and the Sigmoid function is used to represent the transition between motion states. An identification method is used to quickly identify the dynamic parameters of the robot. The joint position/speed command of the robot’s inner joint servo loop is dynamically generated based on the user-designed adaptive control law. In addition, the zero-moment lead-through teaching scheme based on the dynamic model is applied to a spray-painting robot with closed control system. In order to verify our method, CMA GR630ST is used to conduct experiments. We identified the parameters of the dynamic model and carried out the zero-moment lead-through teaching experiment to track the target trajectory. The results show that the proposed method can realize the application of modern control methods in industrial robot with closed control systems, and achieve a preliminary exploration to improve the application scenarios of spray-painting robots.

Design of Full-Order State Observer for Two-Mass Joint Servo System Based on the Fixed Gain Filter

This article mainly designs a novel full-order state observer for the two-mass elastic servo system. In order to observe all the states of the two-mass system without the aid of any additional sensors, the model of the observer is constructed that includes two relative parts. Based on the theory of steady-state Kalman filter (KF), the fixed gain filter (FGF) scheme is studied. To overcome the heavy computational processing burden from the KF, the mechanism of the only one adjustable parameter is studied for the FGF-based observer. The adjustable parameter can be further refined by stability analysis and control characteristics within a small range, and the exact value can be calculated according to the desired observation performance, by compromising both the noise sensitivity and tracking capability. The proposed full-order observer method is experimentally verified in a two-mass system to provide easy parameter tuning, decreased computational complexity, and flexible observation performance in all cases.

Electromechanical coupling modeling and motor current signature analysis of bolt loosening of industrial robot joint

Since loosening of the bolt connection reduce the stability and working accuracy of industrial robot joint, developing and applying new detection methods to provide effective and reliable diagnosis is still a challenging task. In this study, a detection method for bolt loosening of industrial robot joint based on electromechanical modeling and motor current signature analysis (MCSA) is proposed. Firstly, a dynamics model is established based on the electromechanical coupling characteristics of the robot joint servo system, and the bolt loosening factor in the model is equivalent to the variations of support stiffness. The vibration performance of the system due to bolt loosening is analyzed, and the dynamical equations show the coupling relationship between the motor current and bolt loosening. Then according to the traits of motor current variation, this study proposes to utilize the time–frequency features of the motor current to detect loosening. The energy concentrated time–frequency representation (TFR) is obtained by the synchrosqueezing transform (SST) method, and then time–frequency ridges are extracted. The features of the time–frequency ridges are adopted as indicators of the bolt loosening. The support vector machine (SVM) classifier is utilized to identify the loosening of bolts. The simulated motor current signal analysis shows that the SST can highlight the current transients caused by bolt loosening. The bolt loosening experiment is conducted on the single-degree-of-freedom servo joint test bench, and the results prove the effectiveness of the proposed method.

Adaptive sliding mode robust control of manipulator driven by tendon-sheath based on HJI theory

The load side and the motor connected by flexible joints in the manipulators’ joint servo system. During the motion of manipulators driven by tendon-sheath, the status change of the end-effector will result in the change of the load side rotational inertia. The perturbation of the inertia of the load side will result in the modeling mismatch of the servo system. So the modeling uncertainty and the system robustness will decrease. An adaptive sliding mode robust control based on HJI (Hamilton-Jacobi-Issacs) theory is proposed in this paper to improve the robustness of the system. Firstly, according to D-H coordinate method, kinematics and dynamics models of the manipulator are established. Then, the basic strategy of adaptive sliding mode robust control is proposed. The variation of control parameters of a single joint of the manipulator is adjusted to reduce the control cost. Next, the sliding mode control law was established through the design of the Lyapunov function based on the HJI theory. The manipulator dynamics model was taken as the research object. The simulation analysis was conducted in uncertain parameters. Finally, a series of manipulator prototype experiments were carried out to proof our control theory. The experiment results show that our method can better solve the model uncertainty caused by the servo system. The adaptive sliding mode robust control strategy based on HJI theory has lower dependence on accurately modeling and stronger robustness.

Modeling and control strategy of flexible joint servo system in humanoid manipulator driven by tendon-sheath

Modeling and control strategy of flexible joint servo system in humanoid manipulator driven by tendon-sheath

Industrial Robot Trajectory Tracking Control Using Multi-Layer Neural Networks Trained by Iterative Learning Control

Fast and precise robot motion is needed in many industrial applications. Most industrial robot motion controllers allow externally commanded motion profiles, but the trajectory tracking performance is affected by the robot dynamics and joint servo controllers, to which users have no direct access and about which they have little information. The performance is further compromised by time delays in transmitting the external command as a setpoint to the inner control loop. This paper presents an approach for combining neural networks and iterative learning controls to improve the trajectory tracking performance for a multi-axis articulated industrial robot. For a given desired trajectory, the external command is iteratively refined using a high-fidelity dynamical simulator to compensate for the robot inner-loop dynamics. These desired trajectories and the corresponding refined input trajectories are then used to train multi-layer neural networks to emulate the dynamical inverse of the nonlinear inner-loop dynamics. We show that with a sufficiently rich training set, the trained neural networks generalize well to trajectories beyond the training set as tested in the simulator. In applying the trained neural networks to a physical robot, the tracking performance still improves but not as much as in the simulator. We show that transfer learning effectively bridges the gap between simulation and the physical robot. Finally, we test the trained neural networks on other robot models in simulation and demonstrate the possibility of a general purpose network. Development and evaluation of this methodology are based on the ABB IRB6640-180 industrial robot and ABB RobotStudio software packages.

Modeling, Fabrication &amp; Control of an Articulated Robotic Arm

Modeling and Fabrication of robotic systems and their control for pick &amp;place and maintenance tasks is highly complex activity involving coordination of various sub-systems. The entire design has four important modules: (i) CAD Modeling (ii) Control System Design (iii) Machine Vision and Image Processing, (iv) Hardware Development and Testing. The five- axis articulated manipulator equipped with a vision camera in eye-to-hand configuration is designed for performing the pick and place operations of the defected tiles in a systematic manner. Dynamics of manipulator is required for design of model-based controllers. Interactive programs are developed in Matlab for kinematics and dynamics. Three-dimensional manipulator assembly configuration is modeled in Pro-E software. Motion analysis is conducted in Arduino software in order to compare the results obtained from the classical kinematics. The test set-up is developed using vision camera and microcontroller platform to guide the robot joint servos so as to perform defected object replacement activity. Presences of the coordinate of the region are indicated with the use of image-processing operations.

Robotic Deep Rolling With Iterative Learning Motion and Force Control

Large industrial robots offer an attractive option for deep rolling in terms of cost and flexibility. These robots are typically designed for fast and precise motion, but may be commanded to perform force control by adjusting the position setpoint based on the measurements from a wrist-mounted force/torque sensor. Contact force during deep rolling may be as high as 2000 N. The force control performance is affected by robot dynamics, robot joint servo controllers, and motion-induced inertial force. In this letter, we compare three deep rolling force control strategies: position-based rolling with open-loop force control, impedance control, and gradient-based iterative learning control (ILC). Open loop force control is easy to implement but does not correct for any force deviation. Impedance control uses force feedback, but does not track well non-constant force profiles. The ILC augments the impedance control by updating the commanded motion and force profiles based on the motion and force error trajectories in the previous iteration. The update is based on the gradient of the motion and force trajectories with respect to the commanded motion and force. We show that this gradient may be generated experimentally without the need of an explicit model. This is possible because the mapping from the commanded joint motion to the actual joint motion is nearly identical for all joints in industrial robots. We have evaluated the approach on the physical testbed using an ABB robot and demonstrated the convergence of the ILC scheme. The final ILC tracking performance of a trapezoidal force profile improves by over 70% in terms of the RMS error compared with the impedance controller.

High torque realization of the stepping over gait for a humanoid robot

Purpose This paper aims to propose a pulsing type joint servo driver-based obstacle surmounting method for a humanoid robot according to the whole-body dynamics model, which fully takes into account the relationship between the whole-body stability margin and instantaneous torque. Design/methodology/approach First, the authors designed a new practical instantaneous large torque strategy for a pulsing type joint servo driver by modeling the whole-body dynamics of the humanoid robot. The work also considered joint angle planning based on the dynamic model for crossing obstacles. Second, in the simulation and experimentation, the instantaneous torque of the driver is used to realize successful crossing of obstacles by the humanoid robot. This verifies the correctness of the whole-body dynamics model and the feasibility of the method for crossing obstacles. Findings The experimental data and results are described and analyzed, showing that the proposed method is feasible and effective through simulation and implementation. Originality/value The main contribution is the humanoid robot’s actuation control technology and humanoid action realization, which could be used for squatting and moving heavy objects to help a humanoid robot adapt effectively.

Research on four axis manipulator trajectory tracking Based on RBF Neural Network Algorithm

1. According to the characteristics of strong coupling tracking and highly nonlinear of four axis stamping robot, this paper based on neural network control theory proposes a manipulator trajectory tracking method based on RBF neural network. The algorithm is that the neural network as a mechanical arm joint servo controller realizes the fast tracking of mechanical arm movement posture. The simulation results show that this algorithm can improve the effectiveness and accuracy of mechanical arm trajectory tracking.

Research of Absolute Joint Position Measurement for Robot Based on DSP

Absolute position measurement method for robot whose joint servo system consist of motor and servo driver is proposed in this paper. A motion controller based on DSP (TMS320F1812) receives serial data of absolute position in initial phase and gets incremental position through QEP module embedded in DSP in running phase. Then, the absolute position is calculated in real time. A new motor rotation determination method instead of reading pulse counting register direction flag bit is presented to overcome variation of direction flag bit when motor keeps in a fixed position. Hardware and software design schemes of motion controller are described in detail. Finally, an experiment has conducted to verify the absolute position measurement method for robot.

Force-free control for the flexible-joint robot in human-robot interaction

The force-free control means that the robot arm does not seem to be affected by gravity, frictions, and inertial force during the interaction with human. An advanced force-free control method can greatly improve work efficiency. In this paper, a novel force-free control method of the flexible-joint robot is proposed. First, the mathematical models of flexible joint and flexible-joint robot are established, and the force-free controller which can realize the gravity-free situation and reduce the frictions and inertial torques is designed based on the models. Then, the dynamic parameters of the robot arm are obtained by means of a self-measuring way. Finally, a flexible-joint robot experimental system is assembled, and the verification of force-free control method is carried out. Moreover, the method converts external force into joint velocities in the joint servo controllers to improve the stability of the movement.

The impulse excitation joint servo drive design and adaptive backstepping control of humanoid robots

This study aims to explore the humanoid robot joint servo drive integration design and adaptive backstepping control. To make the humanoid robot have explosive power as the human does, simply increasing the power output of the motor of a lightweight design cannot meet the demand of moving heavy objects and so on. Moreover, the backstepping control algorithm is designed to implement the dual-arm cooperative control. The joint servo drive is redesigned in the present study, which can drive the motor at a limitation state when needed output high-voltage pulse can stimulate the motor so that the motor can produce an instantaneous large torque. A miniature design scheme is presented in this study for the servo drive, explaining the design method of each part module. The experimental data illustrate that the servo drive can produce an output torque greater than the rate of the high-voltage pulse that stimulates the motor. Knowledge of the control of humanoid robot moving a heavy object has important practical significance. The present study provides a complete actual problem and exhibits a real practical use case which can be used to speed up the explosive humanoid robot arms.

Simple Physically Parameterized Observer for Vibration Suppression Control of SCARA Robot with Elastic Joints

This paper presents a practical solution for vibration suppression control of a SCARA robot with elastic joints, utilizing motor-side measurements only. We previously proposed a torsion-angular velocity feedback (TVFB) scheme for vibration suppression control. The scheme utilizes an uncomplicated nonlinear observer based on a physically parameterized dynamic model of the elastic-joint robot arm with harmonic-drive (HD) gears. The TVFB can be easily plugged into existing joint servos such as PI velocity controllers. In this paper, the TVFB scheme is applied to the SCARA robot that has a complex structure composed of rotary-vector (RV) gears, timing belts, and an elastic prismatic joint. Experiments are conducted to validate that the TVFB scheme also has the capability to suppress vibration of the tip of the elastic prismatic joint with a payload, utilizing a simple two-link two-inertia model in the nonlinear observer.

Gait and trajectory rolling planning and control of hexapod robots for disaster rescue applications

Hexapod robots have stronger adaptability to dynamic unknown environments than wheeled or trucked ones due to their flexibility. In this paper, a novel control strategy based on rolling gait and trajectory planning, which enables hexapod robots to walk through dynamic environments, is proposed. The core point of this control strategy is to constantly change gait and trajectory according to different environments and tasks as well as stability state of robot. We established a gait library where different kinds of gaits are included. Zero moment point, which indicates the stability of robot, is estimated by a Kalman filter. According to this control strategy, a hierarchical control architecture consisting of a man–machine interface, a vision system, a gait and trajectory planner, a joint motion calculator, a joint servo controller, a compliance controller and a stability observer is presented. The control architecture is applied on a hexapod robot engaging in disaster rescue. Simulation and experimental results show the effectiveness of our control strategy.

Supernumerary Robotic Limbs for Human Body Support

A robot attached to a human body can support the human when performing tasks in dangerous environments or when taking postures that are fatiguing and uncomfortable. This paper presents a new type of supernumerary robotic limbs (SRL) that supports the human body against floors, walls, and surrounding structures so that the human can perform a task safely, comfortably, and stably. First, the use of wearable robots for securing and supporting a human body is discussed, followed by an SRL design concept. The SRL is worn around the waist and can brace the human body by making contact with a wall, grasping a rail, or being anchored to the floor. Quasi-static stability and compliance with which the body is supported are analyzed. Two control methods for stabilizing the body support system are considered: one is null-space stabilization using Hessian matrices, and the other is joint servo stiffness, based on the Jacobian. A prototype robot is designed and tested. Potential applications of the SRL in diverse fields are discussed.