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Manipulators are often subjected to joint flexibility caused by various causes in industrial applications, such as shaft windup, harmonic drives and bearing deformation. However, many industrial robots are only equipped with motor-side encoders because link-side encoders and torque transducers are expensive. Because of joint flexibility and resulted slow response rate, control performance of these manipulators is very limited. Based on this, the purpose of this paper is to use easy-to-install and cheap accelerometers to improve control performance of such manipulators.

First, a novel tip-acceleration feedback method is proposed to avoid amplifications of approximation errors caused by inversion of the Jacobian matrix. Then, a new control scheme, consisting an artificial neural network, a proportional-derivative (PD) controller and a reference model, is proposed to track motor-side position and suppress link-side vibration.

By using the proposed tip-acceleration feedback method, each link’s vibration can be suppressed correlatively. Through the networks, smaller motor-side tracking errors can be obtained and unknown dynamics can be compensated. Tracking and convergence performance of the network-based system can be improved by using the additional PD controller.

The originality is based on using accelerometers to improve link-side vibration suppression and control performance of flexible-joint manipulators. The previously used methods need expensive link-side sensors or accurate robot model, which is unavailable for many industrial robots only equipped with motor-side encoders. The report proposed a novel acceleration feedback method and used networks to solve such problems.

The purpose of this paper is to study the preload range of tendon-driven manipulator and the relationship between preload and damping. The flexible joint manipulator (FJM) with joint flexibility is safer than traditional rigid manipulators. A FJM having an elastic tendon is called an elastic tendon-driven manipulator (ETDM) and has the advantages of being driven by a cable and having a more flexible joint. However, the elastic tendon introduces greater residual vibration, which makes the control of the manipulator more difficult. Accurate dynamic modeling is effective in solving this problem.

The present paper derives the relationship between the preload of the ETDM and the friction moment through the analysis of the forces of cables and pulleys. A dynamic model dominated by Coulomb damping is established.

The linear relationship between a decrease in the damping moment of the system and an increase in the ETDM preload is verified by mechanics analysis and experiment, and a curve of the relationship is obtained. This study provides a reference for the selection of ETDM preload.

The method to identify ETDM damping by vibration attenuation experiments is proposed, which is helpful to obtain a more accurate dynamic model of the system and to achieve accurate control and residual vibration suppression of ETDM.

The purpose of this paper is to present a new method to establish a kinematic model for a continuum manipulator, whose end can be controlled to move in a three-dimensional workspace. A continuum manipulator has significant advantages over traditional, rigid manipulators in many applications because of its ability to conform to the environment. Moreover, because of its excellent flexibility, light weight, low energy consumption, low production cost, it has a number of potential applications in areas of earthquake relief, agricultural harvesting, medical facilities and space exploration.

This paper uses basic theory of material mechanics to deduct motion equations of the manipulator. Unlike other published papers, the manipulator is not based on segments tactics, but regarded as an integrated flexible system, which simplifies its kinematics modelling and motion controlling. The workspace of the manipulator is analysed by theoretical deducing and simulation modelling. For verification of the presented theory, simulation based on ADAMS software was implemented, while a prototype of the manipulator was developed. Both the software simulation and prototype experiment show that the theoretical analysis in this paper is reasonable. The manipulator can move accurately along the desired trajectories.

This paper developed a novel and fully continuous manipulator driven by steel wires. A kinematic model of the manipulator was established. The physical manipulator developed for verifying the kinematic model can effectively track the prescribed trajectory. The presented kinematic model agrees with not only the simulation but also with the experiment.

The manipulator presented in this paper is constructed by steel wires. It possesses the advantages of structural continuity, high flexibility and low production cost. It can be extensively used in many fields, such as search and rescue robotic systems. The limitation of this research is that the dynamic model of the manipulator is not yet clear, which is one of the directions for future research.

The manipulator breaks through the limitation of the joint-type or flexible-link-type manipulator, which can also be extensively used in many fields such as search and rescue robotic systems.

The manipulator developed in this paper, currently, is a prototype under the project of “Automatic Picking Manipulator Research”. It possesses a good market value.

The value of this research is that the manipulator breaks through the limitation of the joint-type or flexible-link-type manipulator and establishes the kinematic model for a fully continuous manipulator by a simple strategy. This is the first study that uses such a strategy for establishing the motion equations of a monolithic continuum manipulator.

This paper aims to design an event-triggered adaptive prescribed performance controller for flexible manipulators, with the primary objectives of achieving output performance constraints and addressing communication resource limitations.

The authors propose a novel prescribed performance barrier Lyapunov function (PP-BLF) that considers both output and tracking performance constraints. The PP-BLF ensures that the system's output, transient behavior and steady-state performance, adhere to prescribed constraints. The boundary of the PP-BLF is established by an exponential function that decays over time. Notably, the PP-BLF can be applied seamlessly in unconstrained cases without necessitating controller redesign. Moreover, the controller design incorporates an event-triggered mechanism, effectively reducing the frequency of controller updates and optimizing the utilization of communication resources. Additionally, the authors employ adaptive techniques to estimate the system's unknown parameters and approximate unknown nonlinear functions using radial basis function neural networks (RBFNN). To address the challenge of “complexity explosion”, dynamic surface technology is employed.

Numerical simulations are conducted under five different cases to verify the effectiveness of the proposed controller. The results demonstrate that the controller successfully constrains the output tracking error within the prescribed performance boundary. Moreover, compared with the traditional time-triggered mechanism, the event-triggered mechanism significantly reduces the controller's update frequency, resolving the problem of limited communication resources.

The paper reduces the update frequency of control signals and improves resource utilization through an event-triggered mechanism in the form of relative thresholds. The authors recognize that the event-triggered mechanism may impact the output performance of the system. To address this challenge, the authors propose a prescribed performance Barrier Lyapunov Function (PP-BLF). The PP-BLF is designed to effectively constrain the output performance of the system, ensuring satisfactory control even when the control signal updates are reduced.

This paper aims to present the optimal design procedure of a symmetrical 2-DOF parallel planar robot with flexible joints by considering several performance criteria based on the workspace size, dynamic dexterity and energy of the control.

Consequently, the optimal design consists in determining the dimensional parameters to maximize the size of the workspace, maximize the dynamic dexterity and minimize the energy of the control action. The design criteria are derived from the kinematics, dynamics, elastodynamics and the position control law of the robot. The analysis of the design criteria is performed by means of the design space and atlases.

Finally, the multi-objective design optimization derived from the optimal design procedure is solved by using multi-objective genetic algorithms, and the results are analyzed to assess the validity of the proposed approach.

An alternative approach to the design of a planar parallel robot with flexible joints that permits determining the structural parameters by considering kinematic, dynamic and control operational performance.

The purpose of this paper is to study the dynamic modeling and controller design for the series element actuator (SEA) joints. The robot equipped with SEA joints is a strong coupling, nonlinear, highly flexible system, which can prevent itself from damaging by the accidental impact and the people to be injured by the robot.

Based on the torque source model, the authors built a dynamic model for the SEA joint. To improve the accuracy of this model, the authors designed an elastic element into the joint and implemented the vector control for the joint motor. A control method of combined PD controller and back-stepping was proposed. Moreover, the torque control could be transformed into position control by stiffness transformation.

The established model and the proposed method are verified by the position and torque control experiments. The experimental results show that the dynamic model of the SEA joint is accurate and the proposed control strategies for the SEA joint are reasonable and feasible.

The main contribution of the paper is as follows: designing an elastic element with high linearity to improve the model accuracy of the SEA joint. The control strategy-based back-stepping method for the SEA joint is proposed to increase the robustness of the controller.

This paper aims to propose a novel system identification and resonance suppression strategy for motor-driven system with high-order flexible manipulator.

In this paper, first, a unified mathematical model is proposed to describe both the flexible joints and the flexible link system. Then to suppress the resonance brought by the system flexibility, a model based high-order notch filter controller is proposed. To get the true value of the parameters of the high-order flexible manipulator system, a fuzzy-Kalman filter-based two-step system identification algorithm is proposed.

Compared to the traditional system identification algorithm, the proposed two-step system identification algorithm can accurately identify the unknown parameters of the high order flexible manipulator system with high dynamic response. The performance of the two-step system identification algorithm and the model-based high-order notch filter is verified via simulation and experimental results.

The proposed system identification method can identify the system parameters with both high accuracy and high dynamic response. With the proposed system identification and model-based controller, the positioning accuracy of the flexible manipulator can be greatly improved.

The purpose of this paper is to study the controller design of flexible manipulator. Flexible manipulator system is a nonlinear, strong coupling, time-varying system, which is introduced elastodynamics in the study and complicated to control. However, due to the flexible manipulator, system has a significant advantage in response speed, control accuracy and load weight ratio to attract a lot of researchers.

Since the order of flexible manipulator system is high, designing controller process will be complex, and have a large amount of calculation, but this paper will use the dynamic surface control method to solve this problem.

Dynamic surface control method as a controller design method which can effectively solve the problem with the system contains nonlinear and reduced design complexity.

The authors assume that the dynamic parameters of flexible manipulator system are unknown, and use Radial Basis Function neural network to approach the unknown system, combined with the dynamic surface control method to design the controller.

The aim of this paper is to prove that the manipulator is able to contact the environment compliantly, and reduce the instantaneous collision impact.

Cartesian impedance control law is introduced to interrelate the external force with the Cartesian position.

When the estimated external force sensor feedback is the input of the on‐line trajectory regeneration, a novel online motion plan could be performed in a task‐consistent manner keeping the interaction force within the acceptable tolerance. The proposed approach also proves that the manipulator is able to contact the environment compliantly, and reduce the instantaneous collision impact. The virtual decomposition control, simplifying the Cartesian impedance control application of the manipulator and guaranteeing the asymptotical stability of the entire system, is implemented to actualize the approach. Furthermore, adaptive dynamics joint controller is extended to all the joints for complementing the biggish friction.

With the proposed adaptive Cartesian impedance control and the online path planner, the robot will be manipulation‐friendly in an unstructured environment.

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.