Motion control design for force-trajectory integrated control to unknown environment

Precise force control and position control is essential for many robotic applications. During unilateral or bilateral object handling remote applications, human operators apply excess forces on the actuators with the intention of better grip and it is possible to damage the handled objects. This paper proposes position control and force control techniques when human applies excess force. The controllers consist of predefined force and equilibrium position which are correspond to remote environmental object safety. The operator applied excess force is modeled as a spring force through a virtual stiffness model. The paper introduces proportional derivative position control loop to conventional virtual stiffness controller. The force control loop and the position control loop references are combined in the common dimension of acceleration to produce current reference to the actuator. The sensorless sensing techniques of disturbance observer and reaction force observer are utilized to disturbance suppression and external force estimation. In the force controller, estimated reaction force is reduced to desired value by introducing virtual force loop between reaction force observer output and reaction force feedback input. The position control is achieved by introducing a scaling factor to reaction force feedback path. The switching between force control and position control is possible with scaling factor value. The performances of proposed methods are compared with conventional method and validity of the proposed methods is verified by simulations and experiments.

In this paper, we propose an adaptive nonlinear strategy for the motion and force control of manipulators with flexible joints. Our approach provides force control when in contact and robust motion control in its absence, all without the need for a control switch. This self-tuning behaviour for mixed contact/non-contact scenarios results from a unified formulation of force and motion control, with an integral transpose-based inverse kinematics core and adaptive update laws to cope with the manipulator flexibility and the contact stiffnesses. The global boundedness of all signals and the asymptotic stability of this controller are guaranteed via Lyapunov analysis. Finally, we validate its applicability experimentally by using low-cost hardware in a realistic mixed-contact scenario, demonstrating low computational demand.

Automatic cell injection has been the focus of many researches and commercial development for several years. In this paper, a robotic cell injection system for automatic batch injection of suspended cells is developed. To facilitate the process, these suspended cells are held and fixed to a cell array by a specially designed cell holding device, and injected one by one through an “out-of-plane” cell injection process. A micropipette equipped with a PVDF micro force sensor is integrated in the proposed system. The force sensor is utilized to measure real time injection force applied to the cells during injection process. Through calibration of the relationship between the cell injection force and the desired injector pipette trajectory, a position (vision) and force control algorithm is proposed and applied to the motion control of the injection pipette in three-coordinate directions during an injection process. The out-of-plane cell injection task is decoupled into a position control in X-Y horizontal plane and an impedance force control in Z-axis. The depth motion of the injector pipette, a common problem of three-dimensional micromanipulation, is indirectly controlled by the force control. Finally, experimental results are given to demonstrate the effectiveness of the proposed approach.

In this paper, a new viewpoint of H X control in frequency domain is presented. From this viewpoint, the robust performance problem is reconsidered. A numerical example is given to show the efficiency of the result.

The best exoskeleton control strategy depends on the task, motivating the development and analysis of an exoskeleton capable of position, force, and impedance control. In this paper, we implement and compare the three controller types via sliding mode control on a custom-built pneumatic cylinder ankle exoskeleton. To evaluate each controller's performance, the exoskeleton was tested on the benchtop and with human subject experiments. With the position controller, the exoskeleton achieved an root-mean-square error (RMSE) of under 5 deg for both the benchtop and human tests. It had a bandwidth of approximately 12 rad/s. The force controller tracked sinusoidal trajectories acceptably well at low frequencies (15% of force range at 6 rad/s), with a bandwidth of approximately 24 rad/s. The error was significantly higher (RMSE of 24% of force range) for the more biologically relevant trajectory. The impedance controller demonstrated the desired spring-like behavior, with position RMSE generally under 5 deg compared to expected position. All three controllers worked equally well for benchtop and human tests. Thus, a pneumatically powered ankle exoskeleton with sliding mode control is capable of accurate position and impedance control and is capable of marginally acceptable force control.

Most of the commercially available motion controllers are designed for position and velocity control, but they do not support force control directly. Since force control requires high bandwidth, it is practically impossible to implement a force controller using the host system which accommodates the motion controller. This paper describes a force interface which can use a standard position controller for force control thus taking advantage of the high sampling rate of the motion controller. The interface is designed for the control of a multifingered dextrous hand.

On-line learning of robot arm impedance using neural networks

In this paper, model-based precision force and position control of an ionic polymer metal composite (IPMC) is presented. A 23.8 mm × 3.4 mm × 0.16 mm IPMC strip was used as an actuator in a cantilever configuration. Open-loop force and position responses of an IPMC are not repeatable, and hence closed-loop precision control is of critical importance to ensure proper functioning, repeat-ability and reliability. After feedback controllers were designed and implemented with empirically obtained fourth-order plant transfer functions, the overshoot decreased from 460 to 2.8 per cent and the settling time was reduced from 37.5 to 3.22 s in force control. In position control the overshoot decreased from 333 to 20.3 per cent and the settling time was reduced from 21.5 to 2.56 s. Microscale precision force and position control capabilities of the IPMC actuator were also demonstrated experimentally. An 8 μN force resolution was achieved with a force noise of 0.5μN r.m.s., and the position resolution was 6 μm with a position noise of 2.5 μm r.m.s. The maximum force and tip displacement achieved with the IPMC actuator under closed-loop control were 2 mN and 5 mm respectively. The IPMC actuator could follow various commanded force and position trajectories such as sinusoidal and trapezoidal position profiles, and a velocity profile with a 3 mm/s maximum velocity. A novel hybrid force and position control strategy demonstrated its utility in practical micromanipulalion applications where the actuator force must be limited to prevent damaging micro-objects. High-precision control of the IPMC at low force level proved its potential for micromanufacturing and micromanipulation applications such as robotic and biomedical microgrippers.

Recently, in the medical care, in order to achieve micro manipulation, many robots are researched. This paper focuses macro-micro bilateral control system which is one of the micro manipulation robots. Macro-micro bilateral control system consists of position control and force control. Therefore, in this paper, in order to achieve high accuracy macro-micro bilateral control system, high accuracy position control and force control is implemented. Firstly, the high resolution encoder is used. A low friction structure is used to force control. In addition, nominal mass is important for accurate force observation. Therefore, identification of mass is proposed. Macro-micro bilateral control system is implemented with proposed structure and identified nominal mass.

This paper proposes a novel force-sensor-less contact motion control for quick and smooth industrial robot motion. Industrial robots serve important functions in modern industrial society. However, their general application is limited because they employ only position based high-stiffness control methods. The proposed method achieves smooth contact motion for new applications of industrial robots, and it solves two of the problems of contact motion control. First, impulsive force is reduced through active braking motion control. Second, wasted motion is decreased by applying integral-proportional(I-P) force control after contact. Experimental results show the validity of the proposed method with a three-degree-of-freedom(DOF) robot. The proposed method achieves a 78.7% decrease in settling time and a 6% reduction in impulsive force. The proposed method has the potential to improve fast contact motion through a profile control application.

Two different control schemes, position model referenced control (PMRC) and force model referenced control (FMRC), are developed for a simplified two robots model with one interacting axis. The dynamic stability of the position (or force) control under the FMRC (or PMRC) is analyzed. Results indicate that PMRC, although providing better dynamic performance of the position control, may degrade the dynamic performance of the force control. However, FMRC can provide better dynamic performance of both position and force control.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

To address the demands for precision and load-bearing capacity in the installation of building panels, a hybrid force-position driven robot with redundant actuation has been developed. The mechanical performance of this robot is primarily governed by its central parallel mechanism, which is equipped with redundant actuators matching the degrees of freedom. Non-redundant and redundant actuators are respectively responsible for position and force control. The inclusion of redundant force-driven joints has increased the internal coupling within the mechanism. To enhance the coordination between position and force control, a hybrid synchronized control method based on cross-coupling has been proposed. Initially, kinematic and dynamic models of the parallel structure were established. Under predefined trajectories, the theoretical inputs for each actuator were calculated using inverse kinematics and dynamics. Subsequently, employing the principle of cross-coupling, the torque output from the position actuators was used as feedback. This feedback was processed by a synchronized coordination controller to adjust the output force of the redundant force-driven joints. By adjusting the output force of the redundant actuators, the torque burden on the position actuators was effectively reduced, thereby enhancing the precision of position control. Additionally, under the same load conditions, smaller power actuators could be utilized for position control, reducing the overall weight of the robot and improving its load-to-weight ratio. To validate the effectiveness of the proposed control strategy, a robotic simulation environment was established. The simulation results demonstrated significant reductions in the average torque required by the position actuators across three different trajectories, with reductions of 91.43%, 54.56%, and 80.6% respectively. Finally, the load-bearing capacity and the load-to-weight ratio of the prototype were assessed. Experimental results confirmed that the prototype achieved a load-to-weight ratio of 15.83%, validating the effectiveness of the hybrid synchronized control method based on cross-coupling.

Single-carrier frequency domain adaptive antenna array for uplink multi-user MIMO transmission in a cellular system

Active magnetic bearings (AMBs) have several advantages such as non-contact and active control, and are getting more applications in rotating machinery. Various control strategies have been applied and designed for this nonlinear system with complex rotor dynamics. Most control schemes are in time domain, while the control in frequency domain, which is also essential for stability, is rarely considered. In this paper, a time-frequency domain control approach is proposed for AMB-rotor system. The control scheme is implemented using wavelet theory and deep learning theory. The controller consists of 2 main parts: a filter bank for discrete wavelet transform (DWT) to obtain time-frequency signal, and a deep neural network (DNN) for nonlinear adaptive control. A 4-DOF AMB-rotor system is analyzed and its model is established. The rotor dynamics are simulated and the results are compared. Simulation results demonstrate that the proposed approach has an obvious control effect in improving precision in time domain and stability in frequency domain. This research provides a new adaptive control approach for AMBs, and this approach can also be adopted in other multi-dimension vibration control, especially in multi-frequency applications.

Two strategies of position and force control for two industrial robots handling a single object