Nonparametric control algorithms for a pneumatic artificial muscle

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.

Hydraulic power systems have greater flexibility and can produce more power than mechanical and electrical systems of equal size. The aim of this paper is to describe results derived from an experimental study on a power hydraulic testing machine with hybrid force and position control. The paper includes the description and fabrication of this novel testing system, named electro-hydraulic load simulator (EHLS), for conducting a performance and stability test in a bench system where force or position control is important. In order to improve the control performance of the loading system and to eliminate or reduce noise, a parallel force and position control strategy using the proportional integral derivative (PID) control method, an online self-tuning fuzzy-neural mechanism, and system identification techniques are also presented in this paper. Experiments are carried out to evaluate the effectiveness of the proposed parallel force and position control method applied to the EHLS system. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

There are many tasks which require robotic manipulators interaction with environment. It consists of three control problems, i.e., position control, impact control and force control. The position control means the way of reaching to the environment. The moment of touching to the environment yields the impact control problem and the force control is to maintain the desired force trajectory after the impact with the environment. These three control problems occur in sequence, so each control algorithm can be developed independently. Especially for redundant manipulators, each of these three control problems has been important independent research topic. For example, joint torque minimization and impulse minimization are typical techniques for such control problems. The three control problems are considered as a single task in this paper. The position control strategy is developed to improve the performance of the task, i.e., minimization of the individual joint torques and impulse. Therefore, initial conditions of the impact control problem are optimized at the previous position control algorithm. Such a control strategy yields improved result of the impact control. Similarly, the initial conditions for the force control problem are indirectly optimized by the previous position control and impact control strategies. The force control algorithm uses the individual joint torque minimization concept. It also minimizes the force disturbances. The simulation results show the proposed control strategy works well.

Haptic cues delivered via wearable devices have great potential to enhance a user's experience by transmitting task information and touch sensations in domains such as virtual reality, teleoperation, and prosthetics. Much is still unknown on how haptic perception, and consequently optimal haptic cue design, varies between individuals. In this work we present three contributions. First, we propose a new metric, the Allowable Stimulus Range (ASR), as a way to capture subject-specific magnitudes for a given cue, using the method of adjustments and the staircase method. Second, we present a modular, grounded, 2-DOF, haptic testbed designed to conduct psychophysical experiments in multiple control schemes and with rapidly-interchangeable haptic interfaces. Third, we demonstrate an application of the testbed and our ASR metric, together with just noticeable differences (JND) measurements, to compare perception of haptic cues delivered via position or force control schemes. Our findings show that users demonstrate higher perceptual resolution in the position-control case, though survey results suggest that force-controlled haptic cues are more comfortable. The results of this work outline a framework to define perceptible and comfortable cue magnitudes for an individual, providing the groundwork to understand haptic variability, and compare the effectiveness of different types of haptic cues.

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.

A self-organizing fuzzy controller to augment a sliding-mode control (SOFSMC) scheme for a class of nonlinear systems is proposed. The motivation behind this scheme is to combine the best features of self-organizing fuzzy control and sliding-mode control to achieve rapid and accurate tracking control of a class of nonlinear systems. The chatter encountered by most sliding-mode control schemes is greatly alleviated without sacrificing invariant properties. A stability analysis is presented; the design guidelines and the class of applicable systems are clearly identified. To verify the scheme, the authors performed experiments on its implementation in a magnetic levitation system. The results show that both alleviation of chatter and robust performance are achieved; the advantages of the scheme are indicated in comparison with the conventional sliding-mode design. >

This paper presents a self-organizing fuzzy logic control scheme based on neural networks, which consists of a traditional fuzzy logic (FL) controller and a conventional derivative (D) controller. Since membership functions regarding change-in-error ė represent the feedback of velocity they strongly affect transient behaviors of a system. In the proposed scheme, therefore, such membership functions are parameterized by the use of the cubic splines. Then, neural networks are adopted to optimize them in self-organizing process. To demonstrate the effectiveness of the proposed method, we report a number of simulation results involving both step and tracking control of a nonlinear plant.

As opposed to traditional pneumatic linear actuators, muscle and rotational actuators are newly developed actuators in rotational and specified applications. In the current paper, these actuators are used to set up two-dimensional pneumatic arms, which are used mainly to simulate the excavator's motion. Fuzzy control algorithms are typically applied in pneumatic control systems owing to their non-linearities and ill-defined mathematical model. The self-organizing fuzzy controller, which includes a self-learning mechanism to modify fuzzy rules, is applied in these two-dimensional pneumatic arm control systems. Via a variety of trajectory tracking experiments, the present paper provides comparisons of system characteristics and control performances.

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>

Constrained motion of a planar rigid-flexible manipulator is considered in this study. a dynamic model with zero tip deformation constraint of constrained rigid-flexible 608

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.

Deep learning approaches for force feedback based void defect detection in friction stir welding

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.

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.

Position control and vibration control of the underactuated flexible robot in operational space is implemented. Firstly, the dynamic equations in operational space are derived using the assumed modes method. And kinematics and dynamics of the system are analyzed. Secondly, position control method of the underactauted flexible manipulator in the operational space is proposed. Because the elastic vibration of flexible links can not be eliminated only via position control, based on position control strategy, vibration control schemes are presented. The simulation of a 2DOF underactuated flexible manipulator indicates that position and vibration control methods have great effects on increasing end manipulation accuracy, reducing tracking errors and improving dynamic characteristics, which also verifies the validity of control strategies. Thus, for the underactuated flexible robot, both the position control and the vibration control are implemented simultaneously.