Friction Compensation Method Research Articles

An Operator Based Modeling and Compensation of VCM Actuator Pivot Friction in a 1.8-inch HDD

The pivot friction of voice-coil-motor (VCM) actuator is measured for a 1.8-inch small disk drive with disk rotating and slider flying. The measurement is carried out under the conditions that the actuator is controlled and the head movement amplitude is growing by changing the references. The hysteresis of friction versus head position is then obtained. An operator based modeling approach is adopted for the hysteresis, and an optimal model is obtained by minimizing the energy gain between the head position and the modeling error. It is also found that the frequency response of the actuator model with the inclusion of the hyteresis model matches well with the measured frequency response of the actuator. A friction compensation method based on the nonlinear hysteresis model is then proposed. The simulation and implementation results demonstrate a significant improvement in disturbance rejection in low frequency range.

Modeling, Identification, and Compensation of Stick-Slip Friction

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The paper presents a novel approach for stick-slip friction modeling. The adaptive friction compensator, which uses this modified model guarantees the convergence of the tracking error to a small residual set and at the same time the algorithm can easily be implemented on standard industrial controller architectures. The model clearly distinguishes the low and the high-velocity regimes. Accordingly, at low velocities the adaptive laws in the friction compensator tune only the parameters which characterizes the low-speed friction behavior (Striebeck friction) and at the high-speed regime the adaptive laws modify only the parameters which characterize the high-speed friction behavior (Coulomb and viscous friction terms). An off-line identification method for the friction model parameters is also presented. Experimental results are provided to show the performances of the proposed friction modeling and compensation method. </para>

Friction compensation in hybrid force/velocity control of industrial manipulators

This paper deals with the implementation of a hybrid force/velocity controller for the automatic edge following of two-dimensional unknown planar contours performed by an industrial robot manipulator. In particular, the authors address the problem of compensating the joint friction effects that have to be taken into account in the controller design in order to achieve a reasonable performance with regards to normal force and tangential velocity errors. For that reason, two model-based friction-compensation methods are compared: a static method, based on a previously identified model, and an adaptive method, where joint friction parameters are recursively updated. By means of an extensive experimental activity, it is shown that, in spite of its simplicity and despite the friction effects changing in time during the robot operations, the devised adaptive procedure obtains a high performance in different operating conditions.

非共振型超音波アクチュエータ駆動精密ステージの位置決め制御における摩擦補償法

非共振型超音波アクチュエータ駆動精密ステージの位置決め制御における摩擦補償法

Robustness evaluation of three friction compensation methods for point-to-point (PTP) positioning systems

Friction is one of the major contributing factors to problems associated with accuracy in positioning systems. The positioning accuracy problem becomes more complicated because of variations in the friction. In this paper, three simple friction compensation methods for the point-to-point (PTP) positioning system, which are easily applied in practical applications, are compared and evaluated experimentally on an experimental rotary positioning system. The first controller is the nominal characteristic trajectory following (NCTF) controller and the other two are the PD controller with a discontinuous non-linear proportional feedback (DNPF) compensator and the smooth robust non-linear feedback (SRNF) compensator. All of the controllers are compared in terms of the effectiveness of the controller to compensate for the friction as well as robustness against inertia and friction variations. The results demonstrate that the NCTF controller is more robust against friction variation than the PD controller with the DNPF or SRNF compensator.

Neuro-Adaptive Friction Compensation for Single-Link Flexible Robots Using Serial-Gray-Box Modeling Strategy

In this paper a previously offered black-box filtered-error neural-approximation-based control method for singularly perturbed flexible-link arms (FLA) is extended to a serial-gray-box method that assumes only the friction torques as unknown functions. Unlike the former method the knowledge of the unknown part is not used in design implementation of the fast control component. Because the neural network weights are updated adaptively the gray-box friction compensation method is applicable even when the friction functions change with time. Moreover, due to incorporation of the available first-principles knowledge into the control law the method exhibits dimensional extrapolation property with respect to nonfrictional measurable parameters of the plant. The capability of the gray-box method in the presence of static friction unmodeled dynamics are examined. Simulation results show that the proposed gray-box-based method provides better control modeling performances with less number of integrators in comparison with the black-box-based method. A procedure for determination of the parameters of the distributed mass-spring model is offered closed-form exact solutions for the equivalent deflection angle the spring coefficient the slope of the flexible-mode friction characteristic are derived. The gray-box method also works better than a newly developed Lyapunov-type controller which can be regarded as a robust control schema.

COMPENSATION OF FRICTION IN ROBOTIC ARMS AND SLIDE TABLES

The paper presents experimental results of friction parameter identification for two different systems: rotational arms of a direct-drive spherical manipulator and linear slide tables. Parameters of the static part of the LuGre friction model are estimated. Several experiments are reported in which selected friction compensation methods are employed for tracking at low velocities. Two compensators working in real time are constructed and verified: the PD-like lead, to avoid stick-slip motion and the on-line trained neural network with a special structure, to avoid errors caused by friction and varying dynamics of robotic actuators.

Nonlinear Friction Compensation Design for Suppressing Stick Slip Oscillations in Oil Well Drillstrings

Friction appears in all mechanical systems and has a significant impact on control. This paper presents simple but effective non linear friction compensation method for a drillstring system, by considering the stick-slip motion of the bit on the bottom hole assembly (BHA) in oil wells. Due to nonlinear problem at near-zero velocity where the torque exerted on bit is a function of the bit speed, the drillstring controlling is not an easy task. The control strategy proposed in this work involves a combination of a feedback model based compensation of friction and linear controller which enables to reduce the stick slip oscillations. The effectiveness of this approach is demonstrated through the resultants simulations

Precise slow motion control of a direct-drive robot arm with velocity estimation and friction compensation

Precise low speed motion control of a robot manipulator calls for precise position and velocity measurement and joint friction compensation, as well as robustness and adaptability of the control scheme. However, precise velocity measurement and friction compensation remain challenging research tasks, especially for very slow motions. In the present work, a simple and efficient method is proposed to estimate velocity from a sampled incremental encoder pulse train, which is then utilized in the experimental investigation on a proposed robust decomposition-based friction compensation method. The experimental results on a direct drive robot arm have demonstrated precise motion control at very slow speeds and in the presence of significant joint friction.

Decomposition-based friction compensation of mechanical systems

In this paper, a linear parametric friction model is formulated by linearizing a nonlinear empirical friction model in parameters. A proposed decomposition-based control design framework is applied to synthesize the friction compensation scheme. A separate compensator is designed for each type of friction utilizing the most suitable control technique. The nominal friction is compensated by feed forward. An adaptive compensator is derived to compensate for parametric unmodeled friction with unknown but constant parameters, and a robust compensator is used to deal with friction model parameter variations, as well as non-parametric unmodeled friction. The combination of the compensators yields the overall compensation scheme. Adaptive and robust compensators complement each other in compensating the effects of model uncertainties. The analytical and simulation studies have confirmed the efficiency of the proposed friction compensation method.

Adaptive friction compensation using extended Kalman–Bucy filter friction estimation

An extended Kalman–Bucy filter (EKBF)-based friction compensation method is presented and validated. The method relies on an accurate model of system rigid-body dynamics and measured motion, rather than a structured nonlinear friction model, to estimate external friction torque. The estimate is used in a traditional friction compensator to cancel friction effects. The EKBF compensator is compared with other model-based and non-model-based friction compensation strategies through position tracking experiments. Results show that when motion is dominated by static and Stribeck friction, non-model-based friction estimation and compensation using the EKBF consistently provides equal or superior performance over model-based adaptive friction compensation methods.

A nonlinear friction compensation method using adaptive control and its practical application to an in-parallel actuated 6-DOF manipulator

This paper presents a simple and effective nonlinear friction compensation method which is derived from an adaptive control strategy and its practical application to a linear actuator. The proposed adaptive friction compensation method is shown to be equivalent to the reversed integral controller that is easily applied to the conventional PID controller. The reversed integral controller reverses the sign of the integrator output as the sign of the velocity changes. It analyzes how the reversed control action can compensate for friction. The effectiveness of this approach is demonstrated by experiments on a 3-PRPS (Prismatic-Revolute-Prismatic-Spherical joints) in-parallel 6-DOF manipulator.

Robust Compensation for Dynamic Friction in Positioning Control of Hard Disk Drives

Friction in actuators of hard disk drives lowers the system gain in low frequency range, which prevents the system positioning accuracy from further improvement. The complexity and multiform of friction make it difficult to obtain a complete friction model. A nonmodel-based robust friction compensation method is introduced, in which the gain decrease in the low frequency domain is compensated by the infinite gain in a bang-bang compensator. The introduced method is simply integrated into the proximate time-optimal servomechanism controller widely used in the current hard disk drives. Simulation results based on a commercial FUJITSU hard disk are presented

A neural-network-based velocity tracking control method for direction-changing motions

The objective of this paper is to develop a velocity-tracking control method for direction-changing motions. A novel feature of the proposed method is the use of a neural network to compensate for the nonlinear effects associated with the friction. The proposed method is compared with a conventional Coulomb-friction-based compensation approach for a DC motor servo system, and is shown to produce more accurate tracking performance in dealing with direction-changing motions. Experimental results have also shown that the performance of the proposed method compares favorably with that of other recently proposed neural-network-based friction-compensation methods.

Adaptive and Robust Techniques for Friction Compensation in Motion Control of Robotic Manipulators

This paper deals with the study of friction compensation methods for motion control of robotic manipulators. First of all, modelling of the friction is carried out decomposing it into three components, Coulomb's, viscous and stiction components. Then, an adaptive model-based control law is designed which includes an adaptive compensation scheme of the modelled friction. Finally, a variable structure robust control loop is designed whose inclusion in an adaptive control scheme designed using a simplified model of the friction allows to obtain better tracking accuracy. Some results of experimental tests, carried out on a two links SCARA manipulator, are displayed with the aim to show the effectiveness of the proposed compensation methods.

Friction Compensation for Impedance Control of Pneumatic Manipulator

In this paper, a friction compensation method using a disturbance observer is proposed for an impedance control of pneumatic manipulator. It is assumed that the generated torque by a pneumatic actuator can be estimated based on the pressure signals and the discharge volume. In order to improve the dynamic characteristics of the pneumatic actuator driven by meter out method, we construct the inner torque control system by feeding back the generated torque. In order to reduce the influence of disturbances comprising friction torque and parameter variations of plant, the impedance control system is constructed with a disturbance observer which estimates the disturbances based on the generated torque of pneumatic actuator, the angular velocity and the reaction torque. From some experiments, it is confirmed that the proposed control system is effective to improve the robustness for the friction torque in the impedance control of a pneumatic manipulator.

Friction Compensation for Control of Drawing an Object by a Dual-Arm Robot Using Fuzzy-Neuro.

Manipulating an object is one of the most important tasks of robots. Numerous studies have been carried out on object manipulation algorithms and optimizing control force. When robots try to manipulate an object on some environments, in other words, when robots try to draw an object, they must take the effect of friction into account in order to control the object smoothly. In this paper, a friction compensation method is proposed for control of drawing an object using a specialized neuron which is connected to a fuzzy neural network. The specialized neuron learns the friction effect only when the object dose not move against applied force. The fuzzy neural network is used for object trajectory control. The controller consists of a main fuzzy neural network controller which includes a neuron for friction compensation for object trajectory control and sub-fuzzy neural network controllers for manipulator force control to the object. Furthermore, modified Delta-Bar-Delta learning rate adaptation method is introduced for the main neural network controller. Computer simulation was performed to evaluate these proposed methods.

Identification and Adaptive Nonlinear Control of Drives with Friction

In this contribution several approaches to nonlinear adaptive control of mechanical drives are proposed taking into account determined nonlinear actuator characteristics such as friction, hysteresis and other static nonlinearities. Improved control performance in terms of dynamics, high positioning accuracy and robustness is achieved by combining linear position control with nonlinear feed-forward and adaptive friction compensation methods. Based on a precise model of the drive dynamics recursive identification techniques are applied to obtain reliable estimates of the time varying and position dependent process parameters, the nonlinear friction characteristic in particular. As examples the nonlinear friction characteristics of robotic joint drives and pneumatic drives are determined and it is shown how the control can be improved considerably by model based nonlinear control in the presence of time varying nonlinear characteristics and hysteresis effects. Experimental results illustrate the efficiency of the developed nonlinear control schemes.

A survey of models, analysis tools and compensation methods for the control of machines with friction

While considerable progress has been made in friction compensation, this is, apparently, the first survey on the topic. In particular, it is the first to bring to the attention of the controls community the important contributions from the tribology, lubrication and physics literatures. By uniting these results with those of the controls community, a set of models and tools for friction compensation is provided which will be of value to both research and application engineers. The successful design and analysis of friction compensators depends heavily upon the quality of the friction model used, and the suitability of the analysis technique employed. Consequently, this survey first describes models of machine friction, followed by a discussion of relevant analysis techniques and concludes with a survey of friction compensation methods reported in the literature. An overview of techniques used by practising engineers and a bibliography of 280 papers is included.