Globally exponential continuous controller/observer for position tracking in robot manipulators with hysteretic joint friction

Robotica ◽  
2009 ◽  
Vol 28 (5) ◽  
pp. 759-763 ◽  
Author(s):  
Srinivasulu Malagari ◽  
Brian J. Driessen
Keyword(s):  
Robot Manipulator ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Degree Of Freedom ◽  
Position Tracking ◽  
Observer Error ◽  
Joint Friction

SUMMARYIn this work, we present a continuous observer and continuous controller for a multiple degree of freedom robot manipulator with hysteretic joint friction. The fictitious hysteresis state is of course unknown to the controller and must be estimated. The joint velocities are assumed measured here. For this considered plant, we propose and present a continuous observer/controller that estimates or observes the hysteresis state and drives the position tracking error to zero. We prove that the combined tracking error and observer error converges to zero globally exponentially.

Experimental Verification of Adaptive Dominant Type Hybrid Adaptive and Learning Controller for Trajectory Tracking of Robot Manipulators

2013 ◽  
Vol 25 (4) ◽  
pp. 737-747 ◽  
Author(s):  
Munadi ◽  
◽  
Tomohide Naniwa ◽  
Keyword(s):  
Adaptive Control ◽  
Motion Control ◽  
Trajectory Tracking ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Control Input ◽  
Dominant Type ◽  
Dynamical Parameters ◽  
Small Robot

This paper presents an experimental study to verify an adaptive dominant type hybrid adaptive and learning controller for acquiring an accurate trajectory tracking of periodic desired trajectory of robot manipulators. The proposed controller is developed based on combining the model-based adaptive control (MBAC), repetitive learning control (RLC) and proportionalderivative (PD) control in which the MBAC input becomes dominant than other inputs. Dominance of adaptive control input gives the advantage that the proposed controller could adjust the feed-forward motion control input immediately after changing the desired motion or load of the manipulator. In motion control law, the proposed controller uses only one vector to estimate the unknown dynamical parameters. It makes the proposed controller as a simpler hybrid adaptive and learning controller which does not need much computational power and also is easily be implemented for real applications of robot manipulators. The proposed controller is verified through experiments on a four-link small robot manipulator as representation of a scale robot manipulator to ensure this controller can be applied in the real applications of robot manipulators. The experimental results show the effectiveness of the proposed controller by indicating the position tracking error approaches to zero.

A new simulation scheme for self-tuning adaptive control of robot manipulators

Robotica ◽  
1991 ◽  
Vol 9 (3) ◽  
pp. 335-339 ◽  
Author(s):  
Q. Wang ◽  
D. R. Broome
Keyword(s):  
Adaptive Control ◽  
Controller Design ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Degree Of Freedom ◽  
Dynamic Equations ◽  
Real Time Control ◽  
Highly Nonlinear ◽  
Self Tuning ◽  
Simulation Scheme

SUMMARYIn most dynamic adaptive control simulation of robotic manipulators, the Langrange–Euler (L–E) dynamic equations are first piecewise linearized about the desired reference and then discretized and rewritten in a state space form. This makes things very complicated and it is easy to make errors. What is more is that with a different reference this work must be done again. A new simulation scheme – Backward Recursive Self-Tuning Adaptive (BRSTA) – as it will be called, is suggested in this paper for adaptive controller design of robot manipulators. A two degree of freedom robot manipulator is used to verify the scheme in the condition of highly nonlinear and highly coupled system. A one degree of freedom robot manipulator is used for comparing both the forward and backward methods. The main advantages of this scheme include that it can be used for evaluating the self-tuning adaptive control laws and provide the initial process parameters for real-time control. And it is concluded here that the Newton–Euler (N–E) dynamic equations are equally well qualified as the Langrange–Euler (L-E) equations for the simulation of self-tuning adaptive control of robot manipulators.

scholarly journals Trajectory Planning of Robot Manipulator Based on RBF Neural Network

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1207
Author(s):  
Qisong Song ◽  
Shaobo Li ◽  
Qiang Bai ◽  
Jing Yang ◽  
Ansi Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Polynomial Interpolation ◽  
Robot Manipulator ◽  
Rbf Neural Network ◽  
Tracking Error ◽  
Lyapunov Theory ◽  
Degree Of Freedom ◽  
Quintic Polynomial ◽  
High Degree

Robot manipulator trajectory planning is one of the core robot technologies, and the design of controllers can improve the trajectory accuracy of manipulators. However, most of the controllers designed at this stage have not been able to effectively solve the nonlinearity and uncertainty problems of the high degree of freedom manipulators. In order to overcome these problems and improve the trajectory performance of the high degree of freedom manipulators, a manipulator trajectory planning method based on a radial basis function (RBF) neural network is proposed in this work. Firstly, a 6-DOF robot experimental platform was designed and built. Secondly, the overall manipulator trajectory planning framework was designed, which included manipulator kinematics and dynamics and a quintic polynomial interpolation algorithm. Then, an adaptive robust controller based on an RBF neural network was designed to deal with the nonlinearity and uncertainty problems, and Lyapunov theory was used to ensure the stability of the manipulator control system and the convergence of the tracking error. Finally, to test the method, a simulation and experiment were carried out. The simulation results showed that the proposed method improved the response and tracking performance to a certain extent, reduced the adjustment time and chattering, and ensured the smooth operation of the manipulator in the course of trajectory planning. The experimental results verified the effectiveness and feasibility of the method proposed in this paper.

Global robust output feedback tracking control of robot manipulators

Robotica ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 351-357 ◽  
Author(s):  
W. E. Dixon ◽  
E. Zergeroglu ◽  
D. M. Dawson
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Position Tracking ◽  
Incomplete Model ◽  
Bounded Disturbances ◽  
Position Tracking Control ◽  
Feedback Tracking

This paper addresses the problem of global output feedback, link position tracking control of robot manipulators. Specifically, a robust, Lyapunov-based controller is designed to ensure that the link position tracking error is globally uniformly ultimately bounded despite the fact that only link position measurements are available in the presence of incomplete model information (i.e., parametric uncertainty and additive bounded disturbances).

Output feedback synchronization of multiple robot systems under parametric uncertainties

2016 ◽  
Vol 39 (3) ◽  
pp. 277-287 ◽  
Author(s):  
Elif Cicek ◽  
Janset Dasdemir
Keyword(s):  
Cooperative Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Position Tracking ◽  
Parametric Uncertainties ◽  
Synchronization Problem ◽  
Control Scheme ◽  
Robot Systems ◽  
Multiple Robot ◽  
Adaptation Law

In this paper, we propose a novel cooperative control scheme that solves the position synchronization problem of multiple robot manipulators, under parametric uncertainties, in the case when only position measurements are available. The synchronization controller, adaptation law and the filter that generates a velocity-related signal from the position tracking error are designed via a Lyapunov-based stability analysis. It is shown that the proposed method guarantees semi-global asymptotic convergence of the position synchronization error. The simulation results on five robot manipulators ensure the feasibility of the filter/controller mechanism.

scholarly journals A model-based velocity controller for chaotization of flexible joint robot manipulators

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880252 ◽  
Author(s):  
Roger Miranda-Colorado ◽  
Luis T Aguilar ◽  
J Moreno-Valenzuela
Keyword(s):  
Vector Field ◽  
Asymptotic Stability ◽  
Chaotic Motion ◽  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Reference Vector ◽  
Flexible Joint ◽  
Model Based

This article presents a model-based velocity controller able to induce a chaotic motion on n-degrees of freedom flexible joint robot manipulators. The proposed controller allows the velocity link vector of a robot manipulator to track an arbitrary, chaotic reference vector field. A rigorous theoretical analysis based on Lyapunov’s theory is used to prove the asymptotic stability of the tracking error signals when using the proposed controller, which implies that a chaotic motion is induced to the robotic system. Experimental results are provided using a flexible joint robot manipulator of two degrees of freedom. Finally, by using Poincaré maps and Lyapunov exponents, it is shown that the behavior exhibited by the robot joint positions is chaotic.

Robust control of robot manipulators with an adaptive fuzzy unmodelled parameter estimation law

Robotica ◽  
2021 ◽  
pp. 1-16
Author(s):  
Recep Burkan ◽  
Askin Mutlu
Keyword(s):  
Lyapunov Function ◽  
Dynamic Model ◽  
Robot Manipulators ◽  
External Disturbance ◽  
Tracking Error ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Friction Forces ◽  
Joint Friction ◽  
Accuracy And Repeatability

Summary For robot manipulators, there are two types of disturbances. One is model parametric uncertainty; the other is unmodelled parameters such as joint friction forces and external disturbances. Unmodelled joint frictions and external disturbances reduce performance in terms of positioning accuracy and repeatability. In order to compensate for unmodelled parameters, the design of a new controller is considered. First, the modelled and unmodelled parameters are included in a dynamic model. Then, based on the dynamic model, a new Lyapunov function is developed. After that, new nonlinear joint friction and external disturbance estimation laws are derived as an analytic solution from the Lyapunov function; thus, the stability of the closed system is guaranteed. Better values of the adaptive dynamic compensators can be extracted by fuzzy rules according to the tracking error. Limitations and knowledge about friction and external disturbances are not required for the design of the controller. The controller compensates for all possible model parameter uncertainties, all possible unknown joint frictions and external disturbances.

Discrete-Time LQR and H 2 Damping Control of Flexible Payloads Using a Robot Manipulator With a Wrist-Mounted Force/Torque Sensor

2000 ◽  
Author(s):  
Chunhao Joseph Lee ◽  
Constantinos Mavroidis
Keyword(s):  
Optimal Control ◽  
Discrete Time ◽  
Robot Manipulator ◽  
Control Design ◽  
Degree Of Freedom ◽  
Flexible Beam ◽  
Torque Sensor ◽  
Damping Control ◽  
Control Feedback ◽  
Six Degree Of Freedom

Abstract This paper presents robust and optimal control methods to suppress vibrations of flexible payloads carried by robotic systems. A new improved estimator in discrete-time H2 optimal control design based on the Kalman Filter predictor form is developed here. Two control design methods using state-space models, LQR and H2 Optimal Design, in discrete-time domain are applied and compared. The manipulator joint encoders and the wrist-mounted six-degree-of-freedom force/torque sensor provide the control feedback. A complete dynamic model of the robot/payload system is taken into account to synthesize the controllers. Experimental verifications of both methods are performed using a Mitsubishi five-degree-of-freedom robot manipulator that carries a flexible beam. It is shown that both methods damp out the vibrations of the payload very effectively.

Pseudoinverse-type bi-criteria minimization scheme for redundancy resolution of robot manipulators

Robotica ◽  
2014 ◽  
Vol 33 (10) ◽  
pp. 2100-2113 ◽  
Author(s):  
Bolin Liao ◽  
Weijun Liu
Keyword(s):  
Robot Manipulator ◽  
Robot Manipulators ◽  
Weighting Factor ◽  
Redundancy Resolution ◽  
Type Solution ◽  
Revolute Joints ◽  
Joint Velocity ◽  
Joint Acceleration ◽  
Minimum Velocity ◽  
Minimization Scheme

SUMMARYIn this paper, a pseudoinverse-type bi-criteria minimization scheme is proposed and investigated for the redundancy resolution of robot manipulators at the joint-acceleration level. Such a bi-criteria minimization scheme combines the weighted minimum acceleration norm solution and the minimum velocity norm solution via a weighting factor. The resultant bi-criteria minimization scheme, formulated as the pseudoinverse-type solution, not only avoids the high joint-velocity and joint-acceleration phenomena but also causes the joint velocity to be near zero at the end of motion. Computer simulation results based on a 4-Degree-of-Freedom planar robot manipulator comprising revolute joints further verify the efficacy and flexibility of the proposed bi-criteria minimization scheme on robotic redundancy resolution.

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