An Emergency Tracking Controller Design for a Manipulator After its Actuator Failure

2015 ◽  
Author(s):  
Elżbieta Jarzębowska ◽  
Adam Szewczyk
Keyword(s):  
Degrees Of Freedom ◽  
Controller Design ◽  
Actuator Failure ◽  
End Effector ◽  
Model Based ◽  
Rest Position ◽  
Control Goal ◽  
Tracking Controllers ◽  
Tracking Controller ◽  
Simulation Results

This paper presents a development of two model-based emergency tracking controllers which can be turned on when one of actuators of a system fails during motion. The system is represented by a manipulator possessing 3 degrees of freedom, which may work in horizontal or vertical planes. The control goal is to enable an end effector of a broken manipulator completing tracking a predefined task as good as possible and then get back to its rest position. Simulation results confirm good performance of the designed emergency tracking controllers.

Decentralized LPV Gain-Scheduled PD Control of a Robotic Manipulator

2009 ◽  
Author(s):  
H. Abbas ◽  
S. M. Hashemi ◽  
H. Werner
Keyword(s):  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Controller Design ◽  
Robotic Manipulator ◽  
Low Complexity ◽  
Torque Control ◽  
Tracking Performance ◽  
Pd Controller ◽  
Model Based ◽  
Gain Scheduled

In this paper, low-complexity linear parameter-varying (LPV) modeling and control of a two-degrees-of-freedom robotic manipulator is considered. A quasi-LPV model is derived and simplified in order to facilitate LPV controller synthesis. An LPV gain-scheduled, decentralized PD controller in linear fractional transformation form is designed, using mixed sensitivity loop shaping to take — in addition to high tracking performance — noise and disturbance rejection into account, which are not considered in model-based inverse dynamics or computed torque control schemes. The controller design is based on the existence of a parameter-dependent Lyapunov function — employing the concept of quadratic separators — thus reducing the conservatism of design. The resulting bilinear matrix inequality (BMI) problem is solved using a hybrid gradient-LMI technique. Experimental results illustrate that the LPV controller clearly outperforms a decentralized LTI-PD controller and achieves almost the same accuracy as a model-based inverse dynamics and a full-order LPV controllers in terms of tracking performance while being of significantly lower complexity.

Gateway Configuration for Rapid Pick-and-Place Operations of 2-Degrees-of-Freedom Parallel Robots

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrea Martin-Parra ◽  
David Rodriguez-Rosa ◽  
Sergio Juarez-Perez ◽  
Guillermo Rubio-Gomez ◽  
Antonio Gonzalez-Rodriguez ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Degrees Of Freedom ◽  
Jacobian Matrix ◽  
Parallel Robots ◽  
End Effector ◽  
Joint Coordinates ◽  
Pick And Place ◽  
Low Energy Consumption ◽  
Simulation Results ◽  
The Difference

Abstract This article presents a new assembling for 2 degrees-of-freedom (DOFs) parallel robots for executing rapid pick-and-place operations with low energy consumption. A conventional design of 2-DOF parallel robots is based on five-bar mechanisms. Collisions between links are highly possible, restricting the end-effector workspace and/or increasing the trajectory time to avoid collisions. In this article, an alternative assembling for preventing collisions is presented. This novel assembling allows exploring the difference between the four five-bar mechanism configurations for the same position of the end-effector. Some of these configurations yield to lower time and/or lower energy consumption for the same motorization. First, a dynamic model of the robot has been developed using matlab® and simulink® and validated by comparison with the results obtained by adams® software. A robust cascade PD regulator for controlling joint coordinates has been tuned providing a high accurate end-effector positioning. Finally, simulation results of four configurations are presented for executing controlled maneuvers. The obtained results demonstrate that the conventional configuration is the worst one in terms of trajectory time or energy consumption and, conversely, the best one corresponds to an uncommonly used configuration. A workspace map where all configurations provide faster maneuvers has been obtained in terms of Jacobian matrix and mechanism elbows distance. The results presented here allow designing a rapid manipulator for pick-and-place operations.

Minimum Energy Control of Redundant Cartesian Manipulators

2012 ◽  
Author(s):  
Yoram Halevi ◽  
Emanuele Carpanzano ◽  
Giuseppe Montalbano
Keyword(s):  
Degrees Of Freedom ◽  
Minimum Energy ◽  
Joint Motion ◽  
Energy Control ◽  
End Effector ◽  
Considerable Saving ◽  
Minimum Energy Control ◽  
Simulation Results ◽  
The Individual ◽  
The Cost

In redundant manipulation systems the end-effector path does not completely determine the trajectories of all the individual degrees of freedom (dof). The redundancy is used in this paper to minimize energy consumption. A full electromechanical model is used, and the invested energy is calculated explicitly. The optimization includes also displacement limits via penalty functions that are included in the cost function. The solution is based on separating the system and the input into two parts. One that is completely determined by the end-effector path and the other that is driven by it, yet free for optimization. The boundary conditions are resolved in a similar manner, where the physical values are translated to the scaled down system by using a specific projection. Simulation results show that even with limited joint motion, the redundancy can lead to a considerable saving in energy.

Simple Robust r − α Tracking Controllers for Uncertain Fully-Actuated Mechanical Systems

1997 ◽  
Vol 119 (4) ◽  
pp. 821-825 ◽  
Author(s):  
Salah Zenieh ◽  
Martin Corless
Keyword(s):  
Numerical Simulation ◽  
Rate Of Convergence ◽  
Lyapunov Functions ◽  
Controller Design ◽  
Mechanical Systems ◽  
Robotic Manipulator ◽  
Robust Tracking ◽  
Robotic Control ◽  
Tracking Controllers ◽  
Simulation Results

We consider the problem of designing robust tracking controllers for uncertain fully-actuated mechanical systems. We propose controllers which are robust r − α tracking controllers in the following sense. For a prespecified rate of convergence α > 0 and a prespecified tolerance r > 0, a proposed controller guarantees that the system’s trajectory exponentially converges to any desired trajectory with rate a and to within the tolerance r. Controller design is based on Lyapunov functions. The main advantage of these controllers is their simplicity. These controllers do not use the regressor matrix made popular in the area of robotic control which makes them simple to implement. Application to a two-link robotic manipulator is presented. Numerical simulation results are included.

Minimum Energy Control of Redundant Manipulators With Axes Coupling and Compounded Path

2014 ◽  
Author(s):  
Lior Alpert ◽  
Yoram Halevi
Keyword(s):  
Energy Consumption ◽  
Degrees Of Freedom ◽  
Minimum Energy ◽  
Joint Motion ◽  
Redundant Manipulators ◽  
End Effector ◽  
Minimum Energy Control ◽  
Optimization Simulation ◽  
Simulation Results ◽  
The Individual

In redundant manipulation systems the end-effector path does not completely determine the trajectories of all the individual degrees of freedom and this freedom can be used to enhance the performance in some sense. The paper deals with utilizing the redundancy to minimize energy consumption. It extends previous results by considering more general cases of possible coupling between the axes, e.g. three axes for planar motion, and more general paths comprising of several primitive motions connected dynamically. The solution is based on projections into lower subspaces that separate the system and the input into two parts. One that is completely determined by the end-effector path and the other that is free for optimization. Simulation results show that redundancy, even with limited joint motion, can lead to a considerable reduction in energy consumption.

scholarly journals A discrete path/trajectory planner for robotic arms

1989 ◽  
Vol 31 (1) ◽  
pp. 1-28 ◽  
Author(s):  
H. H. Tan ◽  
R. B. Potts
Keyword(s):  
Degrees Of Freedom ◽  
Minimum Cost ◽  
Challenging Problem ◽  
Final State ◽  
End Effector ◽  
Joint Torques ◽  
Robotic Arms ◽  
Joint Coordinates ◽  
Simulation Results

AbstractAn interesting and challenging problem in robotics is the off-line determination of the minimum cost path along which an end effector should move from a given initial to a given final state. This paper presents a discrete minimum cost path/trajectory planner which provides a general solution and allows for a range of constraints such as bounds on joint coordinates, joint velocities, joint torques and joint jerks. To demonstrate the practicability and feasibility of the planner, simulation results are presented for the Stanford manipulator using three and then the full six of its degrees of freedom. Simulation runs with two-link planar arms are also presented to enable a comparison with previously published results.

scholarly journals Adaptive control of redundant robot manipulators with sub-task objectives

Robotica ◽  
2009 ◽  
Vol 27 (6) ◽  
pp. 873-881 ◽  
Author(s):  
Enver Tatlicioglu ◽  
David Braganza ◽  
Timothy C. Burg ◽  
Darren M. Dawson
Keyword(s):  
Adaptive Control ◽  
Motion Control ◽  
Robot Manipulators ◽  
Estimation Algorithm ◽  
Kinematic Redundancy ◽  
End Effector ◽  
Redundant Robot ◽  
Tracking Controller ◽  
Simulation Results ◽  
Self Motion

SUMMARYIn this paper, adaptive control of kinematically redundant robot manipulators is considered. An end-effector tracking controller is designed and the manipulator's kinematic redundancy is utilized to integrate a general sub-task controller for self-motion control. The control objectives are achieved by designing a feedback linearizing controller that includes a least-squares estimation algorithm to compensate for the parametric uncertainties. Numerical simulation results are presented to show the validity of the proposed controller.

Tracking Controller Design for MIMO Nonlinear Systems With Application to Automotive Cold Start Emission Reduction

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Selina Pan ◽  
J. Karl Hedrick
Keyword(s):  
Discrete Time ◽  
Model Uncertainty ◽  
Controller Design ◽  
Tracking Error ◽  
Cold Start ◽  
Verification And Validation ◽  
Control Algorithms ◽  
Adaptation Algorithm ◽  
Tracking Controller ◽  
Simulation Results

The main contribution of this paper is the development of a nonlinear multiple-input, multiple-output (MIMO) tracking controller design using a discrete time sliding control approach. A Lyapunov stability analysis is used to prove the asymptotic stability of both the output errors as well as the parameter estimation errors. The application of the “New Invariance Principle” is key to the proof of the parameter error convergence. The developed approach is applied to the cold start emissions problem. The software design process for automotive powertrains on vehicles is growing increasingly complex. Verification and validation provides a systematic procedure to follow for the implementation of control algorithms on physical systems. However, errors can arise that prove costly if not mitigated early on in the verification and validation process. Therefore, the detection and mitigation of potential uncertainties early on in the design process is vital. In this work, the determination of the system model uncertainty is the focus of an adaptation algorithm designed in parallel with a discrete time, MIMO sliding controller. The unknown parameter representing the model uncertainty is updated online in order to decrease tracking error and control effort. The MIMO formulation allows for implementation of both coupled and decoupled frameworks, thus providing a basis for the algorithm to be utilized on a variety of complex vehicle systems. The control algorithms are implemented on a cold start emissions engine model as a case study. A matlab simulink environment is used for simulation results, and an engine test cell is used for experimental validation. Simulation results demonstrate that the algorithm drives tracking error to zero in a fraction of the run time and that the algorithm may be applied with equal efficacy to coupled and decoupled systems. Experimental results demonstrate the ability of the adaptation algorithm to estimate uncertainty in the engine and decrease tracking error.

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