scholarly journals Self-tuning Fuzzy Task Space Controller for Puma 560 Robot

2018 ◽  
Vol 7 (4) ◽  
pp. 273
Author(s):  
Azita Azarfar
Keyword(s):  
High Performance ◽  
Control Method ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Joint Space ◽  
Robot Arm ◽  
Task Space ◽  
Scaling Factors ◽  
Cartesian Space ◽  
Self Tuning

Since in most robot applications the desired paths are determined in task space or Cartesian space, it is important to control the robot arm in task space. In this paper a fuzzy controller with modifiable scaling factors is proposed to control the robot end-effector in task space. The controller is a fuzzy system with a mechanism to change the scaling factors when the error is bounded under a predetermined value. The controller is designed in joint space and is developed to work space by using inverse Jacobian strategy. The simulations results on Puma 560 robot manipulator illustrate the high performance of presented control method.

A Cartesian Workspace Generator for Robot Arm Workcell Obstacle Collision Avoidance

1991 ◽  
Author(s):  
Tak-Lai Daryl Luk ◽  
John E. Sneckenberger
Keyword(s):  
Free Space ◽  
Robot Manipulator ◽  
Joint Space ◽  
Robot Arm ◽  
New Approach ◽  
Cartesian Space ◽  
Manipulator Arm ◽  
Arm Motion ◽  
Space Boundary ◽  
Crank Mechanism

Abstract Most of the methods for planning collision-free robot manipulator arm morions to accomplish collision-free end-effector paths are based on explicit representation of the sub-space of the robot work space that is free of arm motion with obstacles collision. This sub-space is called the robot arm free space and most path planners represent this free space in joint space. If the robot arm free space is represented in joint space, then each point in the free space corresponds to a robot arm configuration for which no arm-obstacle collision occurs. This paper presents a new approach for generating the robot arm free space for an articulated type robot manipulator. This approach uses an oscillating slider crank mechanism for defining the free-space boundary when certain arm-obstacle collisions occurs. The robot arm free space, importantly, is generated in Cartesian space instead of joint space.

scholarly journals Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks

2021 ◽  
Vol 54 (1-2) ◽  
pp. 102-115
Author(s):  
Wenhui Si ◽  
Lingyan Zhao ◽  
Jianping Wei ◽  
Zhiguang Guan
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Control Method ◽  
Joint Space ◽  
Robot Kinematics ◽  
Rbf Neural Networks ◽  
Task Space ◽  
Actuator Dynamics ◽  
Rigid Link ◽  
On Line

Extensive research efforts have been made to address the motion control of rigid-link electrically-driven (RLED) robots in literature. However, most existing results were designed in joint space and need to be converted to task space as more and more control tasks are defined in their operational space. In this work, the direct task-space regulation of RLED robots with uncertain kinematics is studied by using neural networks (NN) technique. Radial basis function (RBF) neural networks are used to estimate complicated and calibration heavy robot kinematics and dynamics. The NN weights are updated on-line through two adaptation laws without the necessity of off-line training. Compared with most existing NN-based robot control results, the novelty of the proposed method lies in that asymptotic stability of the overall system can be achieved instead of just uniformly ultimately bounded (UUB) stability. Moreover, the proposed control method can tolerate not only the actuator dynamics uncertainty but also the uncertainty in robot kinematics by adopting an adaptive Jacobian matrix. The asymptotic stability of the overall system is proven rigorously through Lyapunov analysis. Numerical studies have been carried out to verify efficiency of the proposed method.

Fuzzy Self-Tuning Precompensation PD Control with Gravity Compensation of 3 DOF Planar Robot Manipulators

2010 ◽  
Vol 22 (4) ◽  
pp. 551-560
Author(s):  
Ahmed Foad Amer ◽  
◽  
Elsayed Abdelhameed Sallam ◽  
Wael Mohammed Elawady ◽  
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
External Perturbation ◽  
Gravity Compensation ◽  
Pd Control ◽  
Control Laws ◽  
Self Tuning ◽  
Fuzzy Pd

Industrial robot control covers nonlinearity, uncertainty and external perturbation considered in control laws design. Proportional and Derivative (PD) with gravity compensation control is well-known control used in manipulators to ensure global asymptotic stability for fixed symmetrical positive definite gain matrices. To enhance PD with gravity compensation controller performance, in this paper, we propose hybrid fuzzy PD control precompensation with gravity compensation, consisting of a fuzzy logic-based precompensator followed by hybrid fuzzy PD with gravity compensation controller. Hybrid fuzzy control is done by a Supervisory Hierarchical Fuzzy Controller (SHFC) for tuning conventional controller Proportional and Derivative gains based on actual tracking location and velocity error. Hierarchical hybrid fuzzy control consists of an intelligent upper supervisory fuzzy controller and a lower direct conventional PD controller. Numerical simulations using the dynamic model of a three DOF planar rigid robot manipulator with uncertainty show the effectiveness of the approach in trajectory tracking problems. Our results show that the proposal controller has performance superior to a conventional controller.

Application of Fuzzy Controller with Self-Tuning Scaling Factors for the Filling System of Counter-Gravity Casting

2012 ◽  
Vol 538-541 ◽  
pp. 1122-1129
Author(s):  
Qiang Li ◽  
Qi Tang Hao ◽  
Wan Qi Jie
Keyword(s):  
Control System ◽  
Steady State ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Mold Filling ◽  
Scaling Factors ◽  
Gravity Casting ◽  
Input And Output ◽  
Self Tuning ◽  
Tube Filling

Pressurization control system plays an important role in the process control at the stages of riser-tube filling, mold-filling, pressure-increasing and pressure maintaining in counter-gravity casting. Casting quality is affected by the precision of pressurization control system to a great extent. Input and output scaling factors of conventional fuzzy controller are static, which is hard to ensure a suitable state for various counter-gravity casting equipments. A new fuzzy controller with self-tuning scaling factors has been developed in our laboratory, which will be described in this paper. Input and output scaling factors of fuzzy controller are tuned by different error ranges. When the differential pressure error is large, output scaling factor is increased to speed up dynamic response. At the same time, input scaling factors are also increased in order to reduce steady state error. Compared to fuzzy controller and conventional PID controller, fuzzy-PID controller with self-tuning scaling factors has more steady-state precision and excellent robustness. Experimental results show that at riser-tube filling stage and mold-filling stage the gas flow is stable, and the tracking property of pressurization control system is very satisfactory.

scholarly journals Artificial Intelligent Fuzzy Logic Controller Applied on 6DOF Robot Arm Using LabVIEW and FPGA

2018 ◽  
Vol 3 (5) ◽  
pp. 1
Author(s):  
Ahlam Najm A-Amir ◽  
Hanan A.R. Akkar
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Robot Arm ◽  
Serial Link ◽  
Artificial Intelligent ◽  
Field Programmable ◽  
Labview Fpga

In this work an efficient Artificial Intelligent Robotic Fuzzy Logic Controller (AIRFC) system have been constructed to control the robot arm. A serial link Robot manipulator with 6 Degree of Freedom (DOF) from DFROBOT of code ROB0036 is used as a case study. A fuzzy logic type1 controller is implemented on LabVIEW to control each joint of the robot arm for nonlinearity measurements and a fuzzy logic type2 controller is applied which is more suitable for uncertainty. The hardware design is implemented and finally downloaded using the Field Programmable Gate Array (FPGA) kit named PCI-7833R from National Instrument. By using the LabVIEW FPGA MODEL the target board can be detected for software implementation of the controllers’ systems. The work shows that in case of type2 fuzzy logic the rise time is less than that of type1 fuzzy logic for the shoulder, wrist roll and the gripper angles and it is higher for base, elbow and wrist pitch angles. The settling time is the same in elbow and wrist pitch angles and for the type2 fuzzy controller it is less for other angles.

scholarly journals Path optimization for robots in a constrained workspace

2019 ◽  
Vol 8 (2) ◽  
pp. 89
Author(s):  
Doaa Mahmood Badr ◽  
Abbas Fadhal Mahdi
Keyword(s):  
Optimal Path ◽  
Joint Space ◽  
Task Space ◽  
Dimensional Synthesis ◽  
A Algorithm ◽  
Cartesian Space ◽  
Optimum Path ◽  
Stepper Motors ◽  
Path Planner

In this work, the classical A* algorithm serves as path planner to generate the optimum path that would avoid collisions and take the start, collisions, and goal as an input and give the optimal path as an output. The work was done in a static environment, so the coordinates of the obstacles are predefined for the planner. The obtained path is just a sequence of points in space, and this path may be considered later the task space and the first step for another sequential operation like mapping from Cartesian space to joint space, topology optimization, dimensional synthesis, etc. The case study was Lab-Volt 5150 manipulator; it is an accurate educational five degree of freedom 5DOF stationary robot driven by five stepper motors.

Robot Manipulator Vibration Resistance Control Based on Physical Model

2020 ◽  
Author(s):  
Ting-Sheng Chen ◽  
Jen-Yuan (James) Chang
Keyword(s):  
Control Method ◽  
Robot Manipulator ◽  
Path Following ◽  
Position Error ◽  
Machining Accuracy ◽  
Robot Arm ◽  
End Effector ◽  
Vibration Resistance ◽  
Mass Spring ◽  
Accuracy And Repeatability

Abstract The overwhelming manufacturing process with robotic arm has replaced human labors in handling and manufacturing work-pieces in factories. In these years, higher accuracy and repeatability are required for robotic manipulators to perform processes such as welding, deburring and grinding in factories. In these path-following processes, the manipulator’s end-effector often encounter position error caused by its vibrating structures. Therefore, the quality of machining accuracy and surface roughness becomes unstable and unsatisfied. For the purpose of avoiding the vibrations to occur in the robotic manipulator, this study aims to design a control method to reduce vibrations which is divided into two parts, namely (1) dynamic modeling the robot arm by applying modified mass-spring-damper model to each joints and links of the robot arm, and (2) realizing the control of the robot arm’s vibration resistance with predicated dynamics to compensate for the undesired dynamics, respectively. Through the proposed model, the response of each joints in different postures and different payloads applied at the end effector can be fully analyzed and the vibrations can be predicted and compensated. Results with the proposed vibration resistance control method indicate improvement of the model robot arm’s dynamic position error.

scholarly journals Integrated Trajectory Planning and Sloshing Suppression for Three-Dimensional Motion of Liquid Container Transfer Robot Arm

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Wisnu Aribowo ◽  
Takahito Yamashita ◽  
Kazuhiko Terashima
Keyword(s):  
Trajectory Planning ◽  
Dimensional Space ◽  
Translational Motion ◽  
Three Dimensional ◽  
Joint Space ◽  
Robot Arm ◽  
Task Space ◽  
Robot Wrist ◽  
Point To Point ◽  
Sloshing Suppression

For liquid transfer system in three-dimensional space, the use of multijoint robot arm provides much flexibility. To realize quick point-to-point motion with minimal sloshing in such system, we propose an integrated framework of trajectory planning and sloshing suppression. The robot motion is decomposed into translational motion of the robot wrist and rotational motion of the robot hand to ensure the upright orientation of the liquid container. The trajectory planning for the translational motion is based on cubic spline optimization with free via points that produces smooth trajectory in joint space while it still allows obstacle avoidance in task space. Input shaping technique is applied in the task space to suppress the motion induced sloshing, which is modeled as spherical pendulum with moving support. It has been found through simulations and experiments that the proposed approach is effective in generating quick motion with low amount of sloshing.

High Performance Control of Stewart Platform Manipulator Using Sliding Mode Control with Synchronization Error

2011 ◽  
Vol 1 (4) ◽  
pp. 19-43 ◽  
Author(s):  
Dereje Shiferaw ◽  
Anamika Jain ◽  
R. Mitra
Keyword(s):  
High Performance ◽  
Sliding Mode ◽  
Computation Time ◽  
Variable Structure ◽  
Joint Space ◽  
Stewart Platform ◽  
Task Space ◽  
Tracking Accuracy ◽  
Synchronization Errors ◽  
Equivalent Control

This paper presents the design and analysis of a high performance robust controller for the Stewart platform manipulator. The controller is a variable structure controller that uses a linear sliding surface which is designed to drive both tracking and synchronization errors to zero. In the controller the model based equivalent control part of the sliding mode controller is computed in task space and the discontinuous switching controller part is computed in joint space and hence it is a hybrid of the two approaches. The hybrid implementation helps to reduce computation time and to achieve high performance in task space without the need to measure or estimate 6DOF task space positions. Effect of actuator friction, backlash and parameter variation due to loading have been studied and simulation results confirmed that the controller is robust and achieves better tracking accuracy than other types of sliding mode controllers and simple PID controller.

High Performance Control of Stewart Platform Manipulator Using Sliding Mode Control with Synchronization Error

2013 ◽  
pp. 225-248
Author(s):  
Dereje Shiferaw ◽  
Anamika Jain ◽  
R. Mitra
Keyword(s):  
High Performance ◽  
Sliding Mode ◽  
Computation Time ◽  
Variable Structure ◽  
Joint Space ◽  
Stewart Platform ◽  
Task Space ◽  
Tracking Accuracy ◽  
Synchronization Errors ◽  
Equivalent Control

This paper presents the design and analysis of a high performance robust controller for the Stewart platform manipulator. The controller is a variable structure controller that uses a linear sliding surface which is designed to drive both tracking and synchronization errors to zero. In the controller the model based equivalent control part of the sliding mode controller is computed in task space and the discontinuous switching controller part is computed in joint space and hence it is a hybrid of the two approaches. The hybrid implementation helps to reduce computation time and to achieve high performance in task space without the need to measure or estimate 6DOF task space positions. Effect of actuator friction, backlash and parameter variation due to loading have been studied and simulation results confirmed that the controller is robust and achieves better tracking accuracy than other types of sliding mode controllers and simple PID controller.

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