Joint torque control for the pneumatically robotic manipulator with 3 degrees of freedom

2008 ◽  
Vol 44 (12) ◽  
pp. 254 ◽  
Author(s):  
Xintao MAO
Keyword(s):  
Degrees Of Freedom ◽  
Robotic Manipulator ◽  
Torque Control ◽  
Joint Torque

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.

scholarly journals Robust Control for a 3DOF Articulated Robotic Manipulator Joint Torque under Uncertainties

2020 ◽  
pp. 1-13
Author(s):  
Chukwudi Emmanuel Agbaraji ◽  
Uchenna Henrietta Udeani ◽  
Hyacinth Chibueze Inyiama ◽  
Christiana Chikodi Okezie
Keyword(s):  
Robust Control ◽  
Pid Controller ◽  
Research Work ◽  
Robotic Manipulator ◽  
Torque Control ◽  
Joint Torque ◽  
Low Frequencies ◽  
H Infinity ◽  
Stability Robustness ◽  
Peak Sensitivity

This research work emphasizes on design of a robust control for a 3DOF robotic manipulator under uncertainties. The plant model was achieved using the independent joint method and the uncertainty problem was addressed by designing a robust controller using H-Infinity synthesis which was compared with PID. This was achieved with algorithms implemented in MATLAB. The H-Infinity controller recorded 0dB, while PID controller recorded 0.117dB and 0.061dB for joints I and II respectively in Complementary Sensitivity (T) graph at low frequencies. H-Infinity controller achieved better disturbance rejection characteristics with sensitivity (S) graph recording peak sensitivity of 0.817dB and 1.79dB at joints I and II respectively than PID controller which achieved 3dB and 1.86dB at joints I and II respectively. H-Infinity controller achieved better noise rejection characteristics with T graph recording lower gains at joints I and II respectively at high frequencies than PID controller which recorded higher gains at joints I and II respectively. Thus, it was concluded that the H-Infinity controller achieved better performance and stability robustness characteristics for the joint torque control than the PID.

scholarly journals Cascade position- torque control strategy based on function approximation technique (FAT) for flexible joint robots

2021 ◽  
Author(s):  
Hayder F.N. Al-Shuka ◽  
Burkhard Corves ◽  
Ehab N. Abbas
Keyword(s):  
Time Constant ◽  
Control Strategy ◽  
Function Approximation ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Torque Control ◽  
Joint Torque ◽  
Approximation Technique ◽  
Control Loop ◽  
Torque Control Strategy

Abstract This work deals with control of rigid link robotic manipulators provided with flexible joints. Due to presence of flexible joint dynamics, additional degrees of freedom and underactuation are developed that would complicate the control design. Besides, model uncertainties, unmodeled dynamics and disturbances should be considered in robot modeling and control. Therefore, this paper proposes a cascade position-torque control strategy based on function approximation technique (FAT). The key idea is to design two nested loops: 1) an outer position control loop for tracking reference trajectory, and 2) an inner joint torque control loop to track the desired joint torque resulted from the outer position loop. The torque control loop makes the robot system more adaptable and compliant for sudden disturbances. It increases the perception capability for the target robot mechanisms. Adaptive approximation control (AAC) is used as a strong tool for dealing with time-varying uncertain parameters and disturbances. A sliding mode term is easily integrated with control law structure; however, a constraint on feedback gains are established for compensating modeling (approximation) error. The proposed control architecture can be easily used for high degrees of freedom robotic system due to the decentralized behavior of the AAC. A two-link manipulator is used for simulation experiments.The simulated robot is commanded to move from rest to desired step references considering three cases depending on the selected value of the sliding mode time constant. It is shown that selection of a large time constant parameter related to the position loop leads to slow response. Besides, one of the inherent issues associated with the inner torque control is the presence of derivative of desired joint torque that makes the input control abruptly jumping at the beginning of the dynamic response. To end this, an approximation for derivative term of the desired joint torque is established using a low-pass filter with a time constant selected carefully such that a feasible dynamic response is ensured.The results show the effectiveness of the proposed controller.

scholarly journals Cascade position- torque control strategy based on function approximation technique (FAT) for flexible joint robots

2021 ◽  
Author(s):  
Hayder F.N. Al-Shuka ◽  
Burkhard Corves ◽  
Ehab N. Abbas
Keyword(s):  
Time Constant ◽  
Control Strategy ◽  
Function Approximation ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Torque Control ◽  
Joint Torque ◽  
Approximation Technique ◽  
Control Loop ◽  
Torque Control Strategy

Abstract This work deals with control of rigid link robotic manipulators provided with flexible joints. Due to presence of flexible joint dynamics, additional degrees of freedom and underactuation are developed that would complicate the control design. Besides, model uncertainties, unmodeled dynamics and disturbances should be considered in robot modeling and control. Therefore, this paper proposes a cascade position-torque control strategy based on function approximation technique (FAT). The key idea is to design two nested loops: 1) an outer position control loop for tracking reference trajectory, and 2) an inner joint torque control loop to track the desired joint torque resulted from the outer position loop. The torque control loop makes the robot system more adaptable and compliant for sudden disturbances. It increases the perception capability for the target robot mechanisms. Adaptive approximation control (AAC) is used as a strong tool for dealing with time-varying uncertain parameters and disturbances. A sliding mode term is easily integrated with control law structure; however, a constraint on feedback gains are established for compensating modeling (approximation) error. The proposed control architecture can be easily used for high degrees of freedom robotic system due to the decentralized behavior of the AAC. A two-link manipulator is used for simulation experiments.The simulated robot is commanded to move from rest to desired step references considering three cases depending on the selected value of the sliding mode time constant. It is shown that selection of a large time constant parameter related to the position loop leads to slow response. Besides, one of the inherent issues associated with the inner torque control is the presence of derivative of desired joint torque that makes the input control abruptly jumping at the beginning of the dynamic response. To end this, an approximation for derivative term of the desired joint torque is established using a low-pass filter with a time constant selected carefully such that a feasible dynamic response is ensured.The results show the effectiveness of the proposed controller.

Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

2021 ◽  
pp. 095441192098703
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Experimental Data ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Optimization Method ◽  
Weight Lifting ◽  
Joint Torque ◽  
Maximum Weight ◽  
Angular Velocities ◽  
Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

Design Human-Robot Collaborative Lifting Task Using Optimization

2021 ◽  
Author(s):  
Asif Arefeen ◽  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Joint Angle ◽  
Joint Torque ◽  
Robotic Arm ◽  
Inverse Dynamic ◽  
Floating Base ◽  
Grasping Forces ◽  
Design Variables ◽  
Human Arm ◽  
Lifting Task

Abstract In this paper, an optimization-based dynamic modeling method is used for human-robot lifting motion prediction. The three-dimensional (3D) human arm model has 13 degrees of freedom (DOFs) and the 3D robotic arm (Sawyer robotic arm) has 10 DOFs. The human arm and robotic arm are built in Denavit-Hartenberg (DH) representation. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The interactions between human arm and box, and robot and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. The inverse dynamic optimization is used to simulate the lifting motion where the summation of joint torque squares of human arm is minimized subjected to physical and task constraints. The design variables are control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box, and the box grasping forces at each time point. A numerical example is simulated for huma-robot lifting with a 10 Kg box. The human and robotic arms’ joint angle, joint torque, and grasping force profiles are reported. These optimal outputs can be used as references to control the human-robot collaborative lifting task.

Globalized Dual Heuristic Dynamic Programming in Control of Robotic Manipulator

2016 ◽  
Vol 817 ◽  
pp. 150-161 ◽  
Author(s):  
Marcin Szuster ◽  
Piotr Gierlak
Keyword(s):  
Neural Networks ◽  
Dynamic Programming ◽  
Control System ◽  
Degrees Of Freedom ◽  
Dynamic Programming Algorithm ◽  
Robotic Manipulator ◽  
Iteration Step ◽  
Programming Algorithm ◽  
Heuristic Dynamic Programming ◽  
The Stability

The article focuses on the implementation of the globalized dual-heuristic dynamic programming algorithm in the discrete tracking control system of the three degrees of freedom robotic manipulator. The globalized dual-heuristic dynamic programming algorithm is included in the approximate dynamic programming algorithms family, that bases on the Bellman’s dynamic programming idea. These algorithms generally consist of the actor and the critic structures realized in a form of artificial neural networks. Moreover, the control system includes the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis, which was realized using the Lyapunov stability theorem. The control system works on-line and the neural networks’ weight adaptation process is realized in every iteration step. A series of computer simulations was realized in Matlab/Simulink software to confirm performance of the control system.

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