Dynamics and Trajectory Tracking Control of a Two-Link Robot Manipulator

2004 ◽  
Vol 10 (10) ◽  
pp. 1415-1440 ◽  
Author(s):  
Anthony Green ◽  
Jurek Z. Sasiadek
Keyword(s):  
Fuzzy Logic ◽  
Time Delay ◽  
Inverse Dynamics ◽  
Position Control ◽  
Robot Manipulator ◽  
Phase Response ◽  
Control Law ◽  
Minimum Phase ◽  
Linear Quadratic ◽  
Trajectory Tracking Control

Operational problems with robot manipulators in space relate to several factors, most importantly, structural flexibility and subsequent difficulties with their position control. In this paper we present control methods for endpoint tracking of a 12.6 × 12.6m2 trajectory by a two-link robot manipulator. Initially, a manipulator with rigid links is modeled using inverse dynamics, a linear quadratic regulator and fuzzy logic schemes actuated by a Jacobian transpose control law computed using dominant cantilever and pinned-pinned assumed mode frequencies. The inverse dynamics model is pursued further to study a manipulator with flexible links where nonlinear rigid-link dynamics are coupled with dominant assumed modes for cantilever and pinned-pinned beams. A time delay in the feedback control loop represents elastic wave travel time along the links to generate non-minimum phase response. A time delay acting on control commands ameliorates non-minimum phase response. Finally, a fuzzy logic system outputs a variable to adapt the control law in response to elastic deformation inputs. Results show greater endpoint position control accuracy using a flexible inverse dynamics robot model combined with a fuzzy logic adapted control law and time delays than could be obtained for the rigid dynamics models.

An investigation of fuzzy logic control of flexible robots

Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Yueh-Jaw Lin ◽  
Tian-Soon Lee
Keyword(s):  
Fuzzy Logic ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Robot Manipulator ◽  
Nonlinear Effects ◽  
Control Law ◽  
Flexible Robot ◽  
Control Rules ◽  
Logic Control ◽  
The Mathematical Model

SUMMARYIn this paper a control law, which consists of a fuzzy logic controller plus a nonlinear effects negotiator for a flexible robot manipulator, is presented. The nonlinear effects negotiator is used to enhence the control system's ability in dealing with the uncertainty of the mathematical model. The control algorithm is simple and easy to tune as opposed to conventional control law which requires time consuming gains selections. To obtain fuzzy control rules, an error response plane method is proposed.

A Modular 2-DOF Serial Robot Manipulator for Education in Robot Control

2016 ◽  
Author(s):  
Stephen Mascaro
Keyword(s):  
Robot Control ◽  
Inverse Dynamics ◽  
Position Control ◽  
Sliding Mode ◽  
Feedforward Control ◽  
Robot Manipulator ◽  
Impedance Control ◽  
Force Sensor ◽  
Control Techniques ◽  
Serial Robot

This paper describes a modular 2-DOF serial robot manipulator and accompanying experiments that have been developed to introduce students to the fundamentals of robot control. The robot is designed to be safe and simple to use, and to have just enough complexity (in terms of nonlinear dynamics) that it can be used to showcase and compare the performance of a variety of textbook robot control techniques including computed torque feedforward control, inverse dynamics control, robust sliding-mode control, and adaptive control. These various motion control schemes can be easily implemented in joint space or operational space using a MATLAB/Simulink real-time interface. By adding a simple 2-DOF force sensor to the end-effector, the robot can also be used to showcase a variety of force control techniques including impedance control, admittance control, and hybrid force/position control. The 2-DOF robots can also be used in pairs to demonstrate control architectures for multi-arm coordination and master/slave teleoperation. This paper will describe the 2-DOF robot and control hardware/software, illustrate the spectrum of robot control methods that can be implemented, and show sample results from these experiments.

scholarly journals FPGA Realization and Lyapunov–Krasovskii Analysis for a Master-Slave Synchronization Scheme Involving Chaotic Systems and Time-Delay Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
J. Perez-Padron ◽  
C. Posadas-Castillo ◽  
J. Paz-Perez ◽  
E. Zambrano-Serrano ◽  
M. A. Platas-Garza
Keyword(s):  
Time Delay ◽  
Chaotic System ◽  
Chaotic Systems ◽  
Tracking Error ◽  
Control Law ◽  
Trajectory Tracking Control ◽  
Field Programmable ◽  
Different Chaotic Systems ◽  
Synchronization Scheme ◽  
Theoretical Results

In this paper, the trajectory tracking control and the field programmable gate array (FPGA) implementation between a recurrent neural network with time delay and a chaotic system are presented. The tracking error is globally asymptotically stabilized by means of a control law generated from the Lyapunov–Krasovskii and Lur’e theory. The applicability of the approach is illustrated by considering two different chaotic systems: Liu chaotic system and Genesio–Tesi chaotic system. The numerical results have shown the effectiveness of obtained theoretical results. Finally, the theoretical results are implemented on an FPGA, confirming the feasibility of the synchronization scheme and showing that it is hardware realizable.

Optimal control of a planar robot manipulator based on the Linear Quadratic Inverse-Dynamics design

2019 ◽  
Vol 2 (2) ◽  
pp. 2
Author(s):  
Denis Mosconi ◽  
Adriano Almeida Gonçalves Siqueira ◽  
Everthon Silva Fonseca
Keyword(s):  
Feedback Loop ◽  
Inverse Dynamics ◽  
Robot Manipulator ◽  
Linear Quadratic Regulator ◽  
Robotic Systems ◽  
Reference Trajectory ◽  
Linear Quadratic ◽  
End Effector ◽  
The Right

To ensure the correct positioning of the end-effector of robot manipulators is one of the most important objectives of the robotic systems control. Lack of reliability in tracking the reference trajectory, as well as in the desired final positioning compromises the quality of the task to be performed, even causing accidents. The purpose of this work was to propose an optimal controller with an inner loop based on the dynamic model of the manipulator and a feedback loop based on the Linear Quadratic Regulator, in order to ensure that the end effector is in the right place, at the right time. The controller was compared to the conventional PID, presenting better performance, both in the transient response, eliminating overshoot, and steady-state, eliminating the stationary error.

scholarly journals Fuzzy logic controller design for PUMA 560 robot manipulator

2020 ◽  
Vol 9 (2) ◽  
pp. 73
Author(s):  
Abdel-Azim S. Abdel-Salam ◽  
Ibrahim N. Jleta
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Controller Design ◽  
Robot Manipulator ◽  
Tracking Error ◽  
Pid Controllers ◽  
Fuzzy Logic Controllers ◽  
Better Than ◽  
Computed Torque

The dynamic model of the robot manipulator contain from equations, these equations are nonlinear and contained from variations parameters due to variations in load, friction, and disturbance. The conventional computed torque (PD and PID) controllers are not highly suitable for nonlinear, complex, time-variant systems with delay. In this paper, the fuzzy logic controllers (FLC) has been used because it is efficient tools for control of nonlinear and uncertain parameters systems. This paper aims to design a fuzzy logic controller for position control of a PUMA 560 robot manipulator. Based on simulation results we conclude that the performance of the fuzzy logic controller in term of position tracking error in case of disturbance or load is better than the conventional computed torque (PD-CTC and PID-CTC) controllers.

scholarly journals Optimization of sliding mode control with PID surface for robot manipulator by Evolutionary Algorithms

2020 ◽  
Vol 10 (1) ◽  
pp. 396-407
Author(s):  
Fatiha Loucif ◽  
Sihem Kechida
Keyword(s):  
Sliding Mode ◽  
Robot Manipulator ◽  
Absolute Error ◽  
Grey Wolf Optimizer ◽  
Optimal Parameters ◽  
Error Criterion ◽  
Trajectory Tracking Control ◽  
Integral Time ◽  
Sine Cosine Algorithm ◽  
Antlion Optimization

AbstractIn this paper, a sliding mode controller (SMC) with PID surface is designed for the trajectory tracking control of a robot manipulator using different optimization algorithms such as, Antlion Optimization Algorithm (ALO) Sine Cosine Algorithm (SCA) Grey Wolf Optimizer (GWO) and Whale Optimizer Algorithm (WOA). The aim of this work is to introduce a novel SMC-PID-ALO to control nonlinear systems, especially the position of two of the joints of a 2DOF robot manipulator. The basic idea is to determinate four optimal parameters (Kp, Ki, Kd and lamda) ensuring the best performance of a robot manipulator system, minimizing the integral time absolute error criterion (ITAE) and the integral time square error criterion (ISTE). The robot manipulator is modeled in Simulink and the control is implemented using the MATLAB environment. The obtained simulation results prove the robustness of ALO in comparison with other algorithms.

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