Tracking Control of Robot Manipulators Using a Robust Deterministic Control Law

1998 ◽  
Vol 120 (4) ◽  
pp. 537-541 ◽  
Author(s):  
C.-G. Kang ◽  
R. Horowitz ◽  
G. Leitmann
Keyword(s):  
Dynamic Systems ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Experimental Studies ◽  
Control Law ◽  
Direct Drive ◽  
Control Scheme ◽  
Deterministic Control ◽  
Two Degree Of Freedom ◽  
Theoretical Developments

There have been theoretical developments on the control of dynamic systems based on deterministically uncertain and singularly perturbed models in recent years. In this paper, a robust deterministic control scheme proposed originally by M. Corless et al. is modified, and is applied to the tracking control of robot manipulators. Simulation and experimental studies for a two degree of freedom, direct drive SCARA manipulator are conducted to evaluate the effectiveness of the control scheme.

Regulation of a Two-Degree-of-Freedom Structure Using Internal Resonance

1995 ◽  
Vol 117 (2) ◽  
pp. 247-251 ◽  
Author(s):  
Shafic S. Oueini ◽  
Kevin L. Tuer ◽  
M. Farid Golnaraghi
Keyword(s):  
Internal Resonance ◽  
Control Technique ◽  
Control Law ◽  
Nonlinear Feedback ◽  
Flexible Arm ◽  
Control Scheme ◽  
Single Input ◽  
Linear Differential ◽  
Two Degree Of Freedom ◽  
Input Torque

In this paper, we present a first attempt at using an energy based control technique to regulate the oscillations of a flexible joint, flexible arm device, through computer simulation. This technique takes advantage of the Internal Resonance (IR) phenomenon. The plant is governed by two coupled linear differential equations. The control scheme is implemented by introducing two software based controllers which are coupled dynamically with the plant through a nonlinear feedback control law. At Internal Resonance, the nonlinear coupling generates an energy link between the plant and the controllers. Thus, energy is transferred from the plant to the controllers where two active damping mechanisms subsequently dissipate it. Here the response of the structure is regulated with a single input torque applied to one plant coordinate. The theoretical analysis is based on the two-variable expansion perturbation method. Thereafter, the analytical findings are verified numerically. Simulation results indicate that the IR control strategy is able to effectively quench the oscillations of the plant.

Multi-Level Phase Shift (MLPS) Control Enabled Variable Displacement Gerotor/Geroler

2007 ◽  
Author(s):  
QingHui Yuan ◽  
Brian Armstrong
Keyword(s):  
Phase Shift ◽  
Tracking Control ◽  
Control Algorithm ◽  
Control Law ◽  
Family Selection ◽  
Control Scheme ◽  
Variable Displacement ◽  
Multi Level ◽  
Velocity Tracking ◽  
Peak Value

The research focuses on enabling gerotor/geroler, a traditional fixed displacement device, with the variable displacement capability by integrating electronically controlled digital valves and the corresponding control algorithm. Each digital valve controls polarity of each corresponding chamber of the fixed displacement device. A novel Multi-Level Phase Shift (MLPS) control scheme is developed such that the instantaneous displacement of such a system can be controlled. This control law is characteristic of classifying all the possible valve configuration into several displacement families where the peak value within each family would be identical. Given a desired displacement, both displacement family selection and phase shift technology are utilized to achieve better performance. In the experimental study, MLPS control has been verified, and successfully achieves a closed loop velocity tracking control of a hydraulic geroler motor.

Modeling and Compensation of Hysteresis in Piezoceramic Transducers for Vibration Control

1999 ◽  
Author(s):  
Soon-Hong Lee ◽  
Thomas J. Royston ◽  
Gary Friedman
Keyword(s):  
Feedforward Control ◽  
Experimental Studies ◽  
Model Identification ◽  
Hysteretic Behavior ◽  
Mathematical Framework ◽  
Hysteresis Model ◽  
Composite Support ◽  
Hysteresis Compensation ◽  
Control Scheme ◽  
Theoretical Developments

Abstract Hysteretic behavior in piezoceramic transducers is investigated theoretically and experimentally. The applicability of the rate-independent generalized Maxwell resistive capacitor (MRC) hysteresis model is established. Methods for MRC and inverse MRC online model identification are developed by first establishing that the MRC and its inverse are the same particular cases of the classical Preisach hysteresis model. This enables use of the extensive mathematical framework that has been developed for Preisach models. A method of incorporating the MRC model in a feedforward control scheme for hysteresis compensation is also presented. Experimental studies on a 1-3 piezoceramic composite support the theoretical developments and their applicability to piezoceramics.

A generalized global adaptive tracking control scheme for robot manipulators with bounded inputs

2014 ◽  
Vol 29 (2) ◽  
pp. 180-200 ◽  
Author(s):  
Daniela J. López-Araujo ◽  
Arturo Zavala-Río ◽  
Víctor Santibáñez ◽  
Fernando Reyes
Keyword(s):  
Tracking Control ◽  
Robot Manipulators ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Control Scheme

scholarly journals Adaptive Reinforcement Learning-Enhanced Motion/Force Control Strategy for Multirobot Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Phuong Nam Dao ◽  
Duy Khanh Do ◽  
Dinh Khue Nguyen
Keyword(s):  
Reinforcement Learning ◽  
Force Control ◽  
Tracking Control ◽  
Dynamic Control ◽  
Additional Term ◽  
Control Law ◽  
Force Coefficient ◽  
Constraint Force ◽  
Control Scheme ◽  
Force Tracking

This paper presents an adaptive reinforcement learning- (ARL-) based motion/force tracking control scheme consisting of the optimal motion dynamic control law and force control scheme for multimanipulator systems. Specifically, a new additional term and appropriate state vector are employed in designing the ARL technique for time-varying dynamical systems with online actor/critic algorithm to be established by minimizing the squared Bellman error. Additionally, the force control law is designed after obtaining the computation of constraint force coefficient by the Moore–Penrose pseudo-inverse matrix. The tracking effectiveness of the ARL-based optimal control is verified in the closed-loop system by theoretical analysis. Finally, simulation studies are conducted on a system of three manipulators to validate the physical realization of the proposed optimal tracking control design.

scholarly journals Adaptive Robust Motion Control of Quadrotor Systems Using Artificial Neural Networks and Particle Swarm Optimization

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2367
Author(s):  
Hugo Yañez-Badillo ◽  
Francisco Beltran-Carbajal ◽  
Ruben Tapia-Olvera ◽  
Antonio Favela-Contreras ◽  
Carlos Sotelo ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dynamic Systems ◽  
Tracking Control ◽  
Motion Tracking ◽  
Swarm Optimization ◽  
B Spline ◽  
Control Scheme ◽  
Taylor Series Expansions ◽  
Artificial Neural

Most of the mechanical dynamic systems are subjected to parametric uncertainty, unmodeled dynamics, and undesired external vibrating disturbances while are motion controlled. In this regard, new adaptive and robust, advanced control theories have been developed to efficiently regulate the motion trajectories of these dynamic systems while dealing with several kinds of variable disturbances. In this work, a novel adaptive robust neural control design approach for efficient motion trajectory tracking control tasks for a considerably disturbed non-linear under-actuated quadrotor system is introduced. Self-adaptive disturbance signal modeling based on Taylor-series expansions to handle dynamic uncertainty is adopted. Dynamic compensators of planned motion tracking errors are then used for designing a baseline controller with adaptive capabilities provided by three layers B-spline artificial neural networks (Bs-ANN). In the presented adaptive robust control scheme, measurements of position signals are only required. Moreover, real-time accurate estimation of time-varying disturbances and time derivatives of error signals are unnecessary. Integral reconstructors of velocity error signals are properly integrated in the output error signal feedback control scheme. In addition, the appropriate combination of several mathematical tools, such as particle swarm optimization (PSO), Bézier polynomials, artificial neural networks, and Taylor-series expansions, are advantageously exploited in the proposed control design perspective. In this fashion, the present contribution introduces a new adaptive desired motion tracking control solution based on B-spline neural networks, along with dynamic tracking error compensators for quadrotor non-linear systems. Several numeric experiments were performed to assess and highlight the effectiveness of the adaptive robust motion tracking control for a quadrotor unmanned aerial vehicle while subjected to undesired vibrating disturbances. Experiments include important scenarios that commonly face the quadrotors as path and trajectory tracking, take-off and landing, variations of the quadrotor nominal mass and basic navigation. Obtained results evidence a satisfactory quadrotor motion control while acceptable attenuation levels of vibrating disturbances are exhibited.

scholarly journals Saturating Stiffness Control of Robot Manipulators with Bounded Inputs

2017 ◽  
Vol 27 (1) ◽  
pp. 79-90 ◽  
Author(s):  
María del Carmen Rodríguez-Liñán ◽  
Marco Mendoza ◽  
Isela Bonilla ◽  
César A. Chávez-Olivares
Keyword(s):  
Closed Loop ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Contact Forces ◽  
Control Law ◽  
Closed Loop System ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Stiffness Control ◽  
Three Degree Of Freedom

AbstractA saturating stiffness control scheme for robot manipulators with bounded torque inputs is proposed. The control law is assumed to be a PD-type controller, and the corresponding Lyapunov stability analysis of the closed-loop equilibrium point is presented. The interaction between the robot manipulator and the environment is modeled as spring-like contact forces.The proper behavior of the closed-loop system is validated using a three degree-of-freedom robotic arm.

Inertial and Vision Sensor Based End-Effector Sensing and Control for Robot Manipulators

2010 ◽  
Author(s):  
H. Cheng ◽  
M. Tomizuka
Keyword(s):  
Kalman Filter ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Industrial Robot ◽  
Sampling Rate ◽  
Direct Drive ◽  
End Effector ◽  
Velocity Information ◽  
Accurate Position ◽  
And Control

In the application of industrial robot manipulators, it is often desirable to obtain accurate position and velocity information regarding the end-effector. Estimations based on motor-side encoders alone are often inaccurate due to joint flexibilities and errors in the robot link kinematics. A vision based approach may also be insufficient due to its low sampling rate and image processing and transportation delay. However, with additional accelerometer measurements, a kinematic Kalman filter (KKF) can be formulated to estimate the end-effector motion accurately without encoder signals. The estimation results can be utilized for real time tracking control effectively. In this paper a multirate kinematic Kalman filter (KKF) scheme is formulated using vision and acceleration measurements from the end-effector. Estimations based on the scheme are utilized as feedback signals for tracking control. The effectiveness of the proposed approach is demonstrated by experiments on a single joint direct drive setup.

Model Tracking Control of Hamiltonian Systems

1989 ◽  
Vol 111 (4) ◽  
pp. 656-660 ◽  
Author(s):  
H. Flashner ◽  
J. M. Skowronski
Keyword(s):  
Tracking Control ◽  
Cartesian Product ◽  
Large Angle ◽  
Control Law ◽  
Simulation Studies ◽  
Control Laws ◽  
New Approach ◽  
Finite Time Horizon ◽  
Plant Simulation ◽  
Two Degree Of Freedom

A new approach is presented for deriving control laws for dynamic systems that can be formulated by Hamilton’s canonical equations. The approach uses the complete nonlinear equations of the system without requiring linearization. It is shown that the error equations, between the system and a Hamiltonian model to be followed, can be described by Hamilton’s canonical equations. Using the concept of diagonal set in the cartesian product of the system and the model states, a control law is derived using the Liapunov stability approach. The resulting control law allows tracking within a stipulated precision, and also with a finite time horizon. To demonstrate the method, a control law is derived for a two degree of freedom manipulator, designed to follow a linear plant. Simulation studies show fast convergence of the state error for a large angle motion maneuver.

Sign in / Sign up

Export Citation Format

Share Document