scholarly journals Distributed Synchronization Control to Trajectory Tracking of Multiple Robot Manipulators

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Yassine Bouteraa ◽  
Jawhar Ghommam ◽  
Gérard Poisson ◽  
Nabil Derbel
Keyword(s):  
Decentralized Control ◽  
Information Exchange ◽  
Robot Manipulators ◽  
Direct Method ◽  
Functional Method ◽  
Consensus Algorithm ◽  
Adaptive Synchronization ◽  
Synchronization Control ◽  
Control Law ◽  
Parameter Uncertainties

This paper investigates the issue of designing decentralized control laws to cooperatively command a team of general fully actuated manipulators. The purpose is to synchronize their movements while tracking a common desired trajectory. Based on the well-known consensus algorithm, the control strategy consists in synchronizing the joint position and the velocity of each robot in the network with respect to neighboring robots' joints and velocities. Modeled by an undirected graph, the cooperative robot network requires just local neighbor-to-neighbor information exchange between manipulators. So, it does not assume the existence of an explicit leader in the team. Based above all on combination of Lyapunov direct method and cross-coupling strategy, the proposed decentralized control law is extended to an adaptive synchronization control taking into account parameter uncertainties. To address the time delay problems in the network communication channels, the suggested synchronization control law robustly synchronizes robots to track a given trajectory. To this end, Krasovskii functional method has been used to deal with the delay-dependent stability problem. A real-time software simulator is developed to visualize the robot manipulators coordination.

Decentralized Exergy/Entropy Thermodynamic Control for Collective Robotic Systems

2007 ◽  
Author(s):  
Rush D. Robinett ◽  
David G. Wilson
Keyword(s):  
Decentralized Control ◽  
Direct Method ◽  
Robotic Systems ◽  
Control Law ◽  
Thermodynamic Control ◽  
Order Accuracy ◽  
Control Laws ◽  
Vector Lyapunov Function ◽  
Collective Control ◽  
Plume Tracing

This paper develops a distributed decentralized control law for collective robotic systems. The control laws are developed based on exergy/entropy thermodynamic concepts and information theory. The source field is characterized through second-order accuracy. The proposed feedback control law stability for both the collective and individual robots are demonstrated by selecting a general Hamiltonian based solution developed as Fisher Information Equivalency as the vector Lyapunov function. Stability boundaries and system performance are then determined with Lyapunov’s direct method. A robot collective plume tracing numerical simulation example demonstrates this decentralized exergy/entropy collective control architecture.

Spacecraft Attitude and Orbit Coupled Nonlinear Adaptive Synchronization Control

2011 ◽  
Vol 327 ◽  
pp. 6-11
Author(s):  
Yu Jia Tie ◽  
Wei Yang ◽  
Hao Yu Tan
Keyword(s):  
Dynamic Model ◽  
Dynamic Models ◽  
Direct Method ◽  
Adaptive Synchronization ◽  
Synchronization Control ◽  
Nonlinear Dynamic Model ◽  
Asymptotic Stable ◽  
Nonlinear Relative Motion ◽  
Attitude Dynamic ◽  
Coupling Dynamic

Precise dynamic model of spacecraft is essential for the space missions, to be completed successfully. Nevertheless, the independent orbit or attitude dynamic models can not meet high precision tasks. This paper developed a 6-DOF relative coupling dynamic model based upon the nonlinear relative motion dynamics equations and attitude kinematics equations described by MRP. Nonlinear synchronization control law was designed for the coupled nonlinear dynamic model, whose close-loop system was proved to be global asymptotic stable by Lyapunov direct method. Finallly, the simulation results illustrate that the nonlinear adaptive synchronization control algorithm can robustly drive the orbit and attitude errors to converge to zero.

Consensus in networks of uncertain robot manipulators without using neighbors’ velocity information

Robotica ◽  
2021 ◽  
pp. 1-17
Author(s):  
Seyed Mostafa Almodarresi ◽  
Marzieh Kamali ◽  
Farid Sheikholeslam
Keyword(s):  
Information Exchange ◽  
Lyapunov Functions ◽  
Robot Manipulators ◽  
Adaptive Methods ◽  
Convergence Time ◽  
Parameter Search ◽  
Velocity Information ◽  
Simulation Results ◽  
Uncertain Robot ◽  
Asymptotic Synchronization

Abstract In this paper, new distributed adaptive methods are proposed for solving both leaderless and leader–follower consensus problems in networks of uncertain robot manipulators, by estimating only the gravitational torque forces. Comparing with the existing adaptive methods, which require the estimation of the whole dynamics, presented methods reduce the excitation levels required for efficient parameter search, the convergence time, and the complexity of the regressor. Additionally, proposed schemes eliminate the need for velocity information exchange between the agents. Global asymptotic synchronization is shown by introducing new Lyapunov functions. Simulation results are provided for a network of 10 4-DOF robot manipulators.

scholarly journals Position Domain Synchronization Control For Robotic Manipulators

2021 ◽  
Author(s):  
Vangjel Pano
Keyword(s):  
Time Domain ◽  
Robotic Manipulators ◽  
Synchronization Control ◽  
Control Law ◽  
Control Input ◽  
Contour Tracking ◽  
Hybrid Controller ◽  
Reference Motion ◽  
Control Scheme ◽  
Control Schemes

Developed in this thesis is a new control law focusing on the improvement of contour tracking of robotic manipulators. The new control scheme is a hybrid controller based on position domain control (PDC) and position synchronization control (PSC). On PDC, the system’s dynamics are transformed from time domain to position domain via a one-to-one mapping and the position of the master axis motion is used as reference instead of time. The elimination of the reference motion from the control input improves contouring performance relative to time domain controllers. Conversely, PSC seeks to reduce the error of the systems by diminishing the synchronization error between each agent of the system. The new control law utilizes the aforementioned techniques to maximize the contour performance. The Lyapunov method was used to prove the proposed controller’s stability. The new control law was compared to existing control schemes via simulations of linear and nonlinear contours, and was shown to provide good tracking and contouring performances.

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