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.

Adaptive visual servoing scheme free of image velocity measurement for uncertain robot manipulators

Automatica ◽  
2013 ◽  
Vol 49 (5) ◽  
pp. 1304-1309 ◽  
Author(s):  
Fernando Lizarralde ◽  
Antonio C. Leite ◽  
Liu Hsu ◽  
Ramon R. Costa
Keyword(s):  
Velocity Measurement ◽  
Visual Servoing ◽  
Robot Manipulators ◽  
Image Velocity ◽  
Uncertain Robot

scholarly journals Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Rong Mei ◽  
ChengJiang Yu
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Disturbance Observer ◽  
Robot Manipulators ◽  
External Disturbance ◽  
Input Saturation ◽  
Output Feedback Control ◽  
System State ◽  
Control Scheme ◽  
Uncertain Robot

This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN) and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.

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.

Second-Order Sliding Mode Control of a Perturbed-Crane

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Carlos Vázquez ◽  
Leonid Fridman ◽  
Joaquin Collado ◽  
Ismael Castillo
Keyword(s):  
Lyapunov Functions ◽  
Pid Controller ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Second Order ◽  
Convergence Time ◽  
Model Description ◽  
External Perturbations ◽  
Wide Range ◽  
Second Order Sliding Mode

A five degrees-of-freedom overhead crane system affected by external perturbations is the topic of study. Existing methods just handle the unperturbed case or, in addition, the analysis is limited to three or two degrees-of-freedom. A wide range of processes cannot be restricted to these scenarios and this paper goes a step forward proposing a control solution for a five degrees-of-freedom system under the presence of matched and unmatched disturbances. The contribution includes a model description and a second-order sliding mode (SOSM) control design ensuring the precise trajectory tracking for the actuated variables and at the same time the regulation of the unactuated variables. Furthermore, the proposed approach is supported by the design of strong Lyapunov functions providing an estimation of the convergence time. Simulations and experiments, including a comparison with a proportional-integral-derivative (PID) controller, verified the advantages of the methodology.

Cellular Differential Evolution for Optimization

2011 ◽  
Vol 474-476 ◽  
pp. 1770-1775
Author(s):  
Gui Wu Hu ◽  
Xiao Yong Du
Keyword(s):  
Cellular Automata ◽  
Differential Evolution ◽  
Information Exchange ◽  
Cellular Structure ◽  
Mutation Operator ◽  
Solution Quality ◽  
Base Vector ◽  
Quality Stability ◽  
Simulation Results ◽  
And Diffusion

This paper is to illustrate the Cellular Differential Evolution with the cellular structure originated from Cellular automata. Cellular neighbor local search has been designed; base vector or global best in mutation operator is substituted by neighborhood-best, which overcomes the weakness of single selection relating to global best, and balances the contradiction of local and global search, and improves the diversity of population. In addition, cellular structure ensures information exchange, inheritance and diffusion. Finally, a specific algorithm has been implemented: compared with similar variants of DE, the simulation results on 9 benchmark functions demonstrate that cellular differential evolutions are provided with obvious advantages in the solution-quality, stability and speed. <b></b>

scholarly journals Chaos Synchronization between Fractional-Order Unified Chaotic System and Rossler Chaotic System

2012 ◽  
Vol 562-564 ◽  
pp. 2088-2091
Author(s):  
Xian Yong Wu ◽  
Yi Long Cheng ◽  
Kai Liu ◽  
Xin Liang Yu ◽  
Xian Qian Wu
Keyword(s):  
Fractional Order ◽  
Chaotic System ◽  
Chaos Synchronization ◽  
Chaotic Dynamics ◽  
Chaotic Attractors ◽  
System Parameters ◽  
Unified Chaotic System ◽  
Simulation Results ◽  
Drive Systems ◽  
Asymptotic Synchronization

The chaotic dynamics of the unified chaotic system and the Rossler system with different fractional-order are studied in this paper. The research shows that the chaotic attractors can be found in the two systems while the orders of the systems are less than three. Asymptotic synchronization of response and drive systems is realized by active control through designing proper controller when system parameters are known. Theoretical analysis and simulation results demonstrate the effective of this method.

Some Interpretations Of Self-Tuning Pid Controllers

1994 ◽  
pp. 27-42
Author(s):  
Rubiyah Yusof ◽  
Marzuki Khalid ◽  
Sigeru Omatu
Keyword(s):  
Adaptive Methods ◽  
Pid Controllers ◽  
Adaptive Controllers ◽  
Tuning Parameters ◽  
Self Tuning ◽  
Simulation Results ◽  
Insight Into ◽  
Selection Of

One of the most recent development in the theories of adaptive methods in the form of self-tuning algorithms is in the area of self-tuning PID controllers (STPID). These controllers are a class of adaptive controllers but are essentially PID controllers with the capabilities of tuning their parameters automatically online. To this end, the theories of these types of controllers are still in the infancy stage. In this paper, we provide some interpretations of a STPID through some analytical and simulation results, thereby lending way for a better understanding of the algorithms and some insight into the usefullness of the algorithm. The interpretations also serve as an aid in the selection of the tuning parameters of this algorithm which can be a time consuming activity if done dilligently.

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