scholarly journals Robust and fault tolerant control of modular and reconfigurable robots

2021 ◽  
Author(s):  
Sajan Abdul

Modular and reconfigurable robot has been one of the main areas of robotics research in recent years due to its wide range of applications, especially in aerospace sector. Dynamic control of manipulators can be performed using joint torque sensing with little information of the link dynamics. From the modular robot perspective, this advantage offered by the torque sensor can be taken to enhance the modularity of the control system. Known modular robots though boast novel and diverse mechanical design on joint modules in one way or another, they still require the whole robot dynamic model for motion control, and modularity offered in the mechanical side does not offer any advantage in the control design. In this work, a modular distributed control technique is formulated for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under this control methodology, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need of re-tuning the controller. Model uncertainties associated with load and links are compensated by the use of joint torque sensors. Other model uncertainties at each joint module are compensated by a decomposition based robust controller for each module. The proposed distributed control technique offers a ‘modular’ approach, featuring a unique joint-by-joint control synthesis of the joint modules. Fault tolerance and fault detection are formulated as a decentralized control problem for modular and reconfigurable robots in this thesis work. The modularity of the system is exploited to derive a strategy dependent only on a single joint module, while eliminating the need for the motion states of other joint modules. While the traditional fault tolerant and detection schemes are suitable for robots with the whole dynamic model, this proposed technique is ideal for modular and reconfigurable robots because of its modular nature. The proposed methods have been investigated with simulations and experimentally tested using a 3-DOF modular and reconfigurable robot.

2021 ◽  
Author(s):  
Sajan Abdul

Modular and reconfigurable robot has been one of the main areas of robotics research in recent years due to its wide range of applications, especially in aerospace sector. Dynamic control of manipulators can be performed using joint torque sensing with little information of the link dynamics. From the modular robot perspective, this advantage offered by the torque sensor can be taken to enhance the modularity of the control system. Known modular robots though boast novel and diverse mechanical design on joint modules in one way or another, they still require the whole robot dynamic model for motion control, and modularity offered in the mechanical side does not offer any advantage in the control design. In this work, a modular distributed control technique is formulated for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under this control methodology, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need of re-tuning the controller. Model uncertainties associated with load and links are compensated by the use of joint torque sensors. Other model uncertainties at each joint module are compensated by a decomposition based robust controller for each module. The proposed distributed control technique offers a ‘modular’ approach, featuring a unique joint-by-joint control synthesis of the joint modules. Fault tolerance and fault detection are formulated as a decentralized control problem for modular and reconfigurable robots in this thesis work. The modularity of the system is exploited to derive a strategy dependent only on a single joint module, while eliminating the need for the motion states of other joint modules. While the traditional fault tolerant and detection schemes are suitable for robots with the whole dynamic model, this proposed technique is ideal for modular and reconfigurable robots because of its modular nature. The proposed methods have been investigated with simulations and experimentally tested using a 3-DOF modular and reconfigurable robot.


Robotica ◽  
2008 ◽  
Vol 26 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Guangjun Liu ◽  
Sajan Abdul ◽  
Andrew A. Goldenberg

SUMMARYA major technical challenge in controlling modular and reconfigurable robots is associated with the kinematics and dynamic model uncertainties caused by reconfiguration. In parallel, conventional model uncertainties such as uncompensated joint friction still persist. This paper presents a modular distributed control technique for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under the proposed control method that is based on joint torque sensing, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need to adjust control parameters of the other modules of the robot. Model uncertainties associated with link and payload masses are compensated using joint torque sensor measurement. The remaining model uncertainties, including uncompensated dynamic coupling and joint friction, are compensated by a decomposition-based robust controller. Simulation results have confirmed the effectiveness of the proposed method.


2021 ◽  
Vol 11 (12) ◽  
pp. 5468
Author(s):  
Elizaveta Shmalko ◽  
Askhat Diveev

The problem of control synthesis is considered as machine learning control. The paper proposes a mathematical formulation of machine learning control, discusses approaches of supervised and unsupervised learning by symbolic regression methods. The principle of small variation of the basic solution is presented to set up the neighbourhood of the search and to increase search efficiency of symbolic regression methods. Different symbolic regression methods such as genetic programming, network operator, Cartesian and binary genetic programming are presented in details. It is shown on the computational example the possibilities of symbolic regression methods as unsupervised machine learning control technique to the solution of MLC problem of control synthesis for obtaining the stabilization system for a mobile robot.


2021 ◽  
Vol 01 (01) ◽  
pp. 2150001
Author(s):  
Jianye Gong ◽  
Yajie Ma ◽  
Bin Jiang ◽  
Zehui Mao

In this paper, the adaptive fault-tolerant formation tracking control problem for a set of heterogeneous unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) systems with actuator loss of effectiveness faults is investigated. The cooperative fault-tolerant formation control strategy for UAV and UGV collaborative systems is classified into the altitude consensus control scheme for follower UAVs and the position cooperative formation control scheme for all followers. The altitude consensus control algorithm is designed by utilizing backstepping control technique to drive all UAVs to a desired predefined height. Then, based on synchronization formation error information, the position cooperative formation control algorithm is proposed for all followers to reach the expected position and perform the desired formation configuration. The adaptive fault estimation term is adopted in the designed fault-tolerant formation control algorithm to compensate for the actuator loss of effectiveness fault. Finally, a simulation example is proposed to reveal the validity of the designed cooperative formation tracking control scheme.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wei Jiang ◽  
Yating Shi ◽  
Dehua Zou ◽  
Hongwei Zhang ◽  
Hong Jun Li

Purpose The purpose of this paper is to achieve the optimal system design of a four-wheel mobile robot on transmission line maintenance, as the authors know transmission line mobile robot is a kind of special robot which runs on high-voltage cable to replace or assist manual power maintenance operation. In the process of live working, the manipulator, working end effector and the working environment are located in the narrow space and with heterogeneous shapes, the robot collision-free obstacle avoidance movement is the premise to complete the operation task. In the simultaneous operation, the mechanical properties between the manipulator effector and the operation object are the key to improve the operation reliability. These put forward higher requirements for the mechanical configuration and dynamic characteristics of the robot, and this is the purpose of the manuscript. Design/methodology/approach Based on the above, aiming at the task of tightening the tension clamp for the four-split transmission lines, the paper proposed a four-wheel mobile robot mechanism configuration and its terminal tool which can adapt to the walking and operation on multi-split transmission lines. In the study, the dynamic models of the rigid robot and flexible transmission line are established, respectively, and the dynamic model of rigid-flexible coupling system is established on this basis, the working space and dynamic characteristics of the robot have been simulated in ADAMS and MATLAB. Findings The research results show that the mechanical configuration of this robot can complete the tightening operation of the four-split tension clamp bolts and the motion of robot each joint meets the requirements of driving torque in the operation process, which avoids the operation failure of the robot system caused by the insufficient or excessive driving force of the robot joint torque. Originality/value Finally, the engineering practicability of the mechanical configuration and dynamic model proposed in the paper has been verified by the physical prototype. The originality value of the research is that it has double important theoretical significance and practical application value for the optimization of mechanical structure parameters and electrical control parameters of transmission line mobile robots.


2018 ◽  
Vol 2018 ◽  
pp. 1-26
Author(s):  
Ying He ◽  
Jiangping Mei ◽  
Zhiwei Fang ◽  
Fan Zhang ◽  
Yanqin Zhao

Palletizing robot is widely used in logistics operation. At present, people pay attention to not only the loading capacity and working efficiency of palletizing robots, but also the energy consumption in their working process. This paper takes MD1200-YJ palletizing robot as the research object and studies the problem of low energy consumption optimization of joint driving system from the perspective of trajectory optimization. Firstly, a multifactor dynamic model of palletizing robot is established based on the conventional inverse rigid body dynamic model of the robot, the Stribeck friction model and the spring balance torque model. And then based on joint torque, friction torque, motion parameter, and joule’s law, the useful work model, thermal loss model of joint motor, friction energy consumption model of joint system, and total energy consumption model of palletizing robot are established, and through simulation and experiment, the correctness of the multifactor dynamic model and energy consumption model is verified. Secondly, based on the Fourier series approximation method to construct the joint trajectory expression, the minimum total energy consumption as the optimization objective, with coefficients of Fourier series as optimization variables, the motion parameters of initial and final position, and running time constant as constraint conditions, the genetic algorithm is used to solve the optimization problem. Finally, through the simulation analysis the optimized Fourier series motion law and the 3-4-5 polynomial motion law are comprehensively evaluated to verify the effectiveness of the optimization method. Moreover, it provides the theoretical basis for the follow-up research and points out the direction of improvement.


2019 ◽  
Vol 21 (3) ◽  
pp. 92-102
Author(s):  
Kaidi Li ◽  
Chunyang Chen ◽  
Shu Cheng ◽  
Tianjian Yu ◽  
Chaoqun Xiang ◽  
...  

Author(s):  
Farhad Aghili

The paper presents a new paradigm and conceptual design for reconfigurable robots. Unlike conventional reconfigurable robots, our design doesn't achieve reconfigurability by utilizing modular joints. But the robot is equipped with passive joints, i.e. joints with no actuator or sensor, which permit changing the Denavit-Hartenberg (DV) parameters such as the arm length, and the twist angle. The passive joints are controllable when the robot forms a closed kinematic chain. Also each passive joint is equipped with a built-in brake mechanism which is normally locked but it can be released whenever changing of the parameters is required. Kinematics analysis of such a robot plus control synthesis and mechanical design of the brake mechanism are described.


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