scholarly journals Realistic Active Haptic Guided Exploration with Cartesian Control for Force–Position Tracking in Finite Time

2006 ◽  
Vol 3 (4) ◽  
pp. 279-289 ◽  
Author(s):  
O. A. Domínguez-Ramírez ◽  
V. Parra-Vega
Keyword(s):  
Dynamic Model ◽  
Finite Time ◽  
Inverse Kinematics ◽  
Time Base ◽  
Haptic Guidance ◽  
Fast Tracking ◽  
Simultaneous Control ◽  
Guided Exploration ◽  
Basic Issue ◽  
Kinaesthetic Feedback

Perception and interaction with virtual surfaces, through kinaesthetic sensation and visual stimuli, is the basic issue of a haptic interface. When the virtual or real object is in a remote location, and guidance is required to perceive kinaesthetic feedback, a haptic guidance scheme is required. In this document, with purpose of haptic-guided exploration, a new scheme for simultaneous control of force and cartesian position is proposed without using inverse kinematics, and without using the dynamic model of PHANToM, though a strict stability analysis includes the dynamic model of PHANToM. We rely on our previously proposed results to propose a new haptic cartesian controller to reduce the burden of computing cartesian forces in PHANToM. Furthermore, a time base generator for finite-time tracking is also proposed to achieve very fast tracking and high precision, which translated into high fidelity kinaesthetic feedback.

Haptic Remote Guided Exploration of Deformable Objects

2003 ◽  
Author(s):  
Omar A. Domi´nguez-Rami´rez ◽  
Vicente Parra-Vega
Keyword(s):  
Spatial Location ◽  
Real Object ◽  
Haptic Interface ◽  
Deformable Objects ◽  
Haptic Guidance ◽  
Guided Exploration ◽  
Basic Issue ◽  
Position Controller ◽  
Remote Station ◽  
Local Station

Perception and interaction with virtual objects through kinesthetic sensation and visual stimuli is the basic issue of a haptic interface. If a real object is located at a remote station and explored (in contact) with a passive device, a haptic interface in a local station can be used to perceive its spatial and surface attributes. This is one type of haptic guidance. This problem has been addressed with undeformable object, and contact force modelled with the penalty-based method. However, this approach yields limited haptic properties of the object, and if the object is deformable, it is difficult to achieve stable contact. However, there exists relevant tasks for exploration of deformable objects, such as exploration of fruits, skin of animals and dermatological procedures. Motivated by these kind of tasks, an approach for guided remote exploration of deformable objects is proposed in this paper. A real object is explored in a remote location and object attributes and properties such as spatial location, shape, texture and roughness are perceived with a constrained Lagrangian-based decentralized force-position controller in the local station. Stable interaction is theoretical proved and experimental results using PHANToM 1.0A validate the approach.

Velocity and Force Observers for the Control of Robot Manipulators

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Marco A. Arteaga–Pérez ◽  
Juan C. Rivera–Dueñas ◽  
Alejandro Gutiérrez–Giles
Keyword(s):  
Dynamic Model ◽  
Tracking Control ◽  
Inverse Kinematics ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Asymptotical Stability ◽  
Joint Angles ◽  
Force Tracking

In this paper, position/force tracking control for rigid robot manipulators interacting with its environment is considered. It is assumed that only joint angles are available for feedback, so that velocity and force observers are designed. The principle of orthogonalization is employed for this particular purpose and some of its main properties are fully exploited to guarantee local asymptotical stability. Only the force observer requires the dynamic model of the robot manipulator for implementation, and the scheme is developed directly in workspace coordinates, so that no inverse kinematics is required. The proposed approach is tested experimentally and compared with a well–known algorithm.

scholarly journals Modeling and Finite-Time Sliding Model Control of a Lower Limb Exoskeleton for Use in Rehabilitation

2021 ◽  
Author(s):  
Uddesh Kishor Tople ◽  
Amrapali Anandkumar Khandare ◽  
Atharv Dipak Itankar ◽  
Satya Kartheek Dogga
Keyword(s):  
Dynamic Model ◽  
Lower Limb ◽  
Finite Time ◽  
Sliding Mode ◽  
Dynamic Modelling ◽  
Work Load ◽  
Modeling And Control ◽  
Lower Limb Exoskeleton ◽  
Exoskeleton Robot ◽  
Model Control

Abstract Exoskeleton systems in recent years has become a prime choice technology due to the various possibilities it can deliver. These possibilities comprise the assisting and rehabilitative techniques designed for disabled and elderly people, so that they can regain control of their limbs and in addition to this also to augment and boost the abilities of able-bodied persons during heavy work-load conditions. Many works are reported on the modeling and control of a exoskeleton robot, but very few paper discuss the complete derivation of the model of the system. Here, first the dynamic model of a physical system used as lower limb exoskeleton robot is obtained. Secondly the analysis of the system done that is derived through dynamic modelling of a 3-link robotic manipulator using Euler-Lagrange approach and validation of the corresponding model in simulation. Further, design of a finite-time SMC for desired trajectory tracking of the system is implemented. The dynamic model of the 3-link system and its control using finite-time sliding mode control are validated in MATLAB simulation environment.

scholarly journals Dynamic analysis of a five degree of freedom robotic arm using MATLAB-Simulink Simscape

2021 ◽  
Vol 343 ◽  
pp. 08004
Author(s):  
Mihai Crenganis ◽  
Alexandru Barsan ◽  
Melania Tera ◽  
Anca Chicea
Keyword(s):  
Dynamic Analysis ◽  
Dynamic Model ◽  
Inverse Kinematics ◽  
Geometric Approach ◽  
Correct Choice ◽  
Inverse Kinematic ◽  
Degree Of Freedom ◽  
Robotic Arm ◽  
Inverse Kinematic Problem ◽  
Joint Torques

In this paper, a dynamic analysis for a 5 degree of freedom (DOF) robotic arm with serial topology is presented. The dynamic model of the robot is based on importing a tri-dimensional CAD model of the robot into Simulink®-Simscape™-Multibody™. The dynamic model of the robot in Simscape is a necessary and important step in development of the mechanical structure of the robot. The correct choice of the electric motors is made according to the resistant joint torques determined by running the dynamic analysis. One can import complete CAD assemblies, including all masses, inertias, joints, constraints, and tri-dimensional geometries, into the model block. The first step for executing a dynamic analysis is to resolve the Inverse Kinematics (IK) problem for the redundant robot. The proposed method for solving the inverse kinematic problem for this type of structure is based on a geometric approach and validated afterwards using SimScape Multibody. Solving the inverse kinematics problem is a mandatory step in the dynamic analysis of the robot, this is required to drive the robot on certain user-imposed trajectories. The dynamic model of the serial robot is necessary for the simulation of motion, analysis of the robot’s structure and design of optimal control algorithms.

scholarly journals Dynamic Model and Inverse Kinematic Identification of a 3-DOF Manipulator Using RLSPSO

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 416 ◽  
Author(s):  
Josias Batista ◽  
Darielson Souza ◽  
Laurinda dos Reis ◽  
Antônio Barbosa ◽  
Rui Araújo
Keyword(s):  
Dynamic Model ◽  
Inverse Kinematics ◽  
Lagrange Equation ◽  
Computational Cost ◽  
Dynamic Parameter ◽  
Search Space ◽  
Least Square ◽  
Identification Accuracy ◽  
Identification Algorithm ◽  
Recursive Least Square

This paper presents the identification of the inverse kinematics of a cylindrical manipulator using identification techniques of Least Squares (LS), Recursive Least Square (RLS), and a dynamic parameter identification algorithm based on Particle Swarm Optimization (PSO) with search space defined by RLS (RLSPSO). A helical trajectory in the cartesian space is used as input. The dynamic model is found through the Lagrange equation and the motion equations, which are used to calculate the torque values of each joint. The torques are calculated from the values of the inverse kinematics, identified by each algorithm and from the manipulator joint speeds and accelerations. The results obtained for the trajectories, speeds, accelerations, and torques of each joint are compared for each algorithm. The computational costs as well as the Multi-Correlation Coefficient ( R 2 ) are computed. The results demonstrated that the identification accuracy of RLSPSO is better than that of LS and PSO. This paper brings an improvement in RLS because it is a method with high complexity, so the proposed method (hybrid) aims to improve the computational cost and the results of the classic RLS.

Control Design of Robotic Manipulator Based on Quantum Neural Network

2017 ◽  
Vol 140 (6) ◽  
Author(s):  
Hayder Mahdi Abdulridha ◽  
Zainab Abdullah Hassoun
Keyword(s):  
Neural Network ◽  
Dynamic Model ◽  
Pid Controller ◽  
Inverse Kinematics ◽  
Robot Manipulator ◽  
System Response ◽  
Proportional Integral Derivative ◽  
Dynamics Model ◽  
Lagrange Method ◽  
Quantum Neural Network

In this study, a control system was designed to control the robot's movement (The Mitsubishi RM-501 robot manipulator) based on the quantum neural network (QNN). A proposed method was used to solve the inverse kinematics in order to determine the angles values for the arm's joints when it follows through any path. The suggested method is the QNN algorithm. The forward kinematics was derived according to Devavit–Hartenberg representation. The dynamics model for the arm was modeled based on Lagrange method. The dynamic model is considered to be a very important step in the world of robots. In this study, two methods were used to improve the system response. In the first method, the dynamic model was used with the traditional proportional–integral–derivative (PID) controller to find its parameters (Kp, Ki, Kd) by using Ziegler Nichols method. In the second method, the PID parameters were selected depending on QNN without the need to a mathematical model of the robot manipulator. The results show a better response to the system when replacing the traditional PID controller with the suggested controller.

scholarly journals Model-Free High Order Sliding Mode Control with Finite-Time Tracking for Unmanned Underwater Vehicles

2021 ◽  
Vol 11 (4) ◽  
pp. 1836
Author(s):  
Josué González-García ◽  
Néstor Alejandro Narcizo-Nuci ◽  
Luis Govinda García-Valdovinos ◽  
Tomás Salgado-Jiménez ◽  
Alfonso Gómez-Espinosa ◽  
...  
Keyword(s):  
Neural Network ◽  
Power Consumption ◽  
Finite Time ◽  
Sliding Mode ◽  
Underwater Vehicles ◽  
High Order ◽  
Time Base ◽  
Unmanned Underwater Vehicles ◽  
Finite Time Convergence ◽  
Model Free

Several strategies to deal with the trajectory tracking problem of Unmanned Underwater Vehicles are encountered, from traditional controllers such as Proportional Integral Derivative (PID) or Lyapunov-based, to backstepping, sliding mode, and neural network approaches. However, most of them are model-based controllers where it is imperative to have an accurate knowledge of the vehicle hydrodynamic parameters. Despite some sliding mode and neural network-based controllers are reported as model-free, just a few of them consider a solution with finite-time convergence, which brings strong robustness and fast convergence compared with asymptotic or exponential solutions and it can also help to reduce the power consumption of the vehicle thrusters. This work aims to implement a model-free high-order sliding-mode controller and synthesize it with a time-base generator to achieve finite-time convergence. The time-base was included by parametrizing the control gain at the sliding surface. Numerical simulations validated the finite-time convergence of the controller for different time-bases even in the presence of high ocean currents. The performance of the obtained solution was also evaluated by the Root Mean Square (RMS) value of the control coefficients computed for the thrusters, as a parameter to measure the power consumption of the vehicle when following a trajectory. Computational results showed a reduction of up to 50% in the power consumption from the thrusters when compared with other solutions.

scholarly journals A Novel Active Fault-Tolerant Tracking Control for Robot Manipulators with Finite-Time Stability

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8101
Author(s):  
Thanh Nguyen Truong ◽  
Anh Tuan Vo ◽  
Hee-Jun Kang ◽  
Mien Van
Keyword(s):  
Dynamic Model ◽  
Finite Time ◽  
Tracking Control ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Lyapunov Theory ◽  
Control Input ◽  
Observation Error ◽  
Simulation Performance

Many terminal sliding mode controllers (TSMCs) have been suggested to obtain exact tracking control of robotic manipulators in finite time. The ordinary method is based on TSMCs that secure trajectory tracking under the assumptions such as the known robot dynamic model and the determined upper boundary of uncertain components. Despite tracking errors that tend to zero in finite time, the weakness of TSMCs is chattering, slow convergence speed, and the need for the exact robot dynamic model. Few studies are handling the weakness of TSMCs by using the combination between TSMCs and finite-time observers. In this paper, we present a novel finite-time fault tolerance control (FTC) method for robotic manipulators. A finite-time fault detection observer (FTFDO) is proposed to estimate all uncertainties, external disturbances, and faults accurately and on time. From the estimated information of FTFDO, a novel finite-time FTC method is developed based on a new finite-time terminal sliding surface and a new finite-time reaching control law. Thanks to this approach, the proposed FTC method provides a fast convergence speed for both observation error and control error in finite time. The operation of the robot system is guaranteed with expected performance even in case of faults, including high tracking accuracy, small chattering behavior in control input signals, and fast transient response with the variation of disturbances, uncertainties, or faults. The stability and finite-time convergence of the proposed control system are verified that they are strictly guaranteed by Lyapunov theory and finite-time control theory. The simulation performance for a FARA robotic manipulator proves the proposed control theory’s correctness and effectiveness.

scholarly journals 3D Trajectory Control of Flexible Manipulator

2020 ◽  
Author(s):  
Minoru Sasaki ◽  
Daiki Maeno ◽  
Jackline Asango ◽  
Wweru Njeri ◽  
Kojiro Matsushita ◽  
...  
Keyword(s):  
Vibration Control ◽  
Inverse Kinematics ◽  
Trajectory Control ◽  
Flexible Manipulator ◽  
Joint Angles ◽  
Position Accuracy ◽  
Simultaneous Control ◽  
Controller Performance ◽  
Tip Position ◽  
The Ideal

This paper describes the development of a controller that enables trajectory control and vibration control. The controller performance was verified the using a 3D 2-link, flexible manipulator. On trajectory control using inverse kinematics, it was confirmed that the deflection due to its own weight deteriorated the track following performance. The vibration component of the resonance frequency of the flexible manipulator was generated, and the tip position accuracy is deteriorated. Using the results of control experiments based on the inverse kinematics, the system is identified and then created an inverse system for simultaneous control of trajectory control and vibration control. The target trajectories were the three joint angles. Finally, it was demonstrated through experiments on actual manipulator, that the system could sufficiently follow the ideal trajectory and suppress link vibrations.

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