scholarly journals A Novel Modified Super-Twisting Control Augmented Feedback Linearization for Wearable Robotic Systems Using Time Delay Estimation

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 597
Author(s):  
Brahim Brahmi ◽  
Ibrahim El Bojairami ◽  
Tanvir Ahmed ◽  
Asif Al Zubayer Swapnil ◽  
Mohammad AssadUzZaman ◽  
...  
Keyword(s):  
Time Delay ◽  
Feedback Linearization ◽  
High Performance ◽  
Time Delay Estimation ◽  
Robotic Systems ◽  
External Disturbances ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
Twisting Control ◽  
Dynamics Stability

The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system’s errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller’s efficiency given its uncertain nonlinear dynamics and the external disturbances involved.

Passive and active rehabilitation control of human upper-limb exoskeleton robot with dynamic uncertainties

Robotica ◽  
2018 ◽  
Vol 36 (11) ◽  
pp. 1757-1779 ◽  
Author(s):  
Brahim Brahmi ◽  
Maarouf Saad ◽  
Cristobal Ochoa Luna ◽  
Philippe S. Archambault ◽  
Mohammad H. Rahman
Keyword(s):  
Time Delay ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Stability And Convergence ◽  
External Disturbances ◽  
Upper Limb Exoskeleton ◽  
Uncertain Dynamics ◽  
Exoskeleton Robot ◽  
Active Rehabilitation ◽  
The Impact

SUMMARYThis paper investigates the passive and active control strategies to provide a physical assistance and rehabilitation by a 7-DOF exoskeleton robot with nonlinear uncertain dynamics and unknown bounded external disturbances due to the robot user's physiological characteristics. An Integral backstepping controller incorporated with Time Delay Estimation (BITDE) is used, which permits the exoskeleton robot to achieve the desired performance of working under the mentioned uncertainties constraints. Time Delay Estimation (TDE) is employed to estimate the nonlinear uncertain dynamics of the robot and the unknown disturbances. To overcome the limitation of the time delay error inherent of the TDE approach, a recursive algorithm is used to further reduce its effect. The integral action is employed to decrease the impact of the unmodeled dynamics. Besides, the Damped Least Square method is introduced to estimate the desired movement intention of the subject with the objective to provide active rehabilitation. The controller scheme is to ensure that the robot system performs passive and active rehabilitation exercises with a high level of tracking accuracy and robustness, despite the unknown dynamics of the exoskeleton robot and the presence of unknown bounded disturbances. The design, stability, and convergence analysis are formulated and proven based on the Lyapunov–Krasovskii functional theory. Experimental results with healthy subjects, using a virtual environment, show the feasibility, and ease of implementation of the control scheme. Its robustness and flexibility to deal with parameter variations due to the unknown external disturbances are also shown.

scholarly journals A Novel Adaptive Super-Twisting Sliding Mode Control Scheme with Time-Delay Estimation for a Single Ducted-Fan Unmanned Aerial Vehicle

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 54
Author(s):  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Unmanned Aerial Vehicle ◽  
Sliding Mode ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Mode Control ◽  
Ducted Fan ◽  
Control Scheme ◽  
Aerial Vehicle

This article proposes a novel adaptive super-twisting sliding mode control scheme with a time-delay estimation technique (ASTSMC-TDE) to control the yaw angle of a single ducted-fan unmanned aerial vehicle system. Such systems are highly nonlinear; hence, the proposed control scheme is a combination of several control schemes; super-twisting sliding mode, TDE technique to estimate the nonlinear factors of the system, and an adaptive sliding mode. The tracking error of the ASTSMC-TDE is guaranteed to be uniformly ultimately bounded using Lyapunov stability theory. Moreover, to enhance the versatility and the practical feasibility of the proposed control scheme, a comparison study between the proposed controller and a proportional-integral-derivative controller (PID) is conducted. The comparison is achieved through two different scenarios: a normal mode and an abnormal mode. Simulation and experimental tests are carried out to provide an in-depth investigation of the performance of the proposed ASTSMC-TDE control system.

Robust Guidance Control for Nonholonomic AGV Based on First Order Dynamic Sliding Mode Techniques

2013 ◽  
Vol 709 ◽  
pp. 583-588
Author(s):  
Jin Hua Ye ◽  
Di Li ◽  
Shi Yong Wang ◽  
Feng Ye
Keyword(s):  
High Performance ◽  
Sliding Mode ◽  
Path Following ◽  
Lyapunov Theory ◽  
External Disturbances ◽  
Guidance Control ◽  
First Order ◽  
Control Scheme ◽  
The Impact ◽  
Dynamic Sliding Mode

This paper develops a high performance guidance controller for automated guided vehicle (AGV) with nonholonomic constraint. In this controller, the path following method in the Serret-Frenet frame is used for driving the AGV onto a predefined path at a constant forward speed. Moreover, a first order dynamic sliding mode controller is proposed, not only to overcome the impact of unknown model uncertainties and external disturbances of the system, but also to weaken the chattering in the standard sliding mode control. The global asymptotic stability and robustness of the system is proven by the Lyapunov theory and LaSalles invariance principle. Simulation results show the validity of the proposed guidance control scheme.

scholarly journals Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Jinzhu Peng ◽  
Zeqi Yang ◽  
Tianlei Ma
Keyword(s):  
Neural Network ◽  
Impedance Control ◽  
Tracking Error ◽  
Tracking Performance ◽  
Robotic Systems ◽  
Position Tracking ◽  
External Disturbances ◽  
Outer Loop ◽  
Control Scheme ◽  
Force Tracking

In this paper, an adaptive Jacobian and neural network based position/force tracking impedance control scheme is proposed for controlling robotic systems with uncertainties and external disturbances. To achieve precise force control performance indirectly by using the position tracking, the control scheme is divided into two parts: the outer-loop force impedance control and the inner-loop position tracking control. In the outer-loop, an improved impedance controller, which combines the traditional impedance relationship with the PID-like scheme, is designed to eliminate the force tracking error quickly and to reduce the force overshoot effectively. In this way, the satisfied force tracking performance can be achieved when the manipulator contacts with environment. In the inner-loop, an adaptive Jacobian method is proposed to estimate the velocities and interaction torques of the end-effector due to the system kinematical uncertainties, and the system dynamical uncertainties and the uncertain term of adaptive Jacobian are compensated by an adaptive radial basis function neural network (RBFNN). Then, a robust term is designed to compensate the external disturbances and the approximation errors of RBFNN. In this way, the command position trajectories generated from the outer-loop force impedance controller can be then tracked so that the contact force tracking performance can be achieved indirectly in the forced direction. Based on the Lyapunov stability theorem, it is proved that all the signals in closed-loop system are bounded and the position and velocity errors are asymptotic convergence to zero. Finally, the validity of the control scheme is shown by computer simulation on a two-link robotic manipulator.

Active fault-tolerant control of a Schon̈flies parallel manipulator based on time delay estimation

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Pegah Ghaf-Ghanbari ◽  
Mahmood Mazare ◽  
Mostafa Taghizadeh
Keyword(s):  
Time Delay ◽  
Feedback Linearization ◽  
Parallel Manipulator ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Fault Tolerant Control ◽  
Time Delay Estimation ◽  
Lyapunov Theory ◽  
Delay Estimation ◽  
Fault Estimation

Abstract In this paper, a new hybrid fault-tolerant control (FTC) strategy based on nonsingular fast integral-type terminal sliding mode (NFITSM) and time delay estimation (TDE) is proposed for a Schönflies parallel manipulator. In order to detect, isolate, and accommodate actuator faults, TDE is used as an online fault estimation algorithm. Stability analysis of the closed-loop system is performed using Lyapunov theory. The proposed controller performance is compared with conventional sliding mode and feedback linearization control methods. The obtained results reveal the superiority of the proposed FTC based on TDE and NFITSM.

scholarly journals Robust Finite-Time Tracking Control for Robotic Manipulators with Time Delay Estimation

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 165
Author(s):  
Tie Zhang ◽  
Aimin Zhang
Keyword(s):  
Time Delay ◽  
Finite Time ◽  
Robotic Manipulators ◽  
High Gain ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Closed Loop System ◽  
External Disturbances ◽  
Estimation Errors ◽  
Theorem Proof

In this study, a robust H∞ finite-time tracking controller is proposed for robotic manipulators based on time delay estimation. In this controller, there is no need to know the dynamics of robots, so it is quite simple. The high-gain observer is employed to estimate the joint velocities, which makes it much lower in cost. The theorem proof shows that the closed-loop system is finite-time stable and has a L2 gain that is less than or equal to γ, which shows high accuracy and strong robustness to estimation errors and external disturbances. Simulations on a two-link robot illustrate the effectiveness and advantages of the proposed controllers.

scholarly journals Adaptive RBF -SMC control for multi-point mooring system

2022 ◽  
Vol 355 ◽  
pp. 03063
Author(s):  
Run Lu ◽  
Guichen Zhang ◽  
Jianqiang Shi
Keyword(s):  
Pid Controller ◽  
Lyapunov Method ◽  
Sliding Mode ◽  
Mooring System ◽  
Control Parameters ◽  
External Disturbances ◽  
Dynamic Changes ◽  
Hybrid Controller ◽  
Uncertain Dynamics ◽  
Control Scheme

A stable adaptive control scheme for multi-point mooring system (MPMS) with uncertain dynamics is proposed in this paper. The control scheme is designed by a hybrid controller based on RBF (Radial Basis Function) NN (Neural Network) and SMC (Sliding Mode Control), which learns the MPMS dynamic changes, and the compensation of external disturbances is realized through adaptive RBFNN control. Meanwhile the RBF-SMC control parameters are adapted by the Lyapunov method to minimize squares dynamic positioning (DP) error. The convergence of the hybrid controller is proved theoretically, and the proposed mooring control scheme is applied to the “Kantan3” mooring simulation system. Finally, the simulation results are compared with the traditional PID controller and standard RBF controller to demonstrate the effective mooring positioning performance of the control scheme for the MPMS.

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