Fuzzy-Based Fixed-Time Nonsingular Tracker of Exoskeleton Robots for Disabilities Using Sliding Mode State Observer

Abstract

In this article, the position tracking control of the wheelchair upper-limb exoskeleton robotic system is investigated with the aim of rehabilitation of disabled people. Hence, the fuzzy nonsingular terminal sliding mode control method by using the state observer with a fixed-time convergence rate is designed in three main parts. In the first part, the fixed-time state observer is proposed for estimation of the states of the system. Secondly, the fixed-time convergence of position tracking error of the upper-limb exoskeleton robot system is examined by using the nonsingular terminal sliding mode control approach. In the third part, with the target of the improvement of the controller performance for removal of the chattering phenomenon which diminishes the controller performance, the fuzzy control method is used. Finally, the efficiency and proficiency of the proposed control method on the upper limb exoskeleton robotic system are demonstrated via the simulation results which are provided by MATLAB/Simulink software. In this part, simulation results are obtained based on different initial conditions in two examples using various desired values. Thus, it can be demonstrated that the proposed method applied to the upper-limb exoskeleton robot system is robust under various initial conditions and desired values.

Constrained Nonsingular Terminal Sliding Mode Attitude Control for Spacecraft: A Funnel Control Approach

“…To this end, at a close vicinity of χ = 0, then Λ = Ω = Ψ = 0 and S = x 1 will be obtained. Based on the definition of µ v (Λ) in (22), when…”

“…Therefore, an exact estimate of the settling time cannot be acquired. In comparison with the control schemes derived from this concept [14][15][16][17][18][19], control laws using the fixed-time stability lead to finite-time convergence of the system states regardless of their initial value [20][21][22]. The significant feature which distinguishes fixed-time control from its finite-time counterpart is that the settling time for the closed-loop system is specified based on the controller gains.…”

High Accuracy Human Motion Trajectory Generation for Exoskeleton Robot Using Curve Fitting Technique

“…( 7) to ( 9), there are six boundary constraints (starting position, 𝜃 0 , ending position, 𝜃 𝑓 , starting velocity, 𝑣 0 , ending velocity, 𝑣 0 , starting acceleration, 𝑠 0 and ending acceleration, 𝑠 𝑓 ) of a quintic polynomial as shown in Eq. (10), that needs to be determined.…”

“…It has the capability to produce the trajectory according to the working space environment. The implementation of Neural Network [9] and Fuzzy Logic [10] attached with an additional sensor [11,12] is used to improve the accuracy of the generating trajectory. However, this strategy must consider issues such as the fastest time adapting for real-time application and accuracy.…”

Design of robust adaptive fuzzy control for uncertain bilateral teleoperation systems based on backstepping approach

“…The latter makes system operation very difficult, deteriorate the performance of the feedback-based control function and can even lead to instability [23,24]. Due to their ability to stabilize structured and unstructured uncertain systems, fuzzy control and neural network approaches are considered as powerful instruments for the control of the robotic systems [25][26][27][28][29]. In [11], an adaptive controller is introduced which is capable of synchronization in the presence of dynamic uncertainties without the appearance of any delay in information from the communication channel.…”