scholarly journals RBF Neural Network Based Sliding Mode Control of a Lower Limb Exoskeleton Suit

2014 ◽  
Vol 60 (6) ◽  
pp. 437-446 ◽  
Author(s):  
Shengli Song ◽  
Xinglong Zhang ◽  
Zhitao Tan
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Lower Limb ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Lower Limb Exoskeleton ◽  
Mode Control

Event driven sliding mode control of a lower limb exoskeleton based on a continuous neural network electromyographic signal classifier

Mechatronics ◽  
2020 ◽  
Vol 72 ◽  
pp. 102451
Author(s):  
Dusthon Llorente-Vidrio ◽  
Rafael Pérez-San Lázaro ◽  
Mariana Ballesteros ◽  
Iván Salgado ◽  
David Cruz-Ortiz ◽  
...  
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Lower Limb ◽  
Sliding Mode ◽  
Lower Limb Exoskeleton ◽  
Mode Control ◽  
Event Driven ◽  
Electromyographic Signal

Design of Intelligent Controller for Ship Motion with Input Saturation Based on Optimized Radial Basis Function Neural Network

2020 ◽  
Vol 13 ◽  
Author(s):  
Renqiang Wang ◽  
Qinrong Li ◽  
Shengze Miao ◽  
Keyin Miao ◽  
Hua Deng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Sliding Mode Control ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Input Saturation ◽  
Ship Motion ◽  
Mode Control

Abstract: The purpose of this paper was to design an intelligent controller of ship motion based on sliding mode control with a Radial Basis Function (RBF) neural network optimized by the genetic algorithm and expansion observer. First, the improved genetic algorithm based on the distributed genetic algorithm with adaptive fitness and adaptive mutation was used to automatically optimize the RBF neural network. Then, with the compensation designed by the RBF neural network, anti-saturation control was realized. Additionally, the intelligent control algorithm was introduced by Sliding Mode Control (SMC) with the stability theory. A comparative study of sliding mode control integrated with the RBF neural network and proportional–integral–derivative control combined with the fuzzy optimization model showed that the stabilization time of the intelligent control system was 43.75% faster and the average overshoot was reduced by 52% compared with the previous two attempts. Background: It was known that the Proportional-Integral-Derivative (PID) control and self-adaptation control cannot really solve the problems of frequent disturbance from external wind and waves, as well as the problems with ship nonlinearity and input saturation. So, the previous ship motion controller should be transformed by advanced intelligent technology, on the basis of referring to the latest relevant patent design methods. Objective: An intelligent controller of ship motion was designed based on optimized Radial Basis Function Neural Network (RBFNN) in the presence of non-linearity, uncertainty, and limited input. Methods: The previous ship motion controller was remodeled based on Sliding Mode Control (SMC) with RBFNN optimized by improved genetic algorithm and expansion observer. The intelligent control algorithm integrated with genetic neural network solved the problem of system model uncertainty, limited control input, and external interference. Distributed genetic with adaptive fitness and adaptive mutation method guaranteed the adequacy of search and the global optimal convergence results, which enhanced the approximation ability of RBFNN. With the compensation designed by the optimized RBFNN, it was realized anti-saturation control. The chattering caused by external disturbance in SMC controller was reduced by the expansion observer. Results: A comparative study with RBFNN-SMC control and fuzzy-PID control, the stabilization time of the intelligent control system was 43.75% faster, the average overshoot was reduced by 52%, compared to the previous two attempts. Conclusion: The intelligent control algorithm succeed in dealing with the problems of nonlinearity, uncertainty, input saturation, and external interference. The intelligent control algorithm can be applied into research and development ship steering system, which would be created a new patent.

Design of M-G modal space sliding mode control for lower limb exoskeleton robot driven by electrical actuators

Mechatronics ◽  
2021 ◽  
Vol 78 ◽  
pp. 102610
Author(s):  
Jinsong Zhao ◽  
Tao Yang ◽  
Zhilei Ma ◽  
Chifu Yang ◽  
Zhipeng Wang ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Lower Limb ◽  
Sliding Mode ◽  
Lower Limb Exoskeleton ◽  
Mode Control ◽  
Exoskeleton Robot ◽  
Modal Space

Fault tolerant control based on backstepping nonsingular terminal integral sliding mode and impedance control for a lower limb exoskeleton

2021 ◽  
pp. 095440622110357
Author(s):  
Majied Mokhtari ◽  
Mostafa Taghizadeh ◽  
Pegah Ghaf Ghanbari
Keyword(s):  
Sliding Mode Control ◽  
Lower Limb ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Impedance Control ◽  
Fault Tolerant Control ◽  
Integral Type ◽  
Lower Limb Exoskeleton ◽  
Mode Control ◽  
Control Scheme

In this paper, an active fault-tolerant control scheme is proposed for a lower limb exoskeleton, based on hybrid backstepping nonsingular fast terminal integral type sliding mode control and impedance control. To increase the robustness of the sliding mode controller and to eliminate the chattering, a nonsingular fast terminal integral type sliding surface is used, which ensures finite time convergence and high tracking accuracy. The backstepping term of this controller guarantees global stability based on Lyapunov stability criterion, and the impedance control reduces the interaction forces between the user and the robot. This controller employs a third order super twisting sliding mode observer for detecting, isolating ad estimating sensor and actuator faults. Motion stability based on zero moment point criterion is achieved by trajectory planning of waist joint. Furthermore, the highest level of stability, minimum error in tracking the desired joint trajectories, minimum interaction force between the user and the robot, and maximum system capability to handle the effect of faults are realized by optimizing the parameters of the desired trajectories, the controller and the observer, using harmony search algorithm. Simulation results for the proposed controller are compared with the results obtained from adaptive nonsingular fast terminal integral type sliding mode control, as well as conventional sliding mode control, which confirm the outperformance of the proposed control scheme.

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