Optimal control model for an index finger exoskeleton of rehabilitation

Hanzhe Zhang

doi:10.1117/12.2680844

23 May 2023 Optimal control model for an index finger exoskeleton of rehabilitation

Hanzhe Zhang

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126454Q (2023) https://doi.org/10.1117/12.2680844
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

To improve the therapeutic effect of the rehabilitation hand exoskeleton robot, this paper analyzes the movable range of each index finger joint based on the structure of the newly proposed rehabilitation hand exoskeleton robot. However, in the actual medical process, the stiffness and damping coefficient of the series elastic actuator need to change with the change of the situation, and the ordinary PID controller obviously cannot meet the medical needs. Therefore, based on the Back-Propagation nerve network algorithm and genetic algorithm, this paper designs a PID controller based on nerve network optimization using a genetic algorithm to control the series elastic driver system, and through MatLab and Simulink modeling analysis, the controller can obtain better PID parameters under various conditions through Backpropagation nerve network training according to system errors. The results show that the performance of a PID controller under a Back-Propagation nerve network is better than that of an ordinary PID controller, the peak time of the output signal and the time to reach stability are shorter, but the randomness of initial weight will affect the performance, if the system coefficient is changed frequently, the BP-PID controller will have excessive overthrow, so the genetic algorithm is used to optimize the initial weight of the Back-Propagation nerve network. The results show that the BP-PID controller using the genetic algorithm can achieve better tracking performance of the input signal and has better adaptability to the parameter change of the system. The controller can improve the control precision of torque and improve the therapeutic effect.

Citation Download Citation

Hanzhe Zhang "Optimal control model for an index finger exoskeleton of rehabilitation", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126454Q (23 May 2023); https://doi.org/10.1117/12.2680844

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KEYWORDS

Nerve

Genetic algorithms

Mathematical optimization

Control systems

Elasticity

3D modeling

Education and training

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