Walking aid electrostimulation fine control method based on genetic-ant colony fusion fuzzy controller

Abstract

The invention relates to the rehabilitation training field and aims to optimize the quantifying factor and scale factor of a fuzzy controller and the fuzzy control rules, then control the current mode of an FES system accurately, stably and instantly and effectively improve the accuracy and stability of the FES system. The technical scheme adopted by the invention is as follows: the walking aid electrostimulation fine control method based on genetic-ant colony fusion fuzzy controller comprises the following steps: firstly, converting the selection of fuzzy control decision variable to the combinational optimization problem adapting to the genetic-ant colony algorithm, coding the decision variable, randomly generating a chromosome composed of n-numbered individuals; secondly, using the genetic algorithm to generate the initial pheromone distribution of the ant algorithm, utilizing the ant colony algorithm to randomly search and optimize the membership function, quantifying factor and scale factor of the fuzzy controller; and performing repeated self-learning and self-regulating according to the system output, and finally using the processes in the FES system. The invention is mainly used for rehabilitation training.

Description

technical field [0001] The invention relates to the field of rehabilitation training, in particular to the measurement of the load-carrying force of a walker, and in particular to a precise control method for electric stimulation of walking aids based on a genetic ant colony fusion fuzzy controller. Background technique [0002] Functional Electrical Stimulation (FES) is a technology that stimulates limb motor muscles and peripheral nerves through current pulse sequences to effectively restore or reconstruct part of the motor function of paraplegic patients. At present, due to the weak regeneration ability of the spinal cord, there is no effective treatment method that can directly repair the injury for paralyzed patients with spinal cord injury. The implementation of functional rehabilitation training is an effective measure. According to statistics, the number of paralyzed patients with spinal cord injury is increasing year by year, and functional rehabilitation training i...

AI Technical Summary

Problems solved by technology

However, there is nothing that can be done about the use of feedback information in the system, so that when the solution reaches a certain range, a large number of powerless redundant iterations are often done, and the efficiency of finding an accurate solution is low.

The ant colony algorithm simulates the foraging behavior of ants in the biological world looking for the shortest path from the ant nest to the food source without any prompts. A population-based simulated evolutionary algorithm is proposed, which has strong adaptability, distributed parallel computing, and is easy for others The advantages of algorithm integration, but the lack of pheromone in the initial stage, the solution speed is slow

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