# Sliding-mode control based on prescribed performance function and its application to a SEA-Based lower limb exoskeleton

**Authors:** Feilong Zhang, Tian Wang, Liang Zhang, Enming Shi, Chengchao Wang, Ning Li, Yu Lu, Bi Zhang

PMC · DOI: 10.3389/frobt.2025.1534040 · Frontiers in Robotics and AI · 2025-03-04

## TL;DR

This paper introduces a new sliding-mode control method with a performance function for exoskeletons, improving system adaptability and response.

## Contribution

The novel approach separates the controller into adaptable parts, allowing integration of model-based control for better performance.

## Key findings

- The proposed method maintains tracking error within a predefined convergence zone.
- Introducing a penalty constant enhances system smoothness or response speed when the model is inaccurate.
- Experiments on a lower limb exoskeleton validate the effectiveness of the new control method.

## Abstract

A sliding-mode control based on a prescribed performance function is proposed for discrete-time single-input single-output systems. The controller design aims to maintain the tracking error in a predefined convergence zone described by a performance function. However, due to the fixed structure of the controller, the applicability and universality of this method are limited. To address this issue, we separate the controller into two parts and analyze the principle of the prescribed performance control (PPC) method. Then we can replace the linear part of the controller with model-based control methods to adapt to the specific characteristics of the controlled system. Compared with current works, when the established system model is inaccurate, we can enhance the smoothness or response speed of the system by introducing a penalty constant to alter the system’s transient characteristics while the tracking error is within the prescribed domain. Finally, numerical comparison simulations and a lower limb exoskeleton experiment illustrate the established results and the effectiveness of the proposed method.

## Full-text entities

- **Diseases:** PPC (MESH:C536209)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

14 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11913672/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/PMC11913672/full.md

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Source: https://tomesphere.com/paper/PMC11913672