# Self-tuning trajectory tracking control for concrete pouring construction robots based on PID-NFTSMC and CPO algorithm

## TL;DR

This paper introduces a self-tuning control system for concrete pouring robots to improve accuracy and stability in construction.

## Contribution

A novel control strategy combining PID-NFTSMC with the CPO algorithm for adaptive trajectory tracking in construction robots.

## Key findings

- The PID-NFTSMC controller achieved maximum trajectory tracking errors of 0.098740, 0.105880, and 0.088740 for three joints.
- The control strategy demonstrated convergence times of 0.1553s, 0.1540s, and 0.0100s for the three joints.
- The approach improved precision and robustness against disturbances in concrete pouring robots.

## Abstract

This paper presented a self-tuning trajectory tracking control strategy for concrete pouring construction robots operating under external disturbances and system uncertainties. To enhance operational stability and robustness, the study integrated proportional-integral-derivative (PID) control with nonsingular fast terminal sliding mode control (NFTSMC), enabling faster convergence to the desired trajectory and reduced steady-state errors. Additionally, the study employed the crested porcupine optimizer (CPO) algorithm to automatically optimize PID control gains and NFTSMC sliding surface parameters, ensuring adaptability across varying conditions. The proposed control strategy was validated through extensive simulations, demonstrating superior trajectory tracking performance. The PID-NFTSMC controller achieved a maximum trajectory tracking error of 0.098740 and a root-mean-square (RMS) error of 0.007405 for Joint 1. For Joint 2 and Joint 3, the proposed controller exhibited maximum errors of 0.105880 and 0.088740, with RMS errors of 0.009859 and 0.007605, respectively. The convergence time for three joints was 0.1553s, 0.1540s and 0.0100s respectively. These results confirmed that concrete pouring construction robots operating had fast and high accuracy trajectory tracking and robustness against external disturbances. The findings highlight the practical significance of this approach in improving the precision and reliability of concrete pouring construction robots.