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

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.