Research on Trajectory Tracking of a Two-Link Robot Based on Hybrid GA-SQP Optimized Feedforward-PID Control

The increasing deployment of robotic systems in industrial applications has driven widespread use of two-link robots, valued for their high speed and precision. However, their inherent nonlinear dynamics and strong coupling effects present substantial challenges to achieving high-precision trajectory tracking. To address these issues, this paper proposes a feedforwardPID control strategy optimized using a hybrid Genetic AlgorithmSequential Quadratic Programming (GASQP) approach. The proposed method combines the anticipatory capabilities of feedforward control with the corrective feedback of PID control, enabling automatic and efficient parameter tuning. Simulation results demonstrate that, in comparison to conventional PID control, the proposed approach enhances trajectory tracking accuracy by approximately 39.61%. Specifically, the GASQP-optimized controller reduces the Root Mean Square Error (RMSE) to 0.48mm for an Archimedean spiral trajectory, and further to 0.01mm for a Sine-like trajectory, confirming its adaptability across various trajectory profiles. Torque analysis further highlights the complementary interaction between feedforward and PID components, substantiating the methods effectiveness. These results underscore the proposed strategys potential to significantly improve trajectory tracking accuracy and robustness for two-link robots, especially in complex dynamic environments.

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Publication Details

Journal
Applied and Computational Engineering
Published
2025-05-06
DOI
https://doi.org/10.54254/2755-2721/2025.22552
Primary Topic
Industrial Technology and Control Systems
Type
article
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article

Research on Trajectory Tracking of a Two-Link Robot Based on Hybrid GA-SQP Optimized Feedforward-PID Control

Keyu Wang
Applied and Computational Engineering
Industrial Technology and Control Systems
article

Research on Trajectory Tracking of a Two-Link Robot Based on Hybrid GA-SQP Optimized Feedforward-PID Control

Keyu Wang
article en

Abstract

The increasing deployment of robotic systems in industrial applications has driven widespread use of two-link robots, valued for their high speed and precision. However, their inherent nonlinear dynamics and strong coupling effects present substantial challenges to achieving high-precision trajectory tracking. To address these issues, this paper proposes a feedforwardPID control strategy optimized using a hybrid Genetic AlgorithmSequential Quadratic Programming (GASQP) approach. The proposed method combines the anticipatory capabilities of feedforward control with the corrective feedback of PID control, enabling automatic and efficient parameter tuning. Simulation results demonstrate that, in comparison to conventional PID control, the proposed approach enhances trajectory tracking accuracy by approximately 39.61%. Specifically, the GASQP-optimized controller reduces the Root Mean Square Error (RMSE) to 0.48mm for an Archimedean spiral trajectory, and further to 0.01mm for a Sine-like trajectory, confirming its adaptability across various trajectory profiles. Torque analysis further highlights the complementary interaction between feedforward and PID components, substantiating the methods effectiveness. These results underscore the proposed strategys potential to significantly improve trajectory tracking accuracy and robustness for two-link robots, especially in complex dynamic environments.

Applied and Computational EngineeringVol. 147(1)
Nanchang University (CN)
Openalex Percentile: Top 90%
Industrial Technology and Control Systems
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Research on Trajectory Tracking of a Two-Link Robot Based on Hybrid GA-SQP Optimized Feedforward-PID Control — Keyu Wang · Applied and Computational Engineering (2025) | TGRS Research Map | TGRS