Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Pre-compensation Strategy for Tracking Error and Contour Error by Using  Cross-Coupled Control based on Improved PSO Optimization Fuzzy-PID Control

View through CrossRef
Abstract This paper primarily investigates how to enhance the tracking accuracy of servo systems and the contour performance of precision machining. Leveraging the characteristics of the servo structure, a tracking error prediction model is established. The contour error model, based on the spatial relationship between tracking error and contour error, simplifies complex traditional iterative calculations and offers greater flexibility. To achieve higher contour accuracy, a novel precompensation control strategy for cross-coupling of tracking error and contour error is designed. This strategy employs an improved particle swarm optimization (PSO) to optimize the fuzzy PID method for adjusting compensation values. The strategy optimizes the parameters of the central fuzzy PID controller through an improved particle swarm optimization algorithm to adjust and allocate compensation values to each axis. It takes into account the mismatch caused by the inertial parameters of each axis, ensuring precise control over contour errors. Compared to other crosscoupling control methods, this approach significantly improves tracking performance and reduces contour errors. Finally, the effectiveness of the proposed strategy is verified through experiments and simulations.
Title: Pre-compensation Strategy for Tracking Error and Contour Error by Using  Cross-Coupled Control based on Improved PSO Optimization Fuzzy-PID Control
Description:
Abstract This paper primarily investigates how to enhance the tracking accuracy of servo systems and the contour performance of precision machining.
Leveraging the characteristics of the servo structure, a tracking error prediction model is established.
The contour error model, based on the spatial relationship between tracking error and contour error, simplifies complex traditional iterative calculations and offers greater flexibility.
To achieve higher contour accuracy, a novel precompensation control strategy for cross-coupling of tracking error and contour error is designed.
This strategy employs an improved particle swarm optimization (PSO) to optimize the fuzzy PID method for adjusting compensation values.
The strategy optimizes the parameters of the central fuzzy PID controller through an improved particle swarm optimization algorithm to adjust and allocate compensation values to each axis.
It takes into account the mismatch caused by the inertial parameters of each axis, ensuring precise control over contour errors.
Compared to other crosscoupling control methods, this approach significantly improves tracking performance and reduces contour errors.
Finally, the effectiveness of the proposed strategy is verified through experiments and simulations.

Related Results

Solar Hydrogen Variable Speed Control of Induction Motor Based on Chaotic Billiards Optimization Technique
Solar Hydrogen Variable Speed Control of Induction Motor Based on Chaotic Billiards Optimization Technique
This paper introduces a brand-new, inspired optimization algorithm (the chaotic billiards optimization (C-BO) approach) to effectively develop the optimal parameters for fuzzy PID ...
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A vast variety of neural network (NN)–based controllers use indirect adaptive control structures for their implementation, which primarily aims at estimating the nonlinear dynamics...
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Abstract. Fuzzy Inference System requires several stages to get the output, 1) formation of fuzzy sets, 2) formation of rules, 3) application of implication functions, 4) compositi...
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Here in this paper, we provide characterizations of fuzzy quasi-ideal in terms of level and strong level subsets. Along with it, we provide expression for the generated fuzzy quasi...
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
An increasing number of applications of the electromechanical actuator (EMA) in the flight vehicle control system have required accurate dynamic models and control strategies. This...
Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy
Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy
Abstract To propose a clinically oriented quantitative metric, Hu similarity coefficient (HSC), to evaluate contour quality, gauge the performance of auto contour...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...

Back to Top