Key Takeaways & Executive Findings
- •• Proposes an observer-based fuzzy adaptive control (OBFAC) scheme for pneumatic polishing end-actuators to enhance force control accuracy under uncertain dynamic contact models. • Integrates a fuzzy state observer and fuzzy logic approximation to handle unmeasured states and nonlinearities, improving robustness and control performance. • Utilizes an integral barrier Lyapunov function to guarantee state constraints, ensuring safe and stable operation during polishing. • Experimental validation on a pneumatic polishing platform demonstrates superior tracking performance of OBFAC over existing control schemes, highlighting its practical applicability.
Abstract
In the field of flexible polishing, the accuracy of contact force control directly affects processing quality and material removal uniformity. However, the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors. To enhance responsiveness and control precision during the flexible polishing process, this study proposes an observer-based fuzzy adaptive control (OBFAC) scheme. To ensure control accuracy under an uncertain dynamic contact model, a fuzzy state observer is designed to estimate unmeasured states, while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance. Additionally, the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints. The stability of the proposed control scheme is analyzed using the Lyapunov function, and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios. Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.
1. Introduction
Aerospace and deep space exploration technologies impose stringent requirements on the performance and reliability of components [1, 2]. Polishing is a critical process in precision machining, significantly improving surface finish and component accuracy while reducing potential failures due to surface defects. It plays a crucial role in intelligent manufacturing and ultra-precision component processing [3–5]. Pneumatic systems are widely utilized as end actuators in polishing systems due to their ability to achieve flexible and compliant contact, preventing damage to high-precision components during machining [6, 7]. However, the inherent time delays, state limitations, and non-linear effects of pneumatic systems can compromise the accuracy of contact force control between the end actuator and the component during the polishing process. These limitations can result in over-polishing and under-polishing, ultimately affecting product quality [8, 9].
Currently, achieving precise control of the output force of polishing systems has garnered significant research attention, with high-precision and low-damage flexible polishing emerging as a prominent research direction in manufacturing and processing [10–13]. In the domain of pneumatic system output force control, numerous studies have sought to address the challenges of slow response times and low control precision [14, 15]. For instance, Hua et al. [16] proposed a neural network predictive proportional-integral-derivative (NNP-PID) control strategy to facilitate fast prediction and precise control of pneumatic actuator output force, mitigating the hysteresis effects present in pneumatic systems. Similarly, Hong et al. [17] introduced a sliding mode control (SMC) method based on a high-gain observer (HGO) to address cylinder friction and valve dead zone effects in pneumatic systems, enhancing control algorithms for blade polishing machining, which addressed the previous challenges in achieving precise pneumatic polishing system control. However, polishing applications impose more stringent requirements on polishing force control of the end-effector tool to ensure consistent machining accuracy and material removal. Unlike general pneumatic system force control, polishing involves dynamic contact and complex disturbances that must be considered. Specifically, the polishing force must be adjusted rapidly in real-time to prevent issues such as component damage caused by delayed force adjustments. Additionally, the uncertain dynamic contact model associated with polishing increases control complexity. Current control algorithms have limited applicability in such scenarios. Therefore, in polishing applications, lever
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Zhiguo Yang, Wenbo Zhao, Jiange Kou, Yushan Ma, Yixuan Wang, Yan Shi (2025). Observer-based Adaptive Fuzzy Force Control for the Pneumatic Polishing System End-actuator with Uncertain Dynamic Contact Model. Chinese Journal of Mechanical Engineering. https://doi.org/10.1186/s10033-025-01317-4
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Frequently Asked Questions
What is the main contribution of this paper?
The paper proposes an observer-based fuzzy adaptive control (OBFAC) scheme for pneumatic polishing end-actuators to improve force control accuracy under uncertain dynamic contact models, addressing challenges like hysteresis and nonlinearities.
How does the proposed control scheme handle uncertainties?
It uses a fuzzy state observer to estimate unmeasured states and fuzzy logic to approximate uncertain nonlinear functions, ensuring robust performance without precise model knowledge.
What experimental validation was performed?
A pneumatic polishing experimental platform was constructed, and polishing contact force control experiments were conducted under multiple scenarios, demonstrating superior tracking performance compared to existing control schemes.
What is the significance of the integral barrier Lyapunov function?
It ensures that all system states remain within predefined constraints, enhancing safety and stability during the polishing process.
What are the potential applications of this research?
The research is applicable to precision polishing in aerospace, deep space exploration, and other high-precision manufacturing fields where consistent material removal and surface quality are critical.
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